PREFIX obo:
PREFIX rdf:
PREFIX rdfs:
PREFIX xsd:
obo:STATO_0000694 a rdfs:Class ;
rdfs:label "probability distribution standard deviation"@en ;
rdfs:comment "A probability distribution attribute that is the square root of the distribution variance."@en ;
rdfs:subClassOf obo:STATO_0000237 .
obo:OBI_0001938 a rdf:Property ;
rdfs:label "has value specification" ;
rdfs:comment "A relation between an information content entity and a value specification that specifies its value." ;
rdfs:domain obo:IAO_0000030 ;
rdfs:range obo:OBI_0001933 ;
rdfs:subPropertyOf obo:BFO_0000051 .
obo:STATO_0000403 a rdf:Property ;
rdfs:label "estimate of"@en ;
rdfs:comment "Relationship between a parameter of a model and the estimate produced by estimation process as used in statistical modeling."@en ;
rdfs:domain obo:STATO_0000039 ;
rdfs:range obo:STATO_0000034 .
obo:RO_0000056 a rdf:Property ;
rdfs:label "participates in"@en ;
rdfs:comment "a relation between a continuant and a process, in which the continuant is somehow involved in the process"@en ;
rdfs:domain obo:BFO_0000002 ;
rdfs:range obo:BFO_0000003 .
obo:IAO_0000235 a rdf:Property ;
rdfs:label "denoted by"@en ;
rdfs:comment "inverse of the relation 'denotes'"@en ;
rdfs:domain obo:BFO_0000001 ;
rdfs:range obo:IAO_0000030 .
obo:IAO_0000219 a rdf:Property ;
rdfs:label "denotes"@en ;
rdfs:comment "denotes is a primitive, instance-level, relation obtaining between an information content entity and some portion of reality. Denotation is what happens when someone creates an information content entity E in order to specifically refer to something. The only relation between E and the thing is that E can be used to 'pick out' the thing. This relation connects those two together. Freedictionary.com sense 3: To signify directly; refer to specifically"@en ;
rdfs:domain obo:IAO_0000030 ;
rdfs:range obo:BFO_0000001 ;
rdfs:subPropertyOf obo:IAO_0000136 .
obo:IAO_0000136 a rdf:Property ;
rdfs:label "is about"@en ;
rdfs:comment "is_about is a (currently) primitive relation that relates an information artifact to an entity."@en ;
rdfs:domain obo:IAO_0000030 ;
rdfs:range .
obo:STATO_0000557 a rdf:Property ;
rdfs:label "computed from" ;
rdfs:comment "computed_from is a relation between 2 information content entity denoting how one is derived from another on through the application of a data transformation or computation process."@en ;
rdfs:domain obo:IAO_0000030 ;
rdfs:range obo:IAO_0000030 .
obo:OBI_0000314 a rdf:Property ;
rdfs:label "is_proxy_for"@en ;
rdfs:comment "A relation between continuant instances c1 and c2 where within an experiment/ protocol application, measurement of c1 is used to determine what a measurement of c2 would be."@en ;
rdfs:domain obo:BFO_0000002 ;
rdfs:range obo:BFO_0000002 .
obo:RO_0000058 a rdf:Property ;
rdfs:label "is concretized as"@en ;
rdfs:comment "A relationship between a generically dependent continuant and a specifically dependent continuant, in which the generically dependent continuant depends on some independent continuant in virtue of the fact that the specifically dependent continuant also depends on that same independent continuant. A generically dependent continuant may be concretized as multiple specifically dependent continuants."@en ;
rdfs:domain obo:BFO_0000031 ;
rdfs:range obo:BFO_0000020 .
obo:STATO_0000485 a rdfs:Class ;
rdfs:label "estimated breeding value"@en ;
rdfs:comment "the estimated breeding value of an organism is a data item computed to estimate the true breeding value defined as genetic merit of an organism, half of which will be passed on to its progeny. While the exact breeding value can not been known, for performance traits it is possible to make good estimates. These estimates are called Estimated Breeding Values (EBVs). EBVs are expressed in the units of measurement for each particular trait. These estimates are output of various estimation methods which differ depending on the underlying assumptions (equal variance of marker effect, all markers contributing to the trait) , the mathemical methods used (bayesian or non-bayesians) and the genetic inheritance models being considered (additive, dominant, epistatic) selected by the analysts."@en ;
rdfs:subClassOf obo:STATO_0000471 .
obo:OBI_0000312 a rdf:Property ;
rdfs:label "is_specified_output_of"@en ;
rdfs:comment "A relation between a continuant participating in a planned process. The presence of the continuant at the end of the process is explicitly specified in the objective specification which the process realizes the concretization of."@en ;
rdfs:domain obo:BFO_0000002 ;
rdfs:range obo:OBI_0000011 ;
rdfs:subPropertyOf obo:RO_0000056 .
obo:OBI_0000094 a rdfs:Class ;
rdfs:label "material processing"@en ;
rdfs:comment "A planned process which results in physical changes in a specified input material"@en ;
rdfs:subClassOf obo:OBI_0000011 .
obo:BFO_0000062 a rdf:Property ;
rdfs:label "preceded by"@en ;
rdfs:domain obo:BFO_0000003 ;
rdfs:range obo:BFO_0000003 .
obo:BFO_0000063 a rdf:Property ;
rdfs:label "precedes"@en ;
rdfs:domain obo:BFO_0000003 ;
rdfs:range obo:BFO_0000003 ;
rdfs:subPropertyOf obo:RO_0002222 .
obo:OBI_0000299 a rdf:Property ;
rdfs:label "has_specified_output"@en ;
rdfs:comment "A relation between a planned process and a continuant participating in that process. The presence of the continuant at the end of the process is explicitly specified in the objective specification which the process realizes the concretization of."@en ;
rdfs:domain obo:OBI_0000011 ;
rdfs:range obo:BFO_0000040 , obo:IAO_0000027 , obo:BFO_0000002 , obo:STATO_0000087 , obo:STATO_0000228 ;
rdfs:subPropertyOf obo:RO_0000057 .
obo:OBI_0000417 a rdf:Property ;
rdfs:label "achieves_planned_objective" ;
rdfs:comment "This relation obtains between a planned process and a objective specification when the criteria specified in the objective specification are met at the end of the planned process." ;
rdfs:domain obo:OBI_0000011 ;
rdfs:range obo:IAO_0000005 .
obo:OBI_0000293 a rdf:Property ;
rdfs:label "has_specified_input"@en ;
rdfs:comment "A relation between a planned process and a continuant participating in that process that is not created during the process. The presence of the continuant during the process is explicitly specified in the plan specification which the process realizes the concretization of."@en ;
rdfs:domain obo:OBI_0000011 ;
rdfs:range obo:BFO_0000040 , obo:IAO_0000027 , obo:BFO_0000002 , obo:STATO_0000003 , obo:OBI_0000118 ;
rdfs:subPropertyOf obo:RO_0000057 .
obo:BFO_0000055 a rdf:Property ;
rdfs:label "realizes"@en ;
rdfs:comment "Paraphrase of elucidation: a relation between a process and a realizable entity, where there is some material entity that is bearer of the realizable entity and participates in the process, and the realizable entity comes to be realized in the course of the process" ;
rdfs:domain obo:BFO_0000015 ;
rdfs:range obo:BFO_0000017 .
obo:RO_0000057 a rdf:Property ;
rdfs:label "has participant"@en ;
rdfs:comment "a relation between a process and a continuant, in which the continuant is somehow involved in the process"@en ;
rdfs:domain obo:BFO_0000003 ;
rdfs:range obo:BFO_0000002 .
obo:STATO_0000471 a rdfs:Class ;
rdfs:label "estimate" ;
rdfs:comment "a estimate is a data item which is computed from a dataset to provide an approximated value (an estimator) for a 'statistical parameter' (a 'characteristics/parameter' of the true underlying distribution) of a real population." ;
rdfs:subClassOf obo:STATO_0000039 .
obo:STATO_0000098 a rdfs:Class ;
rdfs:label "two sample Hotelling T2 test"@en ;
rdfs:comment "Hotelling's T2 test is a statistical test which is a generalization of Student's T-test to a assess if the means of a set of variables remains unchanged when studying 2 populations. It is a type of multivariate analysis"@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000279 .
obo:BFO_0000051 a rdf:Property ;
rdfs:label "has part"@en ;
rdfs:comment "a core relation that holds between a whole and its part"@en ;
rdfs:range , obo:OBI_0000938 .
obo:STATO_0000150 a rdfs:Class ;
rdfs:label "minimum observed value" ;
rdfs:comment "a minimum value is a data item which denotes the smallest value found in a dataset or resulting from a calculation."@en ;
rdfs:subClassOf obo:STATO_0000039 .
obo:OBI_0500003 a rdfs:Class ;
rdfs:label "cross over design"@en ;
rdfs:comment "a repeated measure design which ensures that experimental units receive, in sequence, the treatment (or the control), and then, after a specified time interval (aka *wash-out periods*), switch to the control (or treatment). In this design, subjects (patients in human context) serve as their own controls, and randomization may be used to determine the ordering which a subject receives the treatment and control"@en ;
rdfs:subClassOf obo:OBI_0000115 , obo:OBI_0500002 , obo:OBI_0500020 , obo:STATO_0000046 .
obo:STATO_0000001 a rdf:Property ;
rdfs:label "declares"@en ;
rdfs:comment "property to indicate that a design declares a variable; the inverse property is 'is declared by'"@en ;
rdfs:domain obo:IAO_0000030 ;
rdfs:range ;
rdfs:subPropertyOf obo:IAO_0000136 .
obo:STATO_0000351 a rdfs:Class ;
rdfs:label "spatial gaussian geometric anisotropic covariance structure"@en ;
rdfs:comment "spatial gaussian geometric anisotropic covariance structure is a type of covariance structure characterized by its anisotropy, i.e., the variation of properties can be different in directions x and y, which is this case give gaussian features."@en ;
rdfs:subClassOf obo:STATO_0000346 .
obo:STATO_0000205 a rdf:Property ;
rdfs:label "is denoted by"@en ;
rdfs:comment "Inverse relation of 'denotes', where denotation is what happens when someone creates an information content entity E in order to specifically refer to something (from 'denotes' definition)."@en ;
rdfs:range .
obo:OBI_0000295 a rdf:Property ;
rdfs:label "is_specified_input_of"@en ;
rdfs:comment "The inverse of the relation between a planned process and a continuant participating in that process that is not created during the process. The presence of the continuant during the process is explicitly specified in the plan specification which the process realizes the concretization of."@en ;
rdfs:domain obo:BFO_0000002 ;
rdfs:range obo:OBI_0000011 ;
rdfs:subPropertyOf obo:RO_0000056 .
obo:BFO_0000050 a rdf:Property ;
rdfs:label "part of"@en ;
rdfs:comment "a core relation that holds between a part and its whole"@en ;
rdfs:seeAlso ;
rdfs:range .
obo:STATO_0000341 a rdf:Property ;
rdfs:label "is model for"@en ;
rdfs:comment "This property is the inverse relationship of 'is model by' and represents the relationship between a dependent variable and an statistical model."@en ;
rdfs:domain obo:STATO_0000107 ;
rdfs:range obo:OBI_0000751 .
obo:STATO_0000088 a rdfs:Class ;
rdfs:label "study group population size"@en ;
rdfs:comment "statistical sample size is a count evaluating the number of individual experimental units"@en ;
rdfs:subClassOf obo:STATO_0000047 .
obo:OBI_0000371 a rdfs:Class ;
rdfs:label "heat function"@en ;
rdfs:comment "A heat function is a function that increases the internal kinetic energy of a material"@en ;
rdfs:subClassOf obo:BFO_0000034 .
obo:RO_0000059 a rdf:Property ;
rdfs:label "concretizes"@en ;
rdfs:comment "A relationship between a specifically dependent continuant and a generically dependent continuant, in which the generically dependent continuant depends on some independent continuant in virtue of the fact that the specifically dependent continuant also depends on that same independent continuant. Multiple specifically dependent continuants can concretize the same generically dependent continuant."@en ;
rdfs:domain obo:BFO_0000020 ;
rdfs:range obo:BFO_0000031 .
obo:RO_0000079 a rdf:Property ;
rdfs:label "function of"@en ;
rdfs:comment "a relation between a function and an independent continuant (the bearer), in which the function specifically depends on the bearer for its existence"@en ;
rdfs:domain obo:BFO_0000034 ;
rdfs:range ;
rdfs:subPropertyOf obo:RO_0000052 .
obo:BFO_0000054 a rdf:Property ;
rdfs:label "realized in"@en ;
rdfs:comment "Paraphrase of elucidation: a relation between a realizable entity and a process, where there is some material entity that is bearer of the realizable entity and participates in the process, and the realizable entity comes to be realized in the course of the process" ;
rdfs:domain obo:BFO_0000017 ;
rdfs:range obo:BFO_0000015 , obo:OBI_0000443 , obo:OBI_0600064 , obo:OBI_0000274 , obo:OBI_0000070 , obo:OBI_0000471 .
obo:STATO_0000574 a rdfs:Class ;
rdfs:label "center value" ;
rdfs:comment "The median is that value of the variate which divides the total frequency into two halves. The median is measure of central tendency of data. It is obtained by arranging the observations in order from smallest to largest value. If there is an odd number of observations, the median is the middle value. If there is an even number of observations, the median is the average of the two middle values." ;
rdfs:subClassOf obo:STATO_0000029 , obo:STATO_0000152 .
obo:STATO_0000474 a rdfs:Class ;
rdfs:label "Satterthwaite degree of freedom approximation"@en ;
rdfs:comment "Satterthwaite degree of freedom approximation is a type of degree of freedom approximation which is used to estimate an “effective degrees of freedom” for a probability distribution formed from several independent normal distributions where only estimates of the variance are known. It was originally developed by statistician Franklin E. Satterthwaite."@en ;
rdfs:subClassOf obo:STATO_0000472 .
obo:STATO_0000736 a rdfs:Class ;
rdfs:label "effect size for power calculation" ;
rdfs:comment "a data item used as input to a statistical test power calculation that represents the smallest difference from the value assumed under the null hypothesis that is used to conclude in favor of an alternative hypothesis." ;
rdfs:subClassOf obo:IAO_0000027 .
obo:STATO_0000058 a rdfs:Class ;
rdfs:label "goodness of fit hypothesis"@en ;
rdfs:comment "goodness of fit hypothesis is a null hypothesis stating that the distribution computed from the sample population fits a theoretical distribution or that a dataset can be correctly explained by a model"@en ;
rdfs:subClassOf obo:STATO_0000065 .
obo:STATO_0000129 a rdf:Property ;
rdfs:label "has value"@en ;
rdfs:comment "A relationship (data property) between an entity and its value."@en ;
rdfs:range .
obo:NCBITaxon_117571 a rdfs:Class ;
rdfs:label "Euteleostomi" ;
rdfs:subClassOf obo:NCBITaxon_7742 .
obo:RO_0001000 a rdf:Property ;
rdfs:label "derives from"@en ;
rdfs:comment "a relation between two distinct material entities, the new entity and the old entity, in which the new entity begins to exist when the old entity ceases to exist, and the new entity inherits the significant portion of the matter of the old entity"@en ;
rdfs:domain obo:BFO_0000004 ;
rdfs:range obo:BFO_0000004 .
obo:RO_0001025 a rdf:Property ;
rdfs:label "located in"@en ;
rdfs:comment "a relation between two independent continuants, the target and the location, in which the target is entirely within the location"@en ;
rdfs:domain obo:BFO_0000004 ;
rdfs:range .
obo:RO_0000087 a rdf:Property ;
rdfs:label "has role"@en ;
rdfs:comment "a relation between an independent continuant (the bearer) and a role, in which the role specifically depends on the bearer for its existence"@en ;
rdfs:domain obo:BFO_0000004 ;
rdfs:range obo:BFO_0000023 ;
rdfs:subPropertyOf obo:RO_0000053 .
obo:RO_0000085 a rdf:Property ;
rdfs:label "has function"@en ;
rdfs:comment "a relation between an independent continuant (the bearer) and a function, in which the function specifically depends on the bearer for its existence"@en ;
rdfs:domain obo:BFO_0000004 ;
rdfs:range obo:BFO_0000034 ;
rdfs:subPropertyOf obo:RO_0000053 .
obo:STATO_0000728 a rdfs:Class ;
rdfs:label "date variable" ;
rdfs:comment "An interval variable for which allowable values represent a point in time on a calendar with a year, with or without a month, and with or without a day." ;
rdfs:subClassOf obo:STATO_0000727 .
obo:STATO_0000344 a rdf:Property ;
rdfs:label "has effect on"@en ;
rdfs:comment "'has effect on' is a special case of the 'is about' relationship to be used for mixed effect models"@en ;
rdfs:domain obo:STATO_0000258 ;
rdfs:range obo:STATO_0000258 ;
rdfs:subPropertyOf obo:IAO_0000136 .
obo:OBI_0000916 a rdfs:Class ;
rdfs:label "flow cytometry assay" ;
rdfs:comment "A cytometry assay in which an input cell population is put in solution, is passed by a laser, and optical sensors are used to detect scattering of the laser light and/or fluorescence of specific markers to count and characterize the particles in solution." ;
rdfs:subClassOf obo:OBI_0001977 .
obo:STATO_0000542 a rdfs:Class ;
rdfs:label "genomic estimated breeding value" ;
rdfs:comment "genomic estimated breeding value (GEBV) is an estimated breeding value derived from information in an organism DNA (genotype). GEBV is calculated differently to conventional Estimated Breeding Values using advanced modeling technique to deal with high dimensionality data." ;
rdfs:subClassOf obo:STATO_0000485 .
obo:STATO_0000069 a rdfs:Class ;
rdfs:label "number of degrees of freedom"@en ;
rdfs:comment "The number degree of freedom is a count evaluating the number of values in a calculation that can vary. In statistics, the number of degrees of freedom ν is equal to N-1 in the case of the direct measurement of a quantity estimated by the arithmetic mean of N independent observations."@en ;
rdfs:subClassOf obo:STATO_0000047 .
obo:STATO_0000338 a rdfs:Class ;
rdfs:label "breeding value estimation using genotype data"@en ;
rdfs:comment "breeding value estimation is a data transformation process aiming at computing breeding value estimates of an organism given a set of genomic (SNP) observations." ;
rdfs:subClassOf obo:STATO_0000337 .
obo:STATO_0000325 a rdfs:Class ;
rdfs:label "Akaike information criterion"@en ;
rdfs:comment """The Akaike information criterion (AIC) is a measure of the relative quality of a statistical model for a given set of data. As such, AIC provides a means for model selection. AIC is defined as:
AIC = 2K - 2log(L)
where K is the number of predictors and L is the maximized likelihood value.
AIC deals with the trade-off between the goodness of fit of the model and the complexity of the model. It is founded on information theory: it offers a relative estimate of the information lost when a given model is used to represent the process that generates the data. AIC does not provide a test of a model in the sense of testing a null hypothesis; i.e. AIC can tell nothing about the quality of the model in an absolute sense. If all the candidate models fit poorly, AIC will not give any warning of that."""@en ;
rdfs:subClassOf obo:IAO_0000109 .
obo:IAO_0000221 a rdf:Property ;
rdfs:label "is quality measurement of"@en ;
rdfs:comment "m is a quality measurement of q at t. When q is a quality, there is a measurement process p that has specified output m, a measurement datum, that is about q"@en ;
rdfs:domain obo:IAO_0000109 ;
rdfs:range obo:BFO_0000019 , obo:PATO_0000125 ;
rdfs:subPropertyOf obo:IAO_0000136 .
obo:STATO_0000516 a rdfs:Class ;
rdfs:label "minimax sampling"@en ;
rdfs:comment "In imbalanced datasets, where the sampling ratio does not follow the population statistics, one can resample the dataset in a conservative manner called minimax sampling. The minimax sampling has its origin in Anderson minimax ratio whose value is proved to be 0.5: in a binary classification, the class-sample sizes should be chosen equally. This ratio can be proved to be minimax ratio only under the assumption of LDA classifier with Gaussian distributions. The notion of minimax sampling is recently developed for a general class of classification rules, called class-wise smart classifiers."@en ;
rdfs:subClassOf obo:STATO_0000502 .
obo:STATO_0000531 a rdfs:Class ;
rdfs:label "prior probability distribution" ;
rdfs:comment "a prior probability distribution is a probability distribution used as input to a Bayesian model to represent a priori knowledge about a model parameter. Along with the acquired/observed data, it is used to compute a posterior distribution according to the Bayes theorem." ;
rdfs:subClassOf obo:STATO_0000225 .
obo:STATO_0000004 a rdf:Property ;
rdfs:label "is declared by"@en ;
rdfs:comment "property to indicate the variables declared by a design; the inverse property is 'declares'"@en ;
rdfs:range .
obo:BFO_0000034 a rdfs:Class ;
rdfs:label "function"@en ;
rdfs:subClassOf obo:BFO_0000016 .
obo:STATO_0000254 a rdfs:Class ;
rdfs:label "allele frequency" ;
rdfs:comment "The allele frequency is a data item which denotes the incidence of a gene variant in a population. It is calculated as a ratio, by dividing the number of copies of a particular allele by the number of copies of all alleles at the genetic place (locus) in a population."@en ;
rdfs:subClassOf obo:IAO_0000027 , obo:STATO_0000184 .
obo:STATO_0000259 a rdf:Property ;
rdfs:label "has denominator" ;
rdfs:comment "the relationship between a fraction and the number below the line (or divisor)"@en ;
rdfs:range , obo:STATO_0000627 .
obo:STATO_0000101 a rdf:Property ;
rdfs:label "has numerator" ;
rdfs:comment "the relationship between a fraction and the number above the line"@en ;
rdfs:range , obo:STATO_0000627 .
obo:BFO_0000017 a rdfs:Class ;
rdfs:label "realizable entity"@en ;
rdfs:comment "A specifically dependent continuant that inheres in continuant entities and are not exhibited in full at every time in which it inheres in an entity or group of entities. The exhibition or actualization of a realizable entity is a particular manifestation, functioning or process that occurs under certain circumstances."@en ;
rdfs:subClassOf obo:BFO_0000020 .
obo:STATO_0000590 a rdfs:Class ;
rdfs:label "median of the ratios corrected count" ;
rdfs:comment """median of the ratios corrected count is kind of count produced during an RNA-Seq data normalization procedure which corresponds to dividing counts by sample-specific size factors determined by median ratio of gene counts relative to geometric mean per gene.
It was first described by Anders and Huber in 2010 (https://doi.org/10.1186/gb-2010-11-10-r106)
Recommended use:
-\"median of the ratios corrected count\" is suited for Differential Expression analysis or between samples.
-\"median of the ratios corrected count\" is NOT suited for gene count comparisons within a sample.""" ;
rdfs:subClassOf obo:STATO_0000047 .
obo:UBERON_0000465 a rdfs:Class ;
rdfs:label "material anatomical entity" ;
rdfs:comment "Anatomical entity that has mass." ;
rdfs:subClassOf obo:BFO_0000040 .
obo:STATO_0000265 a rdfs:Class ;
rdfs:label "factor level"@en ;
rdfs:comment "A factor level is data item which corresponds to one of the value assumed by a factor or independent variable manipulated and set by the experimentalist. In the context of factorial design, a factor level is assumed to be or treated as a category in a categorical variable"@en ;
rdfs:subClassOf obo:IAO_0000027 .
obo:IAO_0000009 a rdfs:Class ;
rdfs:label "datum label"@en ;
rdfs:comment "A label is a symbol that is part of some other datum and is used to either partially define the denotation of that datum or to provide a means for identifying the datum as a member of the set of data with the same label"@en ;
rdfs:subClassOf obo:IAO_0000030 .
obo:OBI_0000649 a rdfs:Class ;
rdfs:label "data set of features"@en ;
rdfs:comment "A data set that is produced as the output of a descriptive statistical calculation data transformation and consists of producing a data set that represents one or more features of interest about the input data set."@en ;
rdfs:subClassOf obo:IAO_0000100 .
obo:STATO_0000509 a rdfs:Class ;
rdfs:label "systematic sampling"@en ;
rdfs:comment "systematic sampling is a process for collecting samples and assembling a statistical sample using a system or method (.e.g unequal probabilities, without replacement, fixed sample size), as opposed to a random sampling."@en ;
rdfs:subClassOf obo:STATO_0000502 .
obo:STATO_0000659 a rdfs:Class ;
rdfs:label "median time-to-event" ;
rdfs:comment "A median of values in which each value is the duration of time between the start of observation and the occurrence of an event." ;
rdfs:subClassOf obo:STATO_0000574 .
obo:OBI_0001331 a rdfs:Class ;
rdfs:label "transcription profiling identification objective"@en ;
rdfs:comment "A molecular feature identification objective that aims to characterize the abundance of transcripts"@en ;
rdfs:subClassOf obo:OBI_0000131 .
obo:OBI_0000833 a rdf:Property ;
rdfs:label "objective_achieved_by" ;
rdfs:comment "This relation obtains between a a objective specification and a planned process when the criteria specified in the objective specification are met at the end of the planned process." ;
rdfs:domain obo:IAO_0000005 ;
rdfs:range obo:OBI_0000011 .
obo:STATO_0000024 a rdfs:Class ;
rdfs:label "three dimensional cartesian coordinate system"@en ;
rdfs:comment "a three dimensional cartesian coordinate system is a cartesian coordinate system which defines 3 orthogonal one dimensional axes and which may be used to describe a 3 dimensional spatial region." ;
rdfs:subClassOf obo:STATO_0000009 .
obo:IAO_0000055 a rdfs:Class ;
rdfs:label "rule"@en ;
rdfs:comment "a rule is an executable which guides, defines, restricts actions"@en ;
rdfs:subClassOf obo:IAO_0000001 .
obo:STATO_0000283 a rdfs:Class ;
rdfs:label "negative binomial distribution"@en ;
rdfs:comment "negative binomial probability distribution is a discrete probability distribution of the number of successes in a sequence of Bernoulli trials before a specified (non-random) number of failures (denoted r) occur. The negative binomial distribution, also known as the Pascal distribution or Pólya distribution, gives the probability of r-1 successes and x failures in x+r-1 trials, and success on the (x+r)th trial."@en ;
rdfs:subClassOf obo:STATO_0000117 .
obo:STATO_0000052 a rdfs:Class ;
rdfs:label "Z-test"@en ;
rdfs:comment "Z-test is a statistical test which evaluate the null hypothesis that the means of 2 populations are equal and returns a p-value."@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000279 .
obo:OBI_0200172 a rdfs:Class ;
rdfs:label "partitioning objective"@en ;
rdfs:comment "A partitioning objective is a data transformation objective where the aim is to generate a collection of disjoint non-empty subsets whose union equals a non-empty input set."@en ;
rdfs:subClassOf obo:OBI_0200166 .
obo:STATO_0000206 a rdfs:Class ;
rdfs:label "RPKM-reads per kilobase of transcript per million fragments mapped"@en ;
rdfs:comment """RPKM is a kind of count which numbers the sequence reads found per kilobase of transcript reported to million of sequence reads. RPKM is a metric generated by ERANGE software tool as reported by Mortazi et al, in 2008.
The metric has been enhanced and replaced by FPKM to better take into account splice variant. FKPM uses a statistical model to perform the computation.
Recommended use:
-RPKM measure may be used for gene count comparisons within a sample.
-RPKM measure is NOT suited for between sample comparisons.
-RPKM measure is NOT suited for Differential Expression analysis."""@en ;
rdfs:subClassOf obo:STATO_0000047 .
obo:STATO_0000349 a rdfs:Class ;
rdfs:label "spatial linear geometric anisotropic covariance structure"@en ;
rdfs:comment "spatial linear geometric anisotropic covariance structure is a type of covariance structure characterized by its anisotropy, i.e., the variation of properties can be different in directions x and y, which is this case give linear features."@en ;
rdfs:subClassOf obo:STATO_0000346 .
obo:STATO_0000482 a rdfs:Class ;
rdfs:label "trait-specific relationship matrix best linear unbiaised prediction" ;
rdfs:comment "a data transformation which calculate estimates of genomic estimated breeding values (GEBVs) on an animal or plant model utilizing trait-specific marker information."@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000119 , obo:STATO_0000337 .
obo:STATO_0000013 a rdfs:Class ;
rdfs:label "two dimensional cartesian coordinate system"@en ;
rdfs:comment "a 2 dimensional cartesian coordinate system is a cartesian coordinate system which defines 2 orthogonal one dimensional axes and which may be used to describe a 2 dimensional spatial region." ;
rdfs:subClassOf obo:STATO_0000009 .
obo:OBI_0200042 a rdfs:Class ;
rdfs:label "hierarchical clustering"@en ;
rdfs:comment "A hierarchical clustering is a data transformation which achieves a class discovery objective, which takes as input data item and builds a hierarchy of clusters. The traditional representation of this hierarchy is a tree (visualized by a dendrogram), with the individual input objects at one end (leaves) and a single cluster containing every object at the other (root)."@en ;
rdfs:subClassOf obo:APOLLO_SV_00000796 , obo:OBI_0200175 .
obo:STATO_0000585 a rdfs:Class ;
rdfs:label "degree of freedom calculation" ;
rdfs:comment "degree of freedom calculation is a data transformation which is part of a stastical test and which aims to determine or estimate the number of degrees of freedom in a system." ;
rdfs:subClassOf obo:OBI_0200000 .
obo:OBI_0001573 a rdfs:Class ;
rdfs:label "DNA sequence data" ;
rdfs:comment "A sequence data item that is about the primary structure of DNA" ;
rdfs:subClassOf obo:OBI_0000973 .
obo:STATO_0000634 a rdfs:Class ;
rdfs:label "reciprocal of difference" ;
rdfs:comment "A statistic that is a quotient of one and a difference." ;
rdfs:subClassOf obo:STATO_0000039 .
obo:STATO_0000164 a rdfs:Class ;
rdfs:label "inter quartile range"@en ;
rdfs:comment """The interquartile range is a data item which corresponds to the difference between the upper quartile (3rd quartile) and lower quartile (1st quartile).
The interquartile range contains the second quartile or median.
The interquartile range is a data item providing a measure of data dispersion."""@en ;
rdfs:subClassOf obo:STATO_0000028 .
obo:STATO_0000307 a rdfs:Class ;
rdfs:label "treatment contrast"@en ;
rdfs:comment "treatment contrast is a contrast which allows to test how linear model coefficients of categorical variables are interpreted in case where the “first” level (aka, the baseline) is included into the intercept and all subsequent levels have a coefficient that represents their difference from the baseline."@en ;
rdfs:subClassOf obo:STATO_0000290 .
obo:STATO_0000193 a rdfs:Class ;
rdfs:label "study group population" ;
rdfs:comment "is a population whose individual members realize (may be expressed as) a combination of inclusion rule values specifications or resulting from a sampling process (e.g. recruitment followed by randomization to group) on which a number of measurements will be carried out, which may be used as input to statistical tests and statistical inference." ;
rdfs:subClassOf obo:OBI_0000181 .
obo:STATO_0000527 a rdfs:Class ;
rdfs:label "denominator degrees of freedom" ;
rdfs:comment "The degree of freedom denominator is the number of degrees of freedom that the estimate of variance used in the denominator is based on. It is one of the parameters for the F-distribution used to compute probabilities in analysis of variance." ;
rdfs:subClassOf obo:STATO_0000069 .
obo:STATO_0000579 a rdfs:Class ;
rdfs:label "improved Kernel PLS" ;
rdfs:comment "improved kernel PLS is a data transformation which implement a very fast kernel algorithm for updating PLS models in a recursive manner and for exponentially discounting past data." ;
rdfs:subClassOf obo:OBI_0200000 .
obo:STATO_0000243 a rdfs:Class ;
rdfs:label "box and whisker plot"@en ;
rdfs:comment "a box plot is a graph which plots datasets relying on their quartiles and the interquartile range to create the box and the whiskers."@en ;
rdfs:subClassOf obo:IAO_0000038 .
obo:OBI_0000880 a rdfs:Class ;
rdfs:label "RNA extract" ;
rdfs:comment "an extract which is the output of an extraction process in which RNA molecules are isolated from a specimen." ;
rdfs:subClassOf obo:OBI_0001010 .
obo:OBI_0000643 a rdf:Property ;
rdfs:label "has grain" ;
rdfs:comment "the relation of the cells in the finger of the skin to the finger, in which an indeterminate number of grains are parts of the whole by virtue of being grains in a collective that is part of the whole, and in which removing one granular part does not nec- essarily damage or diminish the whole. Ontological Whether there is a fixed, or nearly fixed number of parts - e.g. fingers of the hand, chambers of the heart, or wheels of a car - such that there can be a notion of a single one being missing, or whether, by contrast, the number of parts is indeterminate - e.g., cells in the skin of the hand, red cells in blood, or rubber molecules in the tread of the tire of the wheel of the car." ;
rdfs:range , obo:CL_0000010 ;
rdfs:subPropertyOf obo:BFO_0000051 .
obo:STATO_0000180 a rdfs:Class ;
rdfs:label "standard normal distribution"@en ;
rdfs:comment "standard normal distribution is a normal distribution with variance = 1 and mean=0"@en ;
rdfs:subClassOf obo:STATO_0000227 .
obo:OBI_0000832 a rdfs:Class ;
rdfs:label "measurement device" ;
rdfs:comment "A device in which a measure function inheres." ;
rdfs:subClassOf obo:OBI_0000968 .
obo:IAO_0000416 a rdfs:Class ;
rdfs:label "time measurement datum"@en ;
rdfs:comment "A scalar measurement datum that is the result of measuring a temporal interval"@en ;
rdfs:subClassOf obo:IAO_0000032 .
obo:IAO_0000004 a rdf:Property ;
rdfs:label "has measurement value"@en ;
rdfs:domain obo:IAO_0000032 ;
rdfs:range xsd:double .
obo:IAO_0000413 a rdf:Property ;
rdfs:label "is duration of"@en ;
rdfs:comment "relates a process to a time-measurement-datum that represents the duration of the process"@en ;
rdfs:domain obo:IAO_0000416 ;
rdfs:range obo:BFO_0000015 ;
rdfs:subPropertyOf obo:IAO_0000136 .
obo:IAO_0000039 a rdf:Property ;
rdfs:label "has measurement unit label"@en ;
rdfs:range obo:UO_0000003 , obo:IAO_0000003 , obo:UO_0000002 ;
rdfs:subPropertyOf obo:BFO_0000051 .
obo:STATO_0000077 a rdfs:Class ;
rdfs:label "Shapiro-Wilk test"@en ;
rdfs:comment "Shapiro-Wilk test is a goodness of fit test which evaluates the null hypothesis that the sample is drawn from a population following a normal distribution"@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000191 .
obo:OBI_0001933 a rdfs:Class ;
rdfs:label "value specification" ;
rdfs:comment "An information content entity that specifies a value within a classification scheme or on a quantitative scale." ;
rdfs:subClassOf obo:IAO_0000030 .
obo:OBI_0002135 a rdf:Property ;
rdfs:label "has specified value"@en ;
rdfs:comment "A relation between a value specification and a literal." ;
rdfs:domain obo:OBI_0001933 ;
rdfs:range .
obo:OBI_0001927 a rdf:Property ;
rdfs:label "specifies value of" ;
rdfs:comment "A relation between a value specification and an entity which the specification is about." ;
rdfs:domain obo:OBI_0001933 ;
rdfs:range ;
rdfs:subPropertyOf obo:IAO_0000136 .
obo:OBI_0001937 a rdf:Property ;
rdfs:label "has specified numeric value" ;
rdfs:comment "A relation between a value specification and a number that quantifies it." ;
rdfs:domain obo:OBI_0001933 ;
rdfs:range ;
rdfs:subPropertyOf obo:OBI_0002135 .
obo:STATO_0000002 a rdfs:Class ;
rdfs:label "digital file"@en ;
rdfs:comment "an electronic file is an information content entity which conforms to a specification or format and which is meant to hold data and information in digital form, accessible to software agents"@en ;
rdfs:subClassOf obo:IAO_0000030 .
obo:STATO_0000314 a rdfs:Class ;
rdfs:label "upper confidence limit"@en ;
rdfs:comment "upper confidence limit is a data item which is a largest value bounding a confidence interval"@en ;
rdfs:subClassOf obo:STATO_0000633 .
obo:STATO_0000717 a rdfs:Class ;
rdfs:label "equivalence testing" ;
rdfs:comment "a type of between group comparison test with the intent to compare two or more interventions or exposures and to determine that the absolute value of any difference in effects is smaller than a prespecified value representing a meaningful difference." ;
rdfs:subClassOf obo:STATO_0000715 .
obo:STATO_0000294 a rdfs:Class ;
rdfs:label "absence of negative difference hypothesis"@en ;
rdfs:comment "absence of negative difference hypothesis is a hypothesis which assumes that a difference significantly less than a threshold does not exist."@en ;
rdfs:subClassOf obo:STATO_0000065 .
obo:STATO_0000645 a rdfs:Class ;
rdfs:label "rate"@en ;
rdfs:comment "A ratio in which the numerator represents any quantity and the denominator represents an interval of time."@en ;
rdfs:seeAlso ;
rdfs:subClassOf obo:STATO_0000184 .
obo:STATO_0000161 a rdfs:Class ;
rdfs:label "data distribution"@en ;
rdfs:comment "variable distribution is data item which denotes the spatial resolution of data point making up a variable. variable distribution may be compared to a known probability distribution using goodness of fit test or plotting a quantile-quantile plot for visual assessment of the fit."@en ;
rdfs:subClassOf obo:IAO_0000030 .
obo:STATO_0000153 a rdfs:Class ;
rdfs:label "one sample Hotelling T2 test"@en ;
rdfs:comment "The one-sample Hotelling’s T2 is the multivariate extension of the common one-sample or paired Student’s t-test. In a one-sample t-test, the mean response is compared against a specific value. Hotelling’s one-sample T2 is used when the number of response variables is two or more, although it can be used when there is only one response variable. T2 makes the usual assumption that the data are approximately multivariate normal. Randomization tests are provided that do not rely on this assumption. These randomization tests should be used whenever you want exact results that do not rely on several assumptions."@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000191 .
obo:STATO_0000561 a rdfs:Class ;
rdfs:label "confidence level" ;
rdfs:comment """the frequency (i.e., the proportion) of possible confidence intervals that contain the true value of their corresponding parameter. In other words, if confidence intervals are constructed using a given confidence level in an infinite number of independent experiments, the proportion of those intervals that contain the true value of the parameter will match the confidence level.
A probability measure of the reliability of an inferential statistical test that has been applied to sample data and which is provided along with the confidence interval for the output statistic.""" ;
rdfs:subClassOf obo:STATO_0000300 .
obo:STATO_0000200 a rdfs:Class ;
rdfs:label "statistical test power"@en ;
rdfs:comment "the statistical test power is data item which is about a statistical test and is obtained by subtracting the false negative rate (type II error rate) to 1. The power of a statistical test is the probability that it will correctly lead to the rejection of a false null hypothesis (Greene 2000). The statistical power is the ability of a test to detect an effect, if the effect actually exists (High 2000)."@en ;
rdfs:subClassOf obo:IAO_0000027 .
obo:OBI_0500000 a rdfs:Class ;
rdfs:label "study design"@en ;
rdfs:comment "A plan specification comprised of protocols (which may specify how and what kinds of data will be gathered) that are executed as part of an investigation and is realized during a study design execution." ;
rdfs:subClassOf obo:IAO_0000104 .
obo:STATO_0000639 a rdfs:Class ;
rdfs:label "percentage" ;
rdfs:comment "A ratio formed between a numerator and a denominator (both described by the same unit), and that is multiplied by 100." ;
rdfs:subClassOf obo:STATO_0000184 .
obo:STATO_0000362 a rdfs:Class ;
rdfs:label "compound symmetry covariance structure"@en ;
rdfs:comment "compound symmetry covariance structure is a covariance structure which means that all the variances are equal and all the covariances are equal."@en ;
rdfs:subClassOf obo:STATO_0000346 .
obo:STATO_0000186 a rdfs:Class ;
rdfs:label "Lineweaver-Burk plot"@en ;
rdfs:comment """Lineweaver-Burk plot is a graph which is the graphical representation of the Lineweaver–Burk equation of enzyme kinetics, described by Hans Lineweaver and Dean Burk in 1934. The plot provides a useful graphical method for analysis of the Michaelis–Menten equation.
It was widely used to determine important terms in enzymology and enzyme kinetics as the x-intercept of the graph represents −1/Km and the y-intercept of such a graph is equivalent to the inverse of Vmax"""@en ;
rdfs:subClassOf obo:IAO_0000038 .
obo:OBI_0001554 a rdfs:Class ;
rdfs:label "rate measurement datum" ;
rdfs:comment "A scalar measurement datum that represents the number of events occuring over a time interval" ;
rdfs:subClassOf obo:IAO_0000032 .
obo:STATO_0000522 a rdfs:Class ;
rdfs:label "multivariate imputation with chained equations" ;
rdfs:comment "multivariate imputation with chained equations (MICE) is a type of data imputation which uses an algorithm devised by Stef van Buuren and Karin Groothuis-Oudshoorn" ;
rdfs:subClassOf obo:STATO_0000518 .
obo:OBI_0200194 a rdfs:Class ;
rdfs:label "survival analysis data transformation" ;
rdfs:comment "A data transformation which has the objective of performing survival analysis." ;
rdfs:subClassOf obo:OBI_0200000 .
obo:STATO_0000270 a rdfs:Class ;
rdfs:label "full factorial design"@en ;
rdfs:comment "a full factorial design is a factorial design which ensures that all possible factor level combinations are defined and used so all between group differences can be explored"@en ;
rdfs:subClassOf obo:OBI_0500014 .
obo:STATO_0000226 a rdfs:Class ;
rdfs:label "equal variance testing objective"@en ;
rdfs:comment "It is a testing objective to ensure the variances of the different groups used in a statistical test are similar (i.e. not too different)." ;
rdfs:subClassOf obo:OBI_0000675 .
obo:STATO_0000688 a rdfs:Class ;
rdfs:label "calibration intercept"@en ;
rdfs:comment "A measure of calibration that is the difference between the mean expected value and the mean observed value."@en ;
rdfs:subClassOf obo:STATO_0000685 .
obo:OBI_0400153 a rdfs:Class ;
rdfs:label "droplet sorter"@en ;
rdfs:comment """A droplet sorter is part_of a flow cytometer sorter that converts the carrier fluid stream into individual droplets, and these droplets are directed into separate locations for recovery (enriching the original
sample for particles of interest based on qualities determined by gating) or disposal."""@en ;
rdfs:subClassOf obo:OBI_0000932 .
a rdfs:Class ;
rdfs:label "Chi-squared statistic for homogeneity"@en ;
rdfs:comment "A Chi-squared statistic used to test whether observed data from two or more groups follow the same distribution."@en ;
rdfs:subClassOf obo:STATO_0000030 .
obo:STATO_0000419 a rdfs:Class ;
rdfs:label "Cochran's Q statistic"@en ;
rdfs:comment "The Cochran's Q statistic is a measure of heterogeneity accros study computed by summing the squared deviations of each study's estimate from the overall meta-analytic estimate, weighting each study's contribution in the same manner as in the meta-analysis."@en ;
rdfs:subClassOf obo:STATO_0000418 .
obo:OBI_0500005 a rdfs:Class ;
rdfs:label "matched pairs design"@en ;
rdfs:comment "A matched pair design is a study design which use groups of individuals associated (hence matched) to each other based on a set of criteria, one member going to one treatment, the other member receiving the other treatment."@en ;
rdfs:subClassOf obo:OBI_0500000 , obo:STATO_0000046 .
obo:STATO_0000724 a rdfs:Class ;
rdfs:label "boolean variable" ;
rdfs:comment "A variable which is defined to have only 2 possible values, True or False." ;
rdfs:subClassOf obo:STATO_0000090 .
obo:STATO_0000448 a rdfs:Class ;
rdfs:label "sub-plot number"@en ;
rdfs:comment """a 'sub plot number' is a data item used to count and identify the actual piece of land located within a 'whole plot', in the case of real field based trials using a split-plot design, and received completely randomized treatments corresponding to the factor levels combinations of the remainder factors declared in the experiment.
in the case of 'split-split plot design', sub-plots also receive treatments corresponding to a factor whose randomization is restriction. In such configuration, each 'sub-plot' is itself divided into 'sub sub-plot', which then received the remainder of the treatments in completely randomized fashion.
In the case of non-field based trials, the notion 'sub-plot' is a metaphor."""@en ;
rdfs:subClassOf obo:IAO_0000027 .
obo:STATO_0000594 a rdfs:Class ;
rdfs:label "confusion matrix"@en ;
rdfs:comment "a confusion matrix is a 2 by 2 contingency table used to evaluate the performance of a classifier, often a machine-learning classifier and that allows visualization of the performance of an algorithm, typically a supervised learning one. It defines two dimensions (\"actual\" and \"predicted\"), and identical sets of \"classes\" in both dimensions (each combination of dimension and class is a variable in the contingency table)."@en ;
rdfs:subClassOf obo:STATO_0000642 .
obo:STATO_0000312 a rdfs:Class ;
rdfs:label "Box–Behnkens design"@en ;
rdfs:comment "The Box-Behnken design is an independent quadratic design in that it does not contain an embedded factorial or fractional factorial design. In this design the treatment combinations are at the midpoints of edges of the process space and at the center. These designs are rotatable (or near rotatable) and require 3 levels of each factor. The designs have limited capability for orthogonal blocking compared to the central composite designs."@en ;
rdfs:subClassOf obo:OBI_0500000 .
obo:STATO_0000640 a rdfs:Class ;
rdfs:label "log-rank test" ;
rdfs:comment "The logrank test is a statistical hypothesis test used to compare the survival distributions of two or more groups. It is commonly employed in survival analysis, where the primary interest lies in comparing the survival experiences of different groups over time." ;
rdfs:subClassOf obo:OBI_0000673 , obo:OBI_0200000 , obo:OBI_0200194 .
obo:NCBITaxon_314146 a rdfs:Class ;
rdfs:label "Euarchontoglires" ;
rdfs:subClassOf obo:NCBITaxon_40674 .
obo:STATO_0000099 a rdfs:Class ;
rdfs:label "random effect model"@en ;
rdfs:comment "a random effect(s) model, also called a variance components model, is a kind of hierarchical linear model. It assumes that the dataset being analysed consists of a hierarchy of different populations whose differences relate to that hierarchy."@en ;
rdfs:subClassOf obo:STATO_0000107 .
obo:STATO_0000697 a rdfs:Class ;
rdfs:label "homogeneity test"@en ;
rdfs:comment "an homogeneity test is a statistical test aiming at evaluate if the statisical measure from several random samples are similar"@en ;
rdfs:subClassOf obo:OBI_0000673 .
obo:STATO_0000147 a rdfs:Class ;
rdfs:label "LD plot"@en ;
rdfs:comment "Linkage Disequilibrium plot is a graph which represents pairwise linkage disequilibrium measures between SNP as a heatmap"@en ;
rdfs:subClassOf obo:IAO_0000038 .
obo:OBI_0000931 a rdfs:Class ;
rdfs:label "study intervention" ;
rdfs:comment "the part of the execution of an intervention design study which is varied between two or more subjects in the study" ;
rdfs:subClassOf obo:OBI_0000011 .
obo:STATO_0000028 a rdfs:Class ;
rdfs:label "measure of dispersion"@en ;
rdfs:comment "measure of variation or statistical dispersion is a data item which describes how much a theoritical distribution or dataset is spread."@en ;
rdfs:subClassOf obo:STATO_0000039 .
obo:STATO_0000395 a rdfs:Class ;
rdfs:label "Pareto type-IV probability distribution"@en ;
rdfs:comment """The Pareto(IV) distribution is a continous probability distribution which is described with a cumulative distribution function of the following form:
F(y) = 1 − [1 + ((y − a)/b)1/g]−s
for y > a, b > 0, g > 0 and s > 0.
a is the location parameter,
b is the scale parameter,
g is the inequality parameter
s is the shape parameter
The distribution is used in actuarial science, economics, finance and telecommunications, but not restricted to those fields."""@en ;
rdfs:subClassOf obo:STATO_0000067 .
obo:STATO_0000081 a rdfs:Class ;
rdfs:label "Pearson's Chi square test of independence between categorical variables"@en ;
rdfs:comment "Pearson's Chi-Squared test is a statistical null hypothesis test which is used to either evaluate goodness of fit of dataset to a Chi-Squared distribution or used to test independence of 2 categorical variables (ie absence of association between those variables)."@en ;
rdfs:subClassOf obo:OBI_0200200 , obo:STATO_0000027 .
obo:STATO_0000511 a rdfs:Class ;
rdfs:label "panel sampling"@en ;
rdfs:comment "Panel sampling is the method of first selecting a group of participants through a random sampling method and then asking that group for (potentially the same) information several times over a period of time. Therefore, each participant is interviewed at two or more time points; each period of data collection is called a \"wave\". The method was developed by sociologist Paul Lazarsfeld in 1938 as a means of studying political campaigns."@en ;
rdfs:subClassOf obo:STATO_0000502 .
obo:STATO_0000030 a rdfs:Class ;
rdfs:label "Chi-Squared statistic"@en ;
rdfs:comment "Chi-squared statistic is a statistic computed from observations and used to produce a p-value in statistical test when compared to a Chi-Squared distribution."@en ;
rdfs:subClassOf obo:STATO_0000609 .
obo:STATO_0000107 a rdfs:Class ;
rdfs:label "statistical model"@en ;
rdfs:comment "a statistical model is an information content entity which is a formalization of relationships between variables in the form of mathematical equations. A statistical model describes how one or more random variables are related to one or more other variables. The model is statistical as the variables are not deterministically but stochastically related."@en ;
rdfs:subClassOf obo:IAO_0000027 , obo:IAO_0000030 .
obo:STATO_0000355 a rdfs:Class ;
rdfs:label "heterogeneous Toeplitz covariance structure"@en ;
rdfs:comment "This covariance structure has heterogenous variances and heterogenous correlations between elements. The correlation between adjacent elements is homogenous across pairs of adjacent elements. The correlation between elements separated by a third is again homogenous, and so on."@en ;
rdfs:subClassOf obo:STATO_0000346 .
obo:STATO_0000409 a rdfs:Class ;
rdfs:label "likelihood ratio"@en ;
rdfs:comment "the likelihood ratio is a ratio which is formed by dividing the post-test odds with the pre-test odds in the context of a Bayesian formulation"@en ;
rdfs:subClassOf obo:STATO_0000184 , obo:STATO_0000622 .
obo:STATO_0000323 a rdfs:Class ;
rdfs:label "contrast weight matrix"@en ;
rdfs:comment "a contrast weight matrix is a information content entity which holds a set of contrast weight, coefficient used in a weighting sum of means defining a contrast"@en ;
rdfs:subClassOf obo:STATO_0000642 .
obo:STATO_0000456 a rdfs:Class ;
rdfs:label "95% credible interval"@en ;
rdfs:comment "In Bayesian statistics context, a 95% credible interval is a credible interval which,given the data, includes the true parameter with probability of 95%."@en ;
rdfs:subClassOf obo:STATO_0000455 .
obo:OBI_0666667 a rdfs:Class ;
rdfs:label "nucleic acid extraction"@en ;
rdfs:comment "a material separation to recover the nucleic acid fraction of an input material"@en ;
rdfs:subClassOf obo:OBI_0302884 .
obo:STATO_0000601 a rdfs:Class ;
rdfs:label "simultaneous multiple testing correction" ;
rdfs:comment "simultaneous multiple testing method is a multiple testing correction method which..." ;
rdfs:subClassOf obo:OBI_0200089 .
obo:STATO_0000437 a rdfs:Class ;
rdfs:label "scale estimator"@en ;
rdfs:comment "a scale estimator is a measurement datum (a statistic) which is calculated to approach the actual scale parameter of a probability distribution from observed data."@en ;
rdfs:subClassOf obo:STATO_0000471 .
obo:PATO_0001018 a rdfs:Class ;
rdfs:label "physical quality" ;
rdfs:comment "A quality of a physical entity that exists through action of continuants at the physical level of organisation in relation to other entities." ;
rdfs:subClassOf obo:PATO_0001241 .
obo:STATO_0000136 a rdfs:Class ;
rdfs:label "Tarone's test for homogeneity of odds ratio"@en ;
rdfs:comment "Tarone's test for homogeneity of odds ratio is a statistical test which evaluates the null hypothesis that odds ratio are homogeneous"@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000247 , obo:STATO_0000697 .
obo:STATO_0000047 a rdfs:Class ;
rdfs:label "count"@en ;
rdfs:comment "a count is a data item denoted by an integer and representing the number of instances or occurences of an entity"@en ;
rdfs:subClassOf obo:STATO_0000039 .
obo:STATO_0000597 a rdfs:Class ;
rdfs:label "number of true negative"@en ;
rdfs:comment "the number of true negative is a count which denotes how many elements are correctly classified as void of a feature they are actually known to be missing (e.g. free of pathogen)." ;
rdfs:subClassOf obo:STATO_0000047 .
obo:STATO_0000292 a rdfs:Class ;
rdfs:label "decile"@en ;
rdfs:comment "a decile is a quantile where n=10 and which splits data into sections accrued of 10% of data, so the first decile delineates 10% of the data, the second decile delineates 20% of the data and the nineth decile, 90 % of the data"@en ;
rdfs:subClassOf obo:STATO_0000291 .
obo:STATO_0000070 a rdfs:Class ;
rdfs:label "Yate's corrected Chi-Squared test"@en ;
rdfs:comment """Yate's corrected Chi-Squared test is a statistical test which is used to test the association/linkage/independence of 2 dichotomous variables while introducing a correction for using the continous Chi-squared distribution for the test.
To reduce the error in approximation, Frank Yates, an English statistician, suggested a correction for continuity that adjusts the formula for Pearson's chi-squared test by subtracting 0.5 from the difference between each observed value and its expected value in a 2 × 2 contingency table. This reduces the chi-squared value obtained and thus increases its p-value."""@en ;
rdfs:subClassOf obo:STATO_0000081 .
obo:STATO_0000087 a rdfs:Class ;
rdfs:label "polychotomous variable"@en ;
rdfs:comment "a polychotomous variable is a categorical variable which is defined to have minimally 2 categories or possible values"@en ;
rdfs:subClassOf obo:STATO_0000252 .
obo:BFO_0000006 a rdfs:Class ;
rdfs:label "spatial region"@en ;
rdfs:subClassOf obo:BFO_0000141 .
obo:STATO_0000677 a rdfs:Class ;
rdfs:label "hazard ratio"@en ;
rdfs:comment "A measure of association that is the ratio of the hazard rate of an event in one group to the hazard rate of the same event in another group."@en ;
rdfs:subClassOf obo:STATO_0000184 .
obo:STATO_0000215 a rdfs:Class ;
rdfs:label "ordered probit regression for analysis of ordinal dependent variable"@en ;
rdfs:comment "probit regression model is a model which attempts to explain data distribution associated with *ordinal* response/dependent variable in terms of values assumed by the independent variable uses a function of predictor/independent variable(s): the function used in this instance of regression modeling is the ordered probit function."@en ;
rdfs:subClassOf obo:OBI_0200102 .
obo:OBI_0200168 a rdfs:Class ;
rdfs:label "correction objective"@en ;
rdfs:comment "A correction objective is a data transformation objective where the aim is to correct for error, noise or other impairments to the input of the data transformation or derived from the data transformation itself"@en ;
rdfs:subClassOf obo:OBI_0200166 .
obo:STATO_0000125 a rdfs:Class ;
rdfs:label "Wilkinson dot plot" ;
rdfs:comment "The dot plot as a representation of a distribution consists of group of data points plotted on a simple scale. Dot plots are used for continuous, quantitative, univariate data. Data points may be labelled if there are few of them."@en ;
rdfs:subClassOf obo:IAO_0000037 .
obo:STATO_0000377 a rdfs:Class ;
rdfs:label "deviance" ;
rdfs:comment """Deviance is an indicator of fit and can be estimated by computing -2 times the log-likelihood ratio of the fitted model compared to a saturated(full) model.
It is a generalization of the idea of using the sum of squares of residuals in ordinary least squares to cases where model-fitting is achieved by maximum likelihood."""@en ;
rdfs:subClassOf obo:STATO_0000039 .
obo:STATO_0000550 a rdfs:Class ;
rdfs:label "log likelihood" ;
rdfs:comment """log likelihood is a data item which corresponds to the natural logarithm of the likelihood.
log likelihood is a data item commonly used to provide a measure of accuracy of a model.""" ;
rdfs:subClassOf obo:IAO_0000027 .
obo:OBI_0200102 a rdfs:Class ;
rdfs:label "regression analysis method"@en ;
rdfs:comment "Regression analysis is a descriptive statistics technique that examines the relation of a dependent variable (response variable) to specified independent variables (explanatory variables). Regression analysis can be used as a descriptive method of data analysis (such as curve fitting) without relying on any assumptions about underlying processes generating the data."@en ;
rdfs:subClassOf obo:OBI_0200000 .
obo:STATO_0000467 a rdfs:Class ;
rdfs:label "model random effect term"@en ;
rdfs:comment "the model random effect term is model term which aims to account for the unwanted variability in the data associated with a range of independent variables which are not the primary interest in the dataset. It is there also known as the variance component of the model" ;
rdfs:subClassOf obo:OBI_0000751 , obo:STATO_0000466 .
obo:STATO_0000476 a rdf:Property ;
rdfs:label "is modeled by"@en ;
rdfs:comment "This property is a specialization of the 'is about' property to represent the relationship between a dependent variable and an statistical model."@en ;
rdfs:domain obo:OBI_0000751 ;
rdfs:range obo:STATO_0000107 ;
rdfs:subPropertyOf obo:IAO_0000136 .
obo:STATO_0000382 a rdf:Property ;
rdfs:label "has order in sequence"@en ;
rdfs:comment "'has order in sequence' is a special case of the 'is about' relation being used to be able to enumerate the different terms within a linear mixed model formula (thus assinging and order to random effect terms, fixed effect terms, interaction effect terms and error terms)."@en ;
rdfs:domain obo:IAO_0000030 ;
rdfs:range obo:STATO_0000047 ;
rdfs:subPropertyOf obo:IAO_0000136 .
obo:STATO_0000713 a rdfs:Class ;
rdfs:label "type I error"@en ;
rdfs:comment "the event of incorrectly rejecting the null hypothesis"@en ;
rdfs:subClassOf obo:STATO_0000242 .
obo:OBI_0000047 a rdfs:Class ;
rdfs:label "processed material"@en ;
rdfs:comment "Is a material entity that is created or changed during material processing."@en ;
rdfs:subClassOf obo:BFO_0000040 .
obo:STATO_0000702 a rdfs:Class ;
rdfs:label "prior probability" ;
rdfs:comment "A statistic that represents the likelihood of a parameter of interest, before accounting for the observed data from the study." ;
rdfs:subClassOf obo:STATO_0000039 .
obo:STATO_0000506 a rdfs:Class ;
rdfs:label "cluster sampling"@en ;
rdfs:comment "Cluster sampling is a sampling plan used when mutually homogeneous yet internally heterogeneous groupings are evident in a statistical population."@en ;
rdfs:subClassOf obo:STATO_0000509 .
obo:STATO_0000388 a rdfs:Class ;
rdfs:label "alpha distribution"@en ;
rdfs:comment "The alpha distribution is a continuous probability distribution whose density function is as defined at: https://docs.scipy.org/doc/scipy-1.0.0/reference/tutorial/stats/continuous_alpha.html"@en ;
rdfs:subClassOf obo:STATO_0000067 .
obo:STATO_0000017 a rdfs:Class ;
rdfs:label "Wilk's lambda distribution"@en ;
rdfs:comment "Wilks' lambda distribution (named for Samuel S. Wilks), is a probability distribution used in multivariate hypothesis testing, especially with regard to the likelihood-ratio test and Multivariate analysis of variance. It is a multivariate generalization of the univariate F-distribution, and generalizes the F-distribution in the same way that the Hotelling's T-squared distribution generalizes Student's t-distribution."@en ;
rdfs:subClassOf obo:STATO_0000225 .
obo:OBI_0302884 a rdfs:Class ;
rdfs:label "extraction"@en ;
rdfs:comment "A material separation in which a desired component of an input material is separated from the remainder" ;
rdfs:subClassOf obo:OBI_0600014 .
obo:STATO_0000158 a rdfs:Class ;
rdfs:label "presence of association hypothesis"@en ;
rdfs:comment "a null hypothesis which states that a linkage exists between 2 categorical variables"@en ;
rdfs:subClassOf obo:STATO_0000065 .
obo:OBI_0000739 a rdfs:Class ;
rdfs:label "Student's t-test"@en ;
rdfs:comment "Studen't t-test is a data transformation with the objective of a statistical hypothesis test in which the test statistic has a Student's t distribution if the null hypothesis is true. It is applied when the population is assumed to be normally distributed but the sample sizes are small enough that the statistic on which inference is based is not normally distributed because it relies on an uncertain estimate of standard deviation rather than on a precisely known value." ;
rdfs:subClassOf obo:OBI_0000673 .
obo:STATO_0000720 a rdfs:Class ;
rdfs:label "observation unit" ;
rdfs:comment "An observation unit (also known as 'measurement unit') is the entity on which data is actually collected or recorded. It is the entity from which a measurement or observation is taken." ;
rdfs:subClassOf obo:BFO_0000004 .
obo:STATO_0000415 a rdfs:Class ;
rdfs:label "accuracy"@en ;
rdfs:comment """in the context of binary classification, accuracy is defined as the proportion of true results (both true positives and true negatives) to the total number of cases examined (the sum of true positive, true negative, false positive and false negative).
It can be understood as a measure of the proximity of measurement results to the true value.
Accuracy is a metric used in the context of classification tasks to evaluate the proportion of correctly predicted instances among the total instances.
Key Points:
Use Case: Classification performance evaluation.
Metric: Measures the proportion of correct predictions.
Interpretation: Higher values indicate better classification performance."""@en ;
rdfs:subClassOf obo:STATO_0000639 .
obo:STATO_0000366 a rdfs:Class ;
rdfs:label "heterogeneous first-order autoregressive covariance structure"@en ;
rdfs:comment "This is an homogeneous structure, i.e. the variance along the main diagonal is constant. The covariances decline exponentially. It has only 2 parameters."@en ;
rdfs:subClassOf obo:STATO_0000365 .
obo:STATO_0000183 a rdfs:Class ;
rdfs:label "sphericity testing objective"@en ;
rdfs:comment "sphericity testing objective is a statistical objective of a data transformation which aims to test a null hypothesis of sphericity holds."@en ;
rdfs:subClassOf obo:OBI_0000675 .
obo:OBI_0000861 a rdfs:Class ;
rdfs:label "Likelihood-ratio test"@en ;
rdfs:comment "Likelihood-ratio is a data transformation which tests whether there is evidence of the need to move from a simple model to a more complicated one (where the simple model is nested within the complicated one); tests of the goodness-of-fit between two models." ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000191 .
obo:OBI_0500014 a rdfs:Class ;
rdfs:label "factorial design"@en ;
rdfs:comment "factorial design is_a study design which is used to evaluate two or more factors simultaneously. The treatments are combinations of levels of the factors. The advantages of factorial designs over one-factor-at-a-time experiments is that they are more efficient and they allow interactions to be detected. In statistics, a factorial design experiment is an experiment whose design consists of two or more factors, each with discrete possible values or levels, and whose experimental units take on all possible combinations of these levels across all such factors. Such an experiment allows studying the effect of each factor on the response variable, as well as the effects of interactions between factors on the response variable."@en ;
rdfs:subClassOf obo:OBI_0500000 .
obo:STATO_0000549 a rdfs:Class ;
rdfs:label "random forest procedure" ;
rdfs:comment "random forest procedure is a type of data transformation used in classification and statistical learning using regression. The random forest procedure is a meta estimator that fits a number of classifying decision trees on various sub-samples of the dataset (it operates by constructing a multitude of decision trees at training time) and use averaging to improve the predictive accuracy and control over-fitting. The sub-sample size is always the same as the original input sample size but the samples are drawn with replacement if bootstrap=True (default). The random forest procedure outputs the class that is the mode of the classes (classification) or mean prediction (regression) of the individual trees."@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:OBI_0200175 .
obo:STATO_0000555 a rdfs:Class ;
rdfs:label "number of predictive components" ;
rdfs:comment "number of predictive components is a count used as input to the principle component analysis (PCA)" ;
rdfs:subClassOf obo:STATO_0000047 .
obo:STATO_0000399 a rdfs:Class ;
rdfs:label "interquartile mean"@en ;
rdfs:comment """The interquartile mean (IQM) (or midmean) is a statistical measure of central tendency based on the truncated mean of the interquartile range.
In the calculation of the IQM, only the data in the second and third quartiles is used (as in the interquartile range), and the lowest 25% and the highest 25% of the scores are discarded. These points are called the first and third quartiles, hence the name of the IQM."""@en ;
rdfs:subClassOf obo:STATO_0000163 .
obo:IAO_0000001 a rdfs:Class ;
rdfs:label "conditional specification"@en ;
rdfs:comment "a directive information entity that specifies what should happen if the trigger condition is fulfilled"@en ;
rdfs:subClassOf obo:IAO_0000033 .
obo:STATO_0000684 a rdfs:Class ;
rdfs:label "standard deviation for sample"@en ;
rdfs:comment "A standard deviation that is the square root of the quotient of the summation across data points of the square of the distance from each data point to the sample mean, and the degrees of freedom (where the degrees of freedom is sample size minus one)."@en ;
rdfs:subClassOf obo:STATO_0000237 .
obo:GO_0003964 a rdfs:Class ;
rdfs:label "RNA-directed DNA polymerase activity" ;
rdfs:comment "Catalysis of the reaction: deoxynucleoside triphosphate + DNA(n) = diphosphate + DNA(n+1). Catalyzes RNA-template-directed extension of the 3'- end of a DNA strand by one deoxynucleotide at a time." ;
rdfs:subClassOf obo:GO_0003824 .
obo:UO_0000003 a rdfs:Class ;
rdfs:label "time unit" ;
rdfs:comment "A unit which is a standard measure of the dimension in which events occur in sequence." ;
rdfs:subClassOf obo:IAO_0000003 .
obo:STATO_0000198 a rdfs:Class ;
rdfs:label "non-parametric test"@en ;
rdfs:comment "a statistical test which makes no assumption about the underlying data distribution"@en ;
rdfs:subClassOf obo:OBI_0000673 , obo:STATO_0000279 .
obo:OBI_0000387 a rdfs:Class ;
rdfs:label "cool function"@en ;
rdfs:comment "A cool function is a function to decrease the internal kinetic energy of a material below the initial kinetic energy of that type of material."@en ;
rdfs:subClassOf obo:BFO_0000034 .
obo:STATO_0000359 a rdfs:Class ;
rdfs:label "equal diagonal Factor Analytic covariance structure"@en ;
rdfs:comment """factor-analytic structure is a covariance structure which is specified for q factors
equal diagonal factor-analytic covariance structure is a type of factor analytic covariance structure specified for q factors, which includes a diagonal component for repeated measures."""@en ;
rdfs:subClassOf obo:STATO_0000361 .
obo:OBI_0000968 a rdfs:Class ;
rdfs:label "device" ;
rdfs:comment "A material entity that is designed to perform a function in a scientific investigation, but is not a reagent." ;
rdfs:subClassOf obo:OBI_0000047 .
obo:STATO_0000566 a rdfs:Class ;
rdfs:label "eigen value"@en ;
rdfs:comment "An eigenvalue is a data item resulting from a data transformation known as eigen value decomposition. It also corresponds to a process of matrix diagonalization or any equivalent operation, ie. transforming the underlying system of equations into a special set of coordinate axes in which the matrix takes this canonical form. Each eigenvalue is paired with a corresponding so-called eigenvector."@en ;
rdfs:subClassOf obo:IAO_0000027 , obo:OBI_0000648 .
obo:STATO_0000142 a rdfs:Class ;
rdfs:label "correlation coefficient"@en ;
rdfs:comment "The correlation coefficient of two variables in a data sample is their covariance divided by the product of their individual standard deviations. It is a normalized measurement of how the two are linearly related."@en ;
rdfs:subClassOf obo:STATO_0000085 , obo:STATO_0000611 .
obo:STATO_0000501 a rdfs:Class ;
rdfs:label "Weibull probability distribution"@en ;
rdfs:comment """the Weibull probability distribution is continuous probabibility distribution which is used to model time to fail, time to repair and material strength in material science. In biomedicine, the Weibull probability is used to in determining 'hazard functions'.
The 'location parameter' of the Weibull probability distribution can be used to define a failure-free zone.
If the quantity X is a \"time-to-failure\", the Weibull distribution gives a distribution for which the failure rate is proportional to a power of time. The shape parameter, k, is that power plus one, and so this parameter can be interpreted directly as follows:
A value of {\\displaystyle k<1\\,} {\\displaystyle k<1\\,} indicates that the failure rate decreases over time. This happens if there is significant \"infant mortality\", or defective items failing early and the failure rate decreasing over time as the defective items are weeded out of the population. In the context of the diffusion of innovations, this means negative word of mouth: the hazard function is a monotonically decreasing function of the proportion of adopters;
A value of {\\displaystyle k=1\\,} {\\displaystyle k=1\\,} indicates that the failure rate is constant over time. This might suggest random external events are causing mortality, or failure. The Weibull distribution reduces to an exponential distribution;
A value of {\\displaystyle k>1\\,} {\\displaystyle k>1\\,} indicates that the failure rate increases with time. This happens if there is an \"aging\" process, or parts that are more likely to fail as time goes on. In the context of the diffusion of innovations, this means positive word of mouth: the hazard function is a monotonically increasing function of the proportion of adopters. The function is first concave, then convex with an inflexion point at {\\displaystyle (e^{1/k}-1)/e^{1/k},k>1\\,} {\\displaystyle (e^{1/k}-1)/e^{1/k},k>1\\,}."""@en ;
rdfs:subClassOf obo:STATO_0000067 .
obo:STATO_0000651 a rdfs:Class ;
rdfs:label "statistical sample" ;
rdfs:comment "the output of a statistical sampling, a draw from a distribution or a population of physical or immaterial entities." ;
rdfs:subClassOf obo:BFO_0000004 .
obo:STATO_0000115 a rdf:Property ;
rdfs:label "has member"@en ;
rdfs:comment "relationship between a set and one of its elements"@en ;
rdfs:range .
obo:STATO_0000199 a rdfs:Class ;
rdfs:label "Mauchly's test for sphericity" ;
rdfs:comment """the Mauchly's test for sphericity is a statistical test which evaluates if the variance of the differences between all combinations of the groups are equal, a property known as 'sphericity' in the context of repeated measures. It is used for instance prior to repeated measure ANOVA.
The test works by assessing if a Wishart-distributed covariance matrix (or transformation thereof) is proportional to a given matrix."""@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000131 .
obo:STATO_0000039 a rdfs:Class ;
rdfs:label "statistic"@en ;
rdfs:comment "a statistic is a measurement datum to describe a dataset or a variable. It is generated by a calculation on set of observed data."@en ;
rdfs:subClassOf obo:IAO_0000027 .
obo:STATO_0000466 a rdfs:Class ;
rdfs:label "model term"@en ;
rdfs:comment "A model term is a data item set in statistical model formula to apportion source of variation."@en ;
rdfs:subClassOf obo:IAO_0000027 .
obo:STATO_0000606 a rdfs:Class ;
rdfs:label "q-statistic" ;
rdfs:comment "q is the basic statistic for the studentized range distribution, which is used for multiple comparison procedures, such as the single step procedure Tukey's range test, the Newman–Keuls method, and the Duncan's step down procedure, and establishing confidence intervals that are still valid after data snooping has occurred" ;
rdfs:subClassOf obo:STATO_0000039 .
obo:STATO_0000219 a rdfs:Class ;
rdfs:label "RT-PCR standard curve"@en ;
rdfs:comment "a real time pcr standard curve is a line graph which plots the fluorescence intensity signal as a function of the concentration of a sample used as reference and used to determine relative abundance of test samples"@en ;
rdfs:subClassOf obo:IAO_0000573 .
obo:OBI_0000453 a rdfs:Class ;
rdfs:label "measure function"@en ;
rdfs:comment "Measure function is a function that is borne by a processed material and realized in a process in which information about some entity is expressed relative to some reference."@en ;
rdfs:subClassOf obo:BFO_0000034 .
obo:STATO_0000624 a rdfs:Class ;
rdfs:label "Gini index"@en ;
rdfs:comment """The Gini index, or Gini coefficient, is a statistical measure of dispersion which assesses the pattern of data in a frequency distribution, in particular it measures the inequality among values.
Geometrically, the Gini index can be defined as the ratio of 2 areas delineated by 2 curves, the line of equality (curve 1) and the Lorenz curve (curve 2). The numerator of the ratio corresponds to the area defined between curve 1 and curve 2 , while the denominator corresponds to the entire area below curve 1.
Mathematically, the Gini index is defined as half of the relative mean absolute difference.
It was therefore originally used to assess income inequality and is named after the italian statistician Corrado Gini who published it in 1912."""@en ;
rdfs:subClassOf obo:STATO_0000028 .
obo:OBI_0001352 a rdfs:Class ;
rdfs:label "allele information"@en ;
rdfs:comment "a genetic alteration information that about one of two or more alternative forms of a gene or marker sequence and differing from other alleles at one or more mutational sites based on sequence. Polymorphisms are included in this definition."@en ;
rdfs:subClassOf obo:OBI_0001364 .
obo:STATO_0000673 a rdfs:Class ;
rdfs:label "event frequency rate"@en ;
rdfs:comment "A ratio in which the numerator represents an event frequency and the denominator represents an interval of time."@en ;
rdfs:subClassOf obo:STATO_0000645 .
obo:STATO_0000492 a rdfs:Class ;
rdfs:label "Bayesian least absolute shrinkage and selection operator" ;
rdfs:comment "Bayesian LASSO is a data transformation where the regression parameters have independent Laplace (i.e., double-exponential) priors and are used to interprete Lasso estimate for linear regression parameters as Bayesian posterior mode estimates in accordance to a Bayesian framework." ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000119 , obo:STATO_0000337 .
obo:STATO_0000373 a rdfs:Class ;
rdfs:label "iteratively reweighted least squares estimation"@en ;
rdfs:comment "the iteratively reweighted least squares estimation is a model parameter estimation which is a practical implementation of Weighted Least Squares, where the heterogeneous variances of the errors are estimated from the residuals of the regression model, providing an estimate for the weights. Each successive estimate of the weights improves the estimation of the regression parameters, which in turn are used to compute residuals and update the weights"@en ;
rdfs:subClassOf obo:STATO_0000119 .
obo:STATO_0000169 a rdfs:Class ;
rdfs:label "fold change"@en ;
rdfs:comment "Fold change is a number describing how much a quantity changes going from an initial to a final value or one condition to another condition"@en ;
rdfs:subClassOf obo:STATO_0000300 .
obo:STATO_0000455 a rdfs:Class ;
rdfs:label "credible interval"@en ;
rdfs:comment """In Bayesian statistics context, a credible interval is an interval of a posterior distribution which is such that the density at any point inside the interval is greater than the density at any point outside and that the area under the curve for that interval is equal to a prespecified probability level. For any probability level there is generally only one such interval, which is also often known as the highest posterior density region. Unlike the usual confidence interval associated with frequentist inference, here the intervals specify the range within which parameters lie with a certain probability.
The Bayesian counterparts of the confidence interval used in Frequentists Statistics."""@en ;
rdfs:subClassOf obo:STATO_0000028 .
obo:STATO_0000236 a rdfs:Class ;
rdfs:label "coefficient of variation"@en ;
rdfs:comment "the coefficient of variation is a normalized measure of dispersion of a probability distribution of frequency distribution."@en ;
rdfs:subClassOf obo:STATO_0000028 .
obo:STATO_0000426 a rdfs:Class ;
rdfs:label "Hunter-Schmidt estimator"@en ;
rdfs:comment "Hunter-Schmidt estimator is a data item computed to estimate heterogeneity parameter (estimate of between-study variance) in a random effect model for meta analysis."@en ;
rdfs:subClassOf obo:STATO_0000471 .
obo:STATO_0000172 a rdfs:Class ;
rdfs:label "FPKM-fragments per kilobase of transcript per million fragments mapped"@en ;
rdfs:comment """FPKM, which is the expected fragments per kilobase of transcript per million fragments mapped is a metric used to report transcript expression event as generated by RNA-Seq using paired-end library. The calculated value results from 2 types of normalization, one to take into account the difference in reads counts associated with transcript length (at equal abundance, longer transcripts will have more reads than shorter transcripts) , (hence the 'per kilobase of transcript') and the other one to take into account different sequencing depth during distinct sequencing runs (hence the 'per millions mapped fragment'. The metric is specifically produced by cufflink software.
Recommended use:
-FPKM measure may be used for gene count comparisons within a sample.
-FPKM measure is NOT suited for between sample comparisons.
-FPKM measure is NOT suited for Differential Expression analysis."""@en ;
rdfs:subClassOf obo:STATO_0000047 .
obo:STATO_0000276 a rdfs:Class ;
rdfs:label "binomial distribution"@en ;
rdfs:comment """The binomial distribution is a discrete probability distribution which describes the probability of k successes in n draws with replacement from a finite population of size N.
The binomial distribution is frequently used to model the number of successes in a sample of size n drawn with replacement from a population of size N.
The binomial distribution gives the discrete probability distribution of obtaining exactly n successes out of N Bernoulli trials (where the result of each Bernoulli trial is true with probability p and false with probability q=1-p )
notation: B(n,p)
The mean is N*p
The variance is N*p*q"""@en ;
rdfs:subClassOf obo:STATO_0000117 .
obo:STATO_0000538 a rdfs:Class ;
rdfs:label "continuous multivariate probability distribution" ;
rdfs:comment "a continuous multivariate probability distribution is a continuous probability distribution which describes the possible values, and corresponding probabilities, of two or more (usually three or more) associated random variables." ;
rdfs:subClassOf obo:STATO_0000067 .
obo:STATO_0000571 a rdfs:Class ;
rdfs:label "Partial Least Square regression"@en ;
rdfs:comment """Partial least squares regression (PLS regression) is a data transformation that bears some relation to principal components regression; instead of finding hyperplanes of maximum variance between the response and independent variables, it finds a linear regression model by projecting the predicted variables and the observable variables to a new space. Because both the X and Y data are projected to new spaces, the PLS family of methods are known as bilinear factor models. Partial least squares Discriminant Analysis (PLS-DA) is a variant used when the Y is categorical.
PLS is used to find the fundamental relations between two matrices (X and Y), i.e. a latent variable approach to modeling the covariance structures in these two spaces. A PLS model will try to find the multidimensional direction in the X space that explains the maximum multidimensional variance direction in the Y space. PLS regression is particularly suited when the matrix of predictors has more variables than observations, and when there is multicollinearity among X values. By contrast, standard regression will fail in these cases (unless it is regularized).
Partial least squares was introduced by the Swedish statistician Herman O. A. Wold, who then developed it with his son, Svante Wold. An alternative term for PLS (and more correct according to Svante Wold[1]) is projection to latent structures, but the term partial least squares is still dominant in many areas. Although the original applications were in the social sciences, PLS regression is today most widely used in chemometrics and related areas. It is also used in bioinformatics, sensometrics, neuroscience and anthropology."""@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:OBI_0200175 .
obo:OBI_0001404 a rdfs:Class ;
rdfs:label "genetic characteristics information"@en ;
rdfs:comment "a data item that is about genetic material including polymorphisms, disease alleles, and haplotypes."@en ;
rdfs:subClassOf obo:IAO_0000027 .
obo:OBI_0600036 a rdfs:Class ;
rdfs:label "establishing cell culture" ;
rdfs:comment "a process through which a new type of cell culture or cell line is created, either through the isolation and culture of one or more cells from a fresh source, or the deliberate experimental modification of an existing cell culture (e.g passaging a primary culture to become a secondary culture or line, or the immortalization or stable genetic modification of an existing culture or line)." ;
rdfs:subClassOf obo:OBI_0000094 .
obo:OBI_0400078 a rdfs:Class ;
rdfs:label "obscuration bar"@en ;
rdfs:comment "An obscuration bar is a an optical subsystem which is a strip of metal or other material that serves to block out direct light from the illuminating beam. The obscuration bar prevents the bright light scattered in the forward directions from burning out the collection device."@en ;
rdfs:subClassOf obo:OBI_0000932 .
obo:STATO_0000662 a rdfs:Class ;
rdfs:label "p-value for two-sided test"@en ;
rdfs:comment "A p-value which represents the probability of obtaining a result at least as far, in either direction, from the value actually obtained as the value expected, assuming the null hypothesis is true. A p-value for two-sided test interprets 'at least as far from' with both the direction of 'greater than' and the direction of 'less than'. For hypothesis test interpretation, the two-tailed p-value is compared to the alpha setting divided by 2."@en ;
rdfs:subClassOf obo:OBI_0000071 .
obo:STATO_0000384 a rdfs:Class ;
rdfs:label "contrast estimate"@en ;
rdfs:comment "estimate of a contrast obtained by computing the weighted sum of model parameter estimates using a set of contrast weights."@en ;
rdfs:subClassOf obo:STATO_0000471 .
obo:STATO_0000706 a rdfs:Class ;
rdfs:label "Bayesian inference" ;
rdfs:comment "A statistical inference paradigm in which the assumptions are that parameters are random variables with probability distributions, that prior knowledge can be represented with such distributions, and that one learns from data by updating those prior distributions using Bayes' Rule." ;
rdfs:subClassOf obo:STATO_0000299 .
obo:OBI_0200169 a rdfs:Class ;
rdfs:label "normalization data transformation"@en ;
rdfs:comment "A normalization data transformation is a data transformation that has objective normalization."@en ;
rdfs:subClassOf obo:APOLLO_SV_00000796 , obo:OBI_0200000 .
obo:OBI_0001177 a rdfs:Class ;
rdfs:label "RNA sequencing assay" ;
rdfs:comment "An assay that determines the sequence of an RNA molecule." ;
rdfs:subClassOf obo:OBI_0600047 .
obo:STATO_0000564 a rdfs:Class ;
rdfs:label "coefficient of determination"@en ;
rdfs:comment """The coefficient of determination is a data item measuring the proportion of the variance in the dependent variable that is predictable from the independent variable(s).
In the case of a linear regression mode, the coefficient of determination r2 is the quotient of the variances of the fitted values and observed values of the dependent variable."""@en ;
rdfs:subClassOf obo:STATO_0000039 .
obo:STATO_0000408 a rdfs:Class ;
rdfs:label "2 step Fagan nomogram"@en ;
rdfs:comment "Two-Step Fagan Nomogram, which adds two extra axis between the LR axis that represents sensibility and specificity to calculate negative and positive likelihood ratios in the same nomogram"@en ;
rdfs:subClassOf obo:IAO_0000038 .
obo:OBI_0200094 a rdfs:Class ;
rdfs:label "logarithmic transformation"@en ;
rdfs:comment "A logarithmic transformation is a data transformation consisting in the application of the logarithm function with a given base a (where a>0 and a is not equal to 1) to a (one dimensional) positive real number input. The logarithm function with base a can be defined as the inverse of the exponential function with the same base. See e.g. http://en.wikipedia.org/wiki/Logarithm."@en ;
rdfs:subClassOf obo:OBI_0200169 .
obo:OBI_0000684 a rdfs:Class ;
rdfs:label "specimen collection objective" ;
rdfs:comment "A objective specification to obtain a material entity for potential use as an input during an investigation." ;
rdfs:subClassOf obo:IAO_0000005 .
obo:OBI_0500020 a rdfs:Class ;
rdfs:label "time series design"@en ;
rdfs:comment "Groups of assays that are related as part of a time series."@en ;
rdfs:subClassOf obo:OBI_0500000 .
obo:OBI_0001108 a rdfs:Class ;
rdfs:label "nucleic acid sequencer" ;
rdfs:comment "An device that is used to determine the order of nucleotides in nucleic acid sequences." ;
rdfs:subClassOf obo:OBI_0000832 .
obo:STATO_0000680 a rdfs:Class ;
rdfs:label "incidence rate ratio"@en ;
rdfs:comment "A measure of association that is the ratio of two incidence rates."@en ;
rdfs:subClassOf obo:STATO_0000622 .
obo:STATO_0000732 a rdfs:Class ;
rdfs:label "multiclass categorical variable" ;
rdfs:comment "A nominal variable that can assume two or more values simultaneously." ;
rdfs:subClassOf obo:STATO_0000721 .
obo:STATO_0000060 a rdfs:Class ;
rdfs:label "hypergeometric distribution"@en ;
rdfs:comment "hypergeometric distribution is a probability distribution that describes the probability of k successes in n draws from a finite population of size N containing K successes without replacement"@en ;
rdfs:subClassOf obo:STATO_0000117 .
obo:STATO_0000655 a rdfs:Class ;
rdfs:label "calibration plot" ;
rdfs:comment "calibration plot is a line graph which plots values resulting from predictions againts values obtained through observation." ;
rdfs:subClassOf obo:IAO_0000573 .
obo:STATO_0000250 a rdfs:Class ;
rdfs:label "group comparison objective"@en ;
rdfs:comment "group comparison objective is a data transformation objective which aims to determine if 2 or more study group differ with respect to the signal of a response variable"@en ;
rdfs:subClassOf obo:OBI_0200166 .
obo:STATO_0000131 a rdfs:Class ;
rdfs:label "sphericity test"@en ;
rdfs:comment "a sphericity test is a null hypothesis statistical testing procedure which posits a null hypothesis of equality of the variances of the differences between levels of the repeated measures factor"@en ;
rdfs:subClassOf obo:OBI_0000673 .
obo:STATO_0000261 a rdfs:Class ;
rdfs:label "Newman-Keuls test post-hoc analysis"@en ;
rdfs:comment "The Newman–Keuls or Student–Newman–Keuls (SNK) method is a stepwise multiple comparisons procedure used to identify sample means that are significantly different from each other. It was named after Student (1927), D. Newman, and M. Keuls. This procedure is often used as a post-hoc test whenever a significant difference between three or more sample means has been revealed by an analysis of variance (ANOVA). The Newman–Keuls method is similar to Tukey's range test as both procedures use Studentized range statistics.Compared to Tukey's range test, the Newman–Keuls method is more powerful but less conservative."@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000133 .
obo:IAO_0000129 a rdfs:Class ;
rdfs:label "version number"@en ;
rdfs:comment "A version number is an information content entity which is a sequence of characters borne by part of each of a class of manufactured products or its packaging and indicates its order within a set of other products having the same name."@en ;
rdfs:subClassOf obo:IAO_0000028 .
obo:STATO_0000402 a rdfs:Class ;
rdfs:label "population mean"@en ;
rdfs:comment """the population mean or distribution mean is a parameter of a probability distribution or population indicative of the data dispersion. For continous probabibility distribution, the population mean is computed using the probability density function, for discrete probability distributions, a mass density function is used instead.
A population mean can be estimated by computing a sample mean"""@en ;
rdfs:subClassOf obo:STATO_0000029 .
a rdfs:Class .
obo:STATO_0000035 a rdfs:Class ;
rdfs:label "range"@en ;
rdfs:comment "the range is a measure of variation which describes the difference between the lowest score and the highest score in a set of numbers (a data set)" ;
rdfs:subClassOf obo:STATO_0000028 .
obo:OBI_0500016 a rdfs:Class ;
rdfs:label "fractional factorial design"@en ;
rdfs:comment "A fractional factorial design is_a study design in which only an adequately chosen fraction of the treatment combinations required for the complete factorial experiment is selected to be run"@en ;
rdfs:subClassOf obo:OBI_0500014 .
obo:STATO_0000521 a rdfs:Class ;
rdfs:label "substitution by the mean data imputation"@en ;
rdfs:comment "substitution by the mean data imputation is a type of data imputation where missing values are replaced with the value the variable mean." ;
rdfs:subClassOf obo:STATO_0000518 .
obo:STATO_0000075 a rdfs:Class ;
rdfs:label "rarefaction curve"@en ;
rdfs:comment "a rarefaction curve is a graph used for estimating species richness in ecology studies"@en ;
rdfs:subClassOf obo:IAO_0000573 .
obo:STATO_0000329 a rdfs:Class ;
rdfs:label "symmetric distribution"@en ;
rdfs:comment "Probability distribution which has no skew so its skewness=0"@en ;
rdfs:subClassOf obo:STATO_0000225 .
obo:PATO_0001241 a rdfs:Class ;
rdfs:label "physical object quality" ;
rdfs:comment "A quality which inheres in a continuant." ;
rdfs:subClassOf obo:BFO_0000019 .
obo:STATO_0000666 a rdfs:Class ;
rdfs:label "maximum possible value"@en ;
rdfs:comment "A statistic that represents the largest value that could occur."@en ;
rdfs:subClassOf obo:STATO_0000039 .
obo:OBI_0000113 a rdfs:Class ;
rdfs:label "sequence feature identification objective"@en ;
rdfs:comment "Sequence_feature_identification_objective is a biological_feature_identification_objective role describing a study designed to examine or characterize molecular features exhibited at the level of a macromolecular sequence, e.g. nucleic acid, protein, polysaccharide."@en ;
rdfs:subClassOf obo:OBI_0000015 .
obo:STATO_0000420 a rdfs:Class ;
rdfs:label "I-squared"@en ;
rdfs:comment """The quantity called I2, describes the percentage of total variation across studies that is due to heterogeneity rather than chance. I2 can be readily calculated from basic results obtained from a typical meta-analysis as I2 = 100%×(Q - df)/Q, where Q is Cochran's heterogeneity statistic and df the degrees of freedom. Negative values of I2 are put equal to zero so that I2 lies between 0% and 100%. A value of 0% indicates no observed heterogeneity, and larger values show increasing heterogeneity.
Unlike Cochran's Q, it does not inherently depend upon the number of studies considered. A confidence interval for I² is constructed using either i) the iterative non-central chi-squared distribution method of Hedges and Piggott (2001); or ii) the test-based method of Higgins and Thompson (2002). The non-central chi-square method is currently the method of choice (Higgins, personal communication, 2006) – it is computed if the 'exact' option is selected."""@en ;
rdfs:subClassOf obo:STATO_0000418 .
obo:STATO_0000343 a rdfs:Class ;
rdfs:label "genotype data set" ;
rdfs:comment "a dataset which is made up of genotypic information, that is presenting allele information at specific loci in a set of individuals of an organism." ;
rdfs:subClassOf obo:IAO_0000100 .
obo:STATO_0000462 a rdfs:Class ;
rdfs:label "Pocock boundary analysis"@en ;
rdfs:comment """The Pocock boundary analysis gives a p-value threshold for each interim analysis which guides the data monitoring committee on whether to stop the trial. The boundary used depends on the number of interim analyses.
The Pocock boundary is simple to use in that the p-value threshold is the same at each interim analysis. The disadvantages are that the number of interim analyses must be fixed at the start and it is not possible under this scheme to add analyses after the trial has started. Another disadvantage is that investigators and readers frequently do not understand how the p-values are reported: for example, if there are five interim analyses planned, but the trial is stopped after the third interim analysis because the p-value was 0.01, then the overall p-value for the trial is still reported as <0.05 and not as 0.01.
As all frequentist methods of the same type, it focuses on controlling the type I error rate as the repeated hypothesis testing of accumulating data increases the type I error rate of a clinical trial."""@en ;
rdfs:subClassOf obo:STATO_0000460 .
obo:STATO_0000301 a rdfs:Class ;
rdfs:label "covariance"@en ;
rdfs:comment """The covariance is a measurement data item about the strength of correlation between a set (2 or more) of random variables.
The covariance is obtained by forming:
cov(X,Y)=E([X-E(X)][Y-E(Y)] where E(X), E(Y) is the expected value (mean) of variable X and Y respectively.
covariance is symmetric so cov(X,Y)=cov(Y,X).
The covariance is usefull when looking at the variance of the sum of the 2 random variables since:
var(X+Y) = var(X) +var(Y) +2cov(X,Y)
The covariance cov(x,y) is used to obtain the coefficient of correlation cor(x,y) by normalizing (dividing) cov(x,y) but the product of the standard deviations of x and y."""@en ;
rdfs:subClassOf obo:STATO_0000611 .
obo:STATO_0000690 a rdfs:Class ;
rdfs:label "area under the value-time curve" ;
rdfs:comment "An area under the curve where the curve is the repeated measures of a variable over time and the domain of interest is time." ;
rdfs:subClassOf obo:STATO_0000209 .
obo:STATO_0000009 a rdfs:Class ;
rdfs:label "cartesian coordinate system"@en ;
rdfs:comment "A Cartesian coordinate system is a coordinate system that specifies each point uniquely in a plane by a pair of numerical coordinates, which are the signed distances from the point to two fixed perpendicular directed lines, measured in the same unit of length." ;
rdfs:subClassOf obo:STATO_0000010 .
obo:BFO_0000141 a rdfs:Class ;
rdfs:label "immaterial entity"@en ;
rdfs:subClassOf obo:BFO_0000004 .
obo:STATO_0000613 a rdfs:Class ;
rdfs:label "difference"@en ;
rdfs:comment "A statistic that is a subtraction of one quantity from another."@en ;
rdfs:subClassOf obo:STATO_0000039 .
obo:STATO_0000332 a rdfs:Class ;
rdfs:label "smooth kernel distribution"@en ;
rdfs:comment "Probability distribution estimated using a smooth kernel function to avoid making assumptions about the distribution of the data. The kernel density estimator is the estimated probability density function (pdf) of the random variable."@en ;
rdfs:subClassOf obo:STATO_0000225 .
obo:STATO_0000451 a rdfs:Class ;
rdfs:label "Pillai's trace"@en ;
rdfs:comment "Pillai trace is a statistic used for the following three tests during a multivariate analysis of variance: (a) equality of mean vectors of lp‐variate normal distributions with the common but unknown covariance matrix, (b) independence between two sets of variates distributed jointly as a normal distribution with unknown mean vector, and (c) equality of covariance matrices of two p‐variate normal distributions with unknown mean vectors."@en ;
rdfs:subClassOf obo:STATO_0000039 .
obo:STATO_0000287 a rdfs:Class ;
rdfs:label "two tailed test"@en ;
rdfs:comment "a two tailed test is a statistical test which assess the null hypothesis of absence of difference assuming a symmetric (not skewed) underlying probability distribution by allocating half of the significance level selected to each of the direction of change which could explain a difference (for example, a difference can be an excess or a loss)."@en ;
rdfs:subClassOf obo:OBI_0000673 , obo:OBI_0200000 .
obo:GO_0010467 a rdfs:Class ;
rdfs:label "gene expression" ;
rdfs:comment "The process in which a gene's sequence is converted into a mature gene product or products (proteins or RNA). This includes the production of an RNA transcript as well as any processing to produce a mature RNA product or an mRNA or circRNA (for protein-coding genes) and the translation of that mRNA or circRNA into protein. Protein maturation is included when required to form an active form of a product from an inactive precursor form." ;
rdfs:subClassOf obo:GO_0008150 .
obo:OBI_0001936 a rdfs:Class ;
rdfs:label "molecular-labeled material" ;
rdfs:comment "a material entity that is the specified output of an addition of molecular label process that aims to label some molecular target to allow for its detection in a detection of molecular label assay" ;
rdfs:subClassOf obo:BFO_0000040 , obo:OBI_0000047 .
obo:STATO_0000220 a rdfs:Class ;
rdfs:label "false negative rate"@en ;
rdfs:comment "the false negative rate is a data item which denotes the proportion of missed detection of elements known to be meeting the detection criteria"@en ;
rdfs:subClassOf obo:STATO_0000607 .
obo:STATO_0000496 a rdfs:Class ;
rdfs:label "P matrix" ;
rdfs:comment "P matrix is a kind of genomic relationship matrix which contains allele frequencies expressed as a difference from 0.5 and multiplied by 2." ;
rdfs:subClassOf obo:STATO_0000642 .
obo:STATO_0000510 a rdfs:Class ;
rdfs:label "quota sampling"@en ;
rdfs:comment """Quota sampling is a method for selecting survey participants that is a non-probabilistic version of stratified sampling.
In quota sampling, a population is first segmented into mutually exclusive sub-groups, just as in stratified sampling. Then judgment is used to select the subjects or units from each segment based on a specified proportion. For example, an interviewer may be told to sample 200 females and 300 males between the age of 45 and 60. This means that individuals can put a demand on who they want to sample (targeting)."""@en ;
rdfs:subClassOf obo:STATO_0000502 .
obo:STATO_0000740 a rdfs:Class ;
rdfs:label "adjusted alpha level" ;
rdfs:comment "An alpha level that is adjusted for multiple comparisons to preserve the intended overall probability cutoff." ;
rdfs:subClassOf obo:STATO_0000738 .
obo:STATO_0000120 a rdfs:Class ;
rdfs:label "bean plot" ;
rdfs:comment """beanplot is a plot in which (one or) multiple batches (\"beans\") are shown. Each bean consists of a density trace, which is mirrored to
form a polygon shape. Next to that, a one-dimensional scatter plot shows all the individual measurements, like in a stripchart.
The name beanplot stems from green beans. The density shape can be seen as the pod of a green bean, while the scatter plot shows the seeds inside the pod."""@en ;
rdfs:subClassOf obo:IAO_0000038 .
obo:STATO_0000536 a rdfs:Class ;
rdfs:label "Gibbs sampling" ;
rdfs:comment "Gibbs sampling or a Gibbs sampler is a Markov chain Monte Carlo (MCMC) algorithm for obtaining a sequence of observations which are approximated from a specified multivariate probability distribution, when direct sampling is difficult." ;
rdfs:subClassOf obo:STATO_0000535 .
obo:OBI_0000938 a rdfs:Class ;
rdfs:label "categorical measurement datum" ;
rdfs:comment "A measurement datum that is reported on a categorical scale" ;
rdfs:subClassOf obo:IAO_0000109 .
obo:NCBITaxon_2157 a rdfs:Class ;
rdfs:label "Archaea" ;
rdfs:subClassOf obo:OBI_0100026 .
obo:OBI_0200171 a rdfs:Class ;
rdfs:label "partitioning data transformation"@en ;
rdfs:comment "A partitioning data transformation is a data transformation that has objective partitioning."@en ;
rdfs:subClassOf obo:OBI_0200000 .
obo:STATO_0000547 a rdfs:Class ;
rdfs:label "Laplace probability distribution" ;
rdfs:comment "The double exponential distribution (a.k.a. Laplace distribution) is the distribution of differences between two independent variates with identical exponential distributions (Abramowitz and Stegun 1972, p. 930)."@en ;
rdfs:subClassOf obo:STATO_0000067 , obo:STATO_0000329 .
obo:STATO_0000046 a rdfs:Class ;
rdfs:label "block design"@en ;
rdfs:comment "a block design is a kind of study design which declares a blocking variable (also known as nuisance variable) in order to account for a known source of variation and reduce its impact on the acquisition of the signal"@en ;
rdfs:subClassOf obo:OBI_0500000 .
obo:OBI_0001305 a rdfs:Class ;
rdfs:label "genotype information"@en ;
rdfs:comment "a genetic characteristics information that is about the genetic material of an organism and minimally includes information about the genetic background and can in addition contain information about specific alleles, genetic modifications, etc."@en ;
rdfs:subClassOf obo:OBI_0001404 .
obo:STATO_0000201 a rdfs:Class ;
rdfs:label "Spearman's rank correlation coefficient"@en ;
rdfs:comment """Spearman's rank correlation coefficient is a correlation coefficient which is a nonparametric measure of statistical dependence between two ranked variables. It assesses how well the relationship between two variables can be described using a monotonic function. If there are no repeated data values, a perfect Spearman correlation of +1 or −1 occurs when each of the variables is a perfect monotone function of the other.
Spearman's coefficient may be used when the conditions for computing Pearson's correlation are not met (e.g linearity, normality of the 2 continuous variables) but may require a ranking transformation of the variables"""@en ;
rdfs:subClassOf obo:STATO_0000142 .
obo:CL_0000010 a rdfs:Class ;
rdfs:label "cultured cell" ;
rdfs:comment "A cell in vitro that is or has been maintained or propagated as part of a cell culture." ;
rdfs:subClassOf obo:CL_0000578 .
obo:STATO_0000190 a rdfs:Class ;
rdfs:label "threshold cycle"@en ;
rdfs:comment "Threshold cycle (or Ct or Cq) is a count which is defined as the fractional PCR cycle number at which the reporter fluorescence is greater than the threshold in the context of the RT-qPCR assay. The Ct is a basic principle of real time PCR and is an essential component in producing accurate and reproducible data."@en ;
rdfs:subClassOf obo:STATO_0000232 .
obo:STATO_0000086 a rdfs:Class ;
rdfs:label "F-test"@en ;
rdfs:comment "an F-test is a statistical test which evaluates that the computed test statistics follows an F-distribution under the null hypothesis. The F-test is sensitive to departure from normality. F-test arise when decomposing the variability in a data set in terms of sum of squares."@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000191 .
obo:STATO_0000232 a rdfs:Class ;
rdfs:label "number of PCR cycle"@en ;
rdfs:comment "number of PCR cycle is a count which enumerates how many iterations of 'annealing, renaturation, amplification,' rounds (or cycles) are performed during a polymerase chain reaction (PCR) or an assay relying on PCR."@en ;
rdfs:subClassOf obo:STATO_0000047 .
obo:STATO_0000318 a rdfs:Class ;
rdfs:label "omega-squared"@en ;
rdfs:comment "omega-squared is a effect size estimate for variance explained which is less biased than the eta-squared coefficient."@en ;
rdfs:subClassOf obo:STATO_0000085 , obo:STATO_0000471 .
obo:STATO_0000689 a rdfs:Class ;
rdfs:label "partial area under the receiver operator characteristic curve" ;
rdfs:comment "An area under the curve where the curve is the true positive rate and the range of interest is a specified portion of the range of possible values for the false positive rate and/or range of possible values for the true positive rate."@en ;
rdfs:subClassOf obo:STATO_0000209 .
obo:IAO_0000308 a rdfs:Class ;
rdfs:label "figure"@en ;
rdfs:comment "An information content entity consisting of a two dimensional arrangement of information content entities such that the arrangement itself is about something."@en ;
rdfs:subClassOf obo:IAO_0000030 .
obo:STATO_0000582 a rdfs:Class ;
rdfs:label "best linear unbiased estimator"@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000119 , obo:STATO_0000337 .
obo:STATO_0000441 a rdfs:Class ;
rdfs:label "Grubbs' test"@en ;
rdfs:comment "Grubbs' test is a statistical test used to detect one outlier in a univariate data set assumed to come from a normally distributed population."@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000443 .
obo:STATO_0000247 a rdfs:Class ;
rdfs:label "odds ratio homogeneity test"@en ;
rdfs:comment "odds ratio homogeneity test is a statistical test which aims to evaluate that null the hypothesis of consistency odds ratio accross different strata of population is true or not"@en ;
rdfs:subClassOf obo:OBI_0000673 .
obo:STATO_0000678 a rdfs:Class ;
rdfs:label "prevalence ratio"@en ;
rdfs:comment "A measure of association that is the ratio of two prevalences."@en ;
rdfs:subClassOf obo:STATO_0000622 .
obo:IAO_0000028 a rdfs:Class ;
rdfs:label "symbol"@en ;
rdfs:comment "An information content entity that is a mark(s) or character(s) used as a conventional representation of another entity."@en ;
rdfs:subClassOf obo:IAO_0000030 .
obo:STATO_0000430 a rdfs:Class ;
rdfs:label "meta analysis by Hartung-Knapp-Sidik-Jonkman method"@en ;
rdfs:comment "a random effect meta analysis procedure defined by Hartung and Knapp and by Sidik and Jonkman which performs better than DerSimonian and Laird approach, especially when there is heterogeneity and the number of studies in the meta-analysis is small."@en ;
rdfs:subClassOf obo:STATO_0000155 .
obo:STATO_0000303 a rdfs:Class ;
rdfs:label "two sample t-test with equal variance"@en ;
rdfs:comment """two sample t-test is a null hypothesis statistical test which is used to reject or accept the hypothesis of absence of difference between the means over 2 randomly sampled populations.
It uses a t-distribution for the test and assumes that the variables in the population are normally distributed and with equal variances."""@en ;
rdfs:subClassOf obo:OBI_0000739 , obo:OBI_0200000 , obo:STATO_0000279 .
obo:STATO_0000272 a rdfs:Class ;
rdfs:label "Michaelis-Menten constant"@en ;
rdfs:comment "The Michaelis constant is the substrate concentration at which the reaction rate is at half-maximum, and is an inverse measure of the substrate's affinity for the enzyme—as a small indicates high affinity, meaning that the rate will approach more quickly.[5] The value of is dependent on both the enzyme and the substrate, as well as conditions such as temperature and pH."@en ;
rdfs:subClassOf obo:IAO_0000032 .
obo:BFO_0000040 a rdfs:Class ;
rdfs:label "material entity"@en ;
rdfs:comment "An independent continuant that is spatially extended whose identity is independent of that of other entities and can be maintained through time."@en ;
rdfs:subClassOf obo:BFO_0000004 .
obo:STATO_0000705 a rdfs:Class ;
rdfs:label "measurement accuracy as a percentage" ;
rdfs:comment """Measurement accuracy refers to how close a measured value is to the true or accepted value of the quantity being measured.
It is a percentage in which the numerator represents the absolute value of one minus the difference between the true value and the observed value, and the denominator represents the true value.
Accuracy is often expressed as a percentage of the true value, based on the relative error:
Accuracy (%)= (1 −∣Measured Value−True Value∣/True Value)×100
True Value: The reference or accepted value.
Measured Value: The value obtained during the measurement.""" ;
rdfs:subClassOf obo:STATO_0000639 .
obo:OBI_0000973 a rdfs:Class ;
rdfs:label "sequence data"@en ;
rdfs:comment """A measurement datum that representing the primary structure of a macromolecule(it's sequence) sometimes associated with an indicator of confidence of that measurement.
""" ;
rdfs:subClassOf obo:IAO_0000109 .
obo:IAO_0000577 a rdfs:Class ;
rdfs:label "centrally registered identifier symbol"@en ;
rdfs:comment "A symbol that is part of a CRID and that is sufficient to look up a record from the CRID's registry."@en ;
rdfs:subClassOf obo:IAO_0000028 .
obo:STATO_0000008 a rdfs:Class ;
rdfs:label "y-axis"@en ;
rdfs:comment "y-axis is a cartesian coordinate axis which is orthogonal to the x-axis and the z-axis"@en ;
rdfs:subClassOf obo:STATO_0000011 .
obo:OBI_0500006 a rdfs:Class ;
rdfs:label "parallel group design"@en ;
rdfs:comment "A parallel group design or independent measure design is a study design which uses unique experimental unit each experimental group, in other word no two individuals are shared between experimental groups, hence also known as parallel group design. Subjects of a treatment group receive a unique combination of independent variable values making up a treatment"@en ;
rdfs:subClassOf obo:OBI_0500000 .
obo:STATO_0000580 a rdfs:Class ;
rdfs:label "variable importance in projection" ;
rdfs:comment "variable importance in projection is a measure computed as part of a partial least square regression to accumulate the importance of each variable j being reflected by w from each component." ;
rdfs:subClassOf obo:STATO_0000039 .
obo:STATO_0000291 a rdfs:Class ;
rdfs:label "quantile"@en ;
rdfs:comment """a quantile is a data item which corresponds to specific elements x in the range of a variate X.
the k-th n-tile P_k is that value of x, say x_k, which corresponds to a cumulative frequency of Nk/n (Kenney and Keeping 1962). If n=4, the quantity is called a quartile, and if n=100, it is called a percentile."""@en ;
rdfs:subClassOf obo:STATO_0000039 .
obo:STATO_0000541 a rdfs:Class ;
rdfs:label "state space model" ;
rdfs:comment "a state space model is a kind of statistical model which describes the probabilistic dependence between the latent state variable and the observed measurement. The state or the measurement can be either continuous or discrete. The term “state space” originated in 1960s in the area of control engineering (Kalman, 1960). SSM provides a general framework for analyzing deterministic and stochastic dynamical systems that are measured or observed through a stochastic process." ;
rdfs:subClassOf obo:STATO_0000107 .
obo:OBI_0002743 a rdfs:Class ;
rdfs:label "molecular label role"@en ;
rdfs:comment "A reagent role inhering in a molecular entity intended to associate with some molecular target to serve as a proxy for the presence, abundance, or location of this target in a detection of molecular label assay."@en ;
rdfs:subClassOf obo:OBI_0000086 .
obo:STATO_0000591 a rdfs:Class ;
rdfs:label "TMM-trimmed mean of M-values corrected count" ;
rdfs:comment """TMM or Trimmed Mean of M-Values is a measurement datum which is the output of the TMM normalization procedure for RNA-Seq data proposed by Robinson and Oshlack (2010). A scaling normalization method for differential expression analysis of RNA-seq data.
The TMM procedure is doubly trimmed, by log-fold-changes (sample k relative to sample r for gene g) and by absolute intensity (A g ).
It was first release as part of the R package edgeR, 10.1093/bioinformatics/btp616
Recommended use:
-TMM measure is suited for gene count comparisons within a sample or between samples of the same sample group.
-TMM measure is suited for Differential Expression analysis.""" ;
rdfs:subClassOf obo:STATO_0000047 .
obo:STATO_0000611 a rdfs:Class ;
rdfs:label "measure of correlation"@en ;
rdfs:comment """measure of correlation is a measure of association between ordinal or continuous variables.
A value of 0 means no association.
A positive value means a positive association (as one variable increases, the other variable increases).
A negative value means a negative association (as one variable increases, the other variable decreases).
For correlation coefficients, the possible values range from +1 (perfect positive association) to -1 (perfect negative association)"""@en ;
rdfs:subClassOf obo:STATO_0000610 .
obo:OBI_0000747 a rdfs:Class ;
rdfs:label "material sample" ;
rdfs:comment "A material entity that has the material sample role" ;
rdfs:subClassOf obo:BFO_0000040 , obo:OBI_0100051 .
obo:OBI_0200117 a rdfs:Class ;
rdfs:label "mode calculation"@en ;
rdfs:comment "A mode calculation is a descriptive statistics calculation in which the mode is calculated which is the most common value in a data set. It is most often used as a measure of center for discrete data."@en ;
rdfs:subClassOf obo:APOLLO_SV_00000796 , obo:OBI_0200181 , obo:OBI_0200184 .
obo:OBI_0000070 a rdfs:Class ;
rdfs:label "assay"@en ;
rdfs:comment "A planned process with the objective to produce information about the material entity that is the evaluant, by physically examining it or its proxies."@en ;
rdfs:subClassOf obo:OBI_0000011 .
obo:STATO_0000191 a rdfs:Class ;
rdfs:label "goodness of fit statistical test" ;
rdfs:comment "a goodness of fit statistical test is a statistical test which aim to evaluate if a sample distribution can be considered equivalent to a theoretical distribution used as input"@en ;
rdfs:subClassOf obo:OBI_0000673 .
obo:STATO_0000718 a rdfs:Class ;
rdfs:label "superiority testing" ;
rdfs:comment "a type of between group comparison test with the intent to compare two or more interventions or exposures and to determine that the absolute value of any difference in effects is larger than a prespecified value representing a meaningful difference." ;
rdfs:subClassOf obo:STATO_0000715 .
obo:STATO_0000280 a rdfs:Class ;
rdfs:label "Pearson's correlation coefficient"@en ;
rdfs:comment """The Pearson's correlation coefficient is a correlation coefficient which evaluates two continuous variables for association strength in a data sample. It assumes that both variables are normally distributed and linearity exists.
The coefficient is calculated by dividing their covariance with the product of their individual standard deviations. It is a normalized measurement of how the two are linearly related."""@en ;
rdfs:subClassOf obo:STATO_0000142 .
obo:STATO_0000371 a rdfs:Class ;
rdfs:label "weighted least squares estimation"@en ;
rdfs:comment "the weighted least squares estimation is a model parameter estimation for a linear regression model with errors that independent but have heterogeneous variance. Difficult to use use in practice, as weights must be set based on the variance which is usually unknown. If true variance is known, it is the Best Linear Unbiased Estimation (BLUE) method under these assumptions, Uniformly Minimum-Variance Unbiased Estimator (UMVUE) with addition of a Gaussian assumption."@en ;
rdfs:subClassOf obo:STATO_0000119 .
obo:IAO_0000402 a rdfs:Class ;
rdfs:label "two dimensional cartesian spatial coordinate datum"@en ;
rdfs:comment "A cartesion spatial coordinate datum that uses two values to specify a position within a two dimensional spatial region"@en ;
rdfs:subClassOf obo:IAO_0000400 .
obo:IAO_0000404 a rdf:Property ;
rdfs:label "has x coordinate value"@en ;
rdfs:domain obo:IAO_0000400 ;
rdfs:range xsd:float .
obo:IAO_0000406 a rdf:Property ;
rdfs:label "has y coordinate value"@en ;
rdfs:domain obo:IAO_0000400 ;
rdfs:range xsd:float .
obo:IAO_0000407 a rdf:Property ;
rdfs:label "has coordinate unit label"@en ;
rdfs:comment "relating a cartesian spatial coordinate datum to a unit label that together with the values represent a point"@en ;
rdfs:domain obo:IAO_0000400 ;
rdfs:range obo:UO_0000001 ;
rdfs:subPropertyOf obo:BFO_0000051 .
obo:OBI_0000275 a rdfs:Class ;
rdfs:label "analyte role"@en ;
rdfs:comment "A measurand role borne by a molecular entity or an atom and realized in an analyte assay which achieves the objective to measure the magnitude/concentration/amount of the analyte in the entity bearing evaluant role."@en ;
rdfs:subClassOf obo:OBI_0002444 .
obo:RO_0000081 a rdf:Property ;
rdfs:label "role of"@en ;
rdfs:comment "a relation between a role and an independent continuant (the bearer), in which the role specifically depends on the bearer for its existence"@en ;
rdfs:range ;
rdfs:subPropertyOf obo:RO_0000052 .
obo:STATO_0000622 a rdfs:Class ;
rdfs:label "ratio-based measure of association"@en ;
rdfs:comment "ratio-based measure of association is a measure of association which relies on a quotient of 2 quantities to indicate the strength of the association."@en ;
rdfs:subClassOf obo:STATO_0000184 , obo:STATO_0000610 .
obo:STATO_0000465 a rdfs:Class ;
rdfs:label "empirical measure"@en ;
rdfs:comment "An empirical measure is a random measure arising from a particular realization of a (usually finite) sequence of random variables."@en ;
rdfs:subClassOf obo:IAO_0000027 .
obo:OBI_0000932 a rdfs:Class ;
rdfs:label "material separation device" ;
rdfs:comment "A device with a separation function realized in a planed process" ;
rdfs:subClassOf obo:OBI_0000968 .
obo:STATO_0000031 a rdfs:Class ;
rdfs:label "binary classification"@en ;
rdfs:comment "binary classification (or binomial classification) is a data transformation which aims to cast members of a set into 2 disjoint groups depending on whether the element have a given property/feature or not."@en ;
rdfs:subClassOf obo:OBI_0200000 .
obo:STATO_0000048 a rdfs:Class ;
rdfs:label "multiway ANOVA"@en ;
rdfs:comment "Multi-way anova is an analysis of variance where the difference groups being compared are associated to the factor levels of more than 2 independent variables. The null hypothesis is an absence of difference between the means calculated for each of the groups. The test assumes normality and equivariance of the data."@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:OBI_0200201 .
obo:STATO_0000167 a rdfs:Class ;
rdfs:label "first quartile"@en ;
rdfs:comment "the first quartile is a quartile which splits the lower 25 % of the data"@en ;
rdfs:subClassOf obo:STATO_0000152 .
obo:STATO_0000735 a rdfs:Class ;
rdfs:label "not statistically significant" ;
rdfs:comment "a conclusion based on the outcome of statistical test means the result of a hypothesis test does not support rejection of the null hypothesis at the specified alpha level." ;
rdfs:subClassOf obo:OBI_0001909 .
obo:OBI_0000124 a rdf:Property ;
rdfs:label "is_supported_by_data" ;
rdfs:comment "The relation between a data item and a conclusion where the conclusion is the output of a data interpreting process and the data item is used as an input to that process" ;
rdfs:domain obo:OBI_0001909 ;
rdfs:range obo:IAO_0000027 .
obo:STATO_0000635 a rdfs:Class ;
rdfs:label "number needed to treat" ;
rdfs:comment """A statistic that represents the number of units that needs to be treated to prevent one additional undesired outcome. The Number Needed to Treat is calculated as the reciprocal of a treatment effect estimate, where the effect estimate is expressed as a risk difference.
The Number Needed to Treat (NNT) value is often rounded up to the next highest whole integer""" ;
rdfs:subClassOf obo:STATO_0000634 .
obo:STATO_0000100 a rdfs:Class ;
rdfs:label "standardized mean difference"@en ;
rdfs:comment """standardized mean difference is statistic computed by forming the difference between two means, divided by an estimate of the within-group standard deviation.
It is used to provide an estimation of the effect size between two treatments when the predictor (independent variable) is categorical and the response(dependent) variable is continuous.
A standardized mean difference is a statistic that is a difference between two means, divided by a statistical measure of dispersion.
The term Standardized Mean Difference is a description of the concept without an explicit type of statistical measure of dispersion. If the statistical measure of dispersion is specified, then a type (child term) of Standardized Mean Difference is preferred."""@en ;
rdfs:subClassOf obo:STATO_0000085 , obo:STATO_0000613 .
obo:STATO_0000071 a rdfs:Class ;
rdfs:label "reaction rate"@en ;
rdfs:comment "reaction rate is a measurement datum which represents the speed of a chemical reaction turning reactive species into product species of event (i.e the number of such conversions)s occuring over a time interval"@en ;
rdfs:subClassOf obo:STATO_0000645 .
obo:OBI_0200184 a rdfs:Class ;
rdfs:label "descriptive statistical calculation data transformation"@en ;
rdfs:comment "A descriptive statistical calculation data transformation is a data transformation that has objective descriptive statistical calculation and which concerns any calculation intended to describe a feature of a data set, for example, its center or its variability."@en ;
rdfs:subClassOf obo:APOLLO_SV_00000796 , obo:OBI_0200000 .
obo:STATO_0000378 a rdfs:Class ;
rdfs:label "deviance information criterion"@en ;
rdfs:comment """The deviance information criterion (DIC) is a hierarchical modeling generalization of the AIC (Akaike information criterion) and BIC (Bayesian information criterion, also known as the Schwarz criterion). It is particularly useful in Bayesian model selection problems where the posterior distributions of the models have been obtained by Markov chain Monte Carlo (MCMC) simulation. Like AIC and BIC it is an asymptotic approximation as the sample size becomes large. It is only valid when the posterior distribution is approximately multivariate normal.
The deviance information criterion was published in 2002 by Spiegelhalter et al.
Spiegelhalter, D. J., N. G. Best, B. P. Carlin, and A. van der Linde, 2002. Bayesian measures of model complexity and fit. Journal of the Royal Statistical Society, B, 64, 583-639."""@en ;
rdfs:subClassOf obo:IAO_0000109 .
obo:STATO_0000005 a rdfs:Class ;
rdfs:label "single factor design"@en ;
rdfs:comment "a single factor design is a study design which declares exactly 1 independent variable"@en ;
rdfs:subClassOf obo:OBI_0500000 .
obo:STATO_0000240 a rdfs:Class ;
rdfs:label "Kendall's correlation coefficient"@en ;
rdfs:comment "Kendall's correlation coefficient is a correlation coefficient between 2 ordinal variables (natively or following a ranking procedure) and may be used when the conditions for computing Pearson's correlation are not met (e.g linearity, normality of the 2 continuous variables)"@en ;
rdfs:subClassOf obo:STATO_0000142 .
obo:STATO_0000251 a rdfs:Class ;
rdfs:label "continuous variable"@en ;
rdfs:comment "A continuous variable is one for which, within the limits the variable ranges, any value is possible."@en ;
rdfs:subClassOf obo:STATO_0000258 , obo:STATO_0000722 .
obo:CL_0000000 a rdfs:Class ;
rdfs:label "cell"@en ;
rdfs:comment "A material entity of anatomical origin (part of or deriving from an organism) that has as its parts a maximally connected cell compartment surrounded by a plasma membrane." ;
rdfs:subClassOf obo:BFO_0000040 .
obo:IAO_0000309 a rdfs:Class ;
rdfs:label "diagram"@en ;
rdfs:comment "A figure that expresses one or more propositions"@en ;
rdfs:subClassOf obo:IAO_0000308 .
obo:STATO_0000053 a rdfs:Class ;
rdfs:label "false positive rate"@en ;
rdfs:comment "a false positive rate is a data item which accounts for the proportion of incorrect rejection of a true null hypothesis."@en ;
rdfs:subClassOf obo:STATO_0000607 .
obo:IAO_0000100 a rdfs:Class ;
rdfs:label "data set"@en ;
rdfs:comment "A data item that is an aggregate of other data items of the same type that have something in common. Averages and distributions can be determined for data sets."@en ;
rdfs:subClassOf obo:IAO_0000027 .
obo:STATO_0000027 a rdfs:Class ;
rdfs:label "test of association between categorical variables"@en ;
rdfs:comment "linkage between 2 categorical variable test is a statistical test which evaluates if there is an association between a predictor variable assuming discrete values and a response variable also assuming discrete values"@en ;
rdfs:subClassOf obo:OBI_0000673 .
obo:OBI_0200043 a rdfs:Class ;
rdfs:label "average linkage hierarchical clustering"@en ;
rdfs:comment "An average linkage hierarchical clustering is an agglomerative hierarchical clustering which generates successive clusters based on a distance measure, where the distance between two clusters is calculated as the average distance between objects from the first cluster and objects from the second cluster."@en ;
rdfs:subClassOf obo:OBI_0200154 .
obo:STATO_0000227 a rdfs:Class ;
rdfs:label "normal distribution"@en ;
rdfs:comment """a normal distribution is a continuous probability distribution described by a probability distribution function described here:
http://mathworld.wolfram.com/NormalDistribution.html"""@en ;
rdfs:subClassOf obo:STATO_0000067 , obo:STATO_0000329 .
obo:STATO_0000342 a rdfs:Class ;
rdfs:label "genomic selection objective"@en ;
rdfs:comment "genomic selection objective is a data transformation objective which is a special case of marker-assisted selection in which genetic markers covering the whole genome are used so that all quantitative trait loci (QTL) are in linkage disequilibrium with at least one marker."@en ;
rdfs:subClassOf obo:OBI_0200166 .
obo:OBI_0600028 a rdfs:Class ;
rdfs:label "artificially induced reverse transcription"@en ;
rdfs:comment "a protocol with the objective to transcribe single-stranded RNA into complementary DNA (cDNA)"@en ;
rdfs:subClassOf obo:OBI_0000094 .
obo:STATO_0000194 a rdfs:Class ;
rdfs:label "cartesian product 2 sets"@en ;
rdfs:comment "self explanatory"@en ;
rdfs:subClassOf obo:STATO_0000192 .
obo:STATO_0000727 a rdfs:Class ;
rdfs:label "interval variable" ;
rdfs:comment "A continuous variable with ordered, equally spaced units where the difference between values is meaningful, but no true zero point exists." ;
rdfs:subClassOf obo:STATO_0000251 .
obo:STATO_0000216 a rdfs:Class ;
rdfs:label "stratum population" ;
rdfs:comment "a stratum population is a population resulting from a population stratification prior to sampling process which aims to produce homogenous subpopulations from an heterogeneous population by applying one or more stratification criteria"@en ;
rdfs:subClassOf obo:OBI_0000047 , obo:OBI_0000181 .
obo:STATO_0000003 a rdfs:Class ;
rdfs:label "balanced design"@en ;
rdfs:comment "a balanced design is a an experimental design where all experimental group have the an equal number of subject observations"@en ;
rdfs:subClassOf obo:OBI_0500000 .
obo:IAO_0000572 a rdfs:Class ;
rdfs:label "documenting"@en ;
rdfs:comment "A planned process in which a document is created or added to by including the specified input in it."@en ;
rdfs:subClassOf obo:OBI_0000011 .
obo:OBI_0200155 a rdfs:Class ;
rdfs:label "divisive hierarchical clustering"@en ;
rdfs:comment "A divisive hierarchical clustering is a hierarchical clustering which starts with a single cluster and then successively splits resulting clusters until only clusters of individual objects remain."@en ;
rdfs:subClassOf obo:OBI_0200042 .
obo:OBI_1110109 a rdfs:Class ;
rdfs:label "target of material addition" ;
rdfs:comment "A material entity into which another is being added in a material combinatino process" ;
rdfs:subClassOf obo:BFO_0000040 .
obo:STATO_0000064 a rdfs:Class ;
rdfs:label "sequence read count"@en ;
rdfs:comment "sequence read count is a data item determining how many sequence reads have been generated by a DNA sequencing assay for a given stretch of DNA" ;
rdfs:subClassOf obo:STATO_0000047 .
obo:STATO_0000646 a rdfs:Class ;
rdfs:label "population variance" ;
rdfs:comment """the population variance is a variance of the true population from which a sample is derived.
the population variance describes the variability of a characteristic in the population.""" ;
rdfs:subClassOf obo:STATO_0000113 .
obo:STATO_0000262 a rdfs:Class ;
rdfs:label "Bernoulli distribution"@en ;
rdfs:comment """Bernoulli distribution is a binomial distribution where the number of trials is equal to 1.
notation: B(1,p)
The mean is p
The variance is p*q"""@en ;
rdfs:subClassOf obo:STATO_0000276 .
obo:OBI_0200031 a rdfs:Class ;
rdfs:label "differential expression analysis objective"@en ;
rdfs:comment "A differential expression analysis objective is a data transformation objective whose input consists of expression levels of entities (such as transcripts or proteins), or of sets of such expression levels, under two or more conditions and whose output reflects which of these are likely to have different expression across such conditions."@en ;
rdfs:subClassOf obo:OBI_0200166 .
obo:STATO_0000156 a rdfs:Class ;
rdfs:label "Scheffe test"@en ;
rdfs:comment "the Scheffe test is a data transformation which evaluates all possible contrasts and adjusting the levels significance by accounting for multiple comparison. The test is therefore conservative. Confidence intervals can be constructed for the corresponding linear regression. It was developped by American statistician Henry Scheffe in 1959."@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000133 .
obo:STATO_0000037 a rdfs:Class ;
rdfs:label "standard error of the mean"@en ;
rdfs:comment """The standard error of the mean (SEM) is data item denoting the standard deviation of the sample-mean's estimate of a population mean.
It is calculated by dividing the sample standard deviation (i.e., the sample-based estimate of the standard deviation of the population) by the square root of n , the size (number of observations) of the sample.
A measure of dispersion applied to means across hypothetical repeated random samples."""@en ;
rdfs:seeAlso ;
rdfs:subClassOf obo:STATO_0000562 .
obo:STATO_0000389 a rdfs:Class ;
rdfs:label "power law distribution"@en ;
rdfs:comment """a power-law probability distribution is a probability distribution whose density function (or mass function in the discrete case) has the form
p(x) = L(x) . x^{-alpha}
where alpha is a parameter >1 and L(x) is a slowly varying function."""@en ;
rdfs:subClassOf obo:STATO_0000225 .
obo:OBI_0500011 a rdfs:Class ;
rdfs:label "latin square design"@en ;
rdfs:comment "Latin square design is_a study design which allows in its simpler form controlling 2 levels of nuisance variables (also known as blocking variables).he 2 nuisance factors are divided into a tabular grid with the property that each row and each column receive each treatment exactly once."@en ;
rdfs:subClassOf obo:OBI_0500000 , obo:OBI_0500007 .
obo:STATO_0000093 a rdfs:Class ;
rdfs:label "date"@en ;
rdfs:comment "Information about a calendar date or timestamp indicating day, month, year and time of an event."@en ;
rdfs:subClassOf obo:IAO_0000582 .
obo:IAO_0000581 a rdf:Property ;
rdfs:label "has time stamp"@en ;
rdfs:comment "relates a time stamped measurement datum to the time measurement datum that denotes the time when the measurement was taken"@en ;
rdfs:domain obo:IAO_0000582 ;
rdfs:range obo:IAO_0000416 ;
rdfs:subPropertyOf obo:BFO_0000051 .
obo:IAO_0000583 a rdf:Property ;
rdfs:label "has measurement datum"@en ;
rdfs:comment "relates a time stamped measurement datum to the measurement datum that was measured"@en ;
rdfs:domain obo:IAO_0000582 ;
rdfs:range ;
rdfs:subPropertyOf obo:BFO_0000051 .
obo:STATO_0000657 a rdfs:Class ;
rdfs:label "intercept" ;
rdfs:comment "an intercept is a data item which corresponds to where a graph line cuts (intercepts) an coordinates axis." ;
rdfs:subClassOf obo:IAO_0000027 .
obo:OBI_0100064 a rdfs:Class ;
rdfs:label "screening library"@en ;
rdfs:comment "a screening library is a collection of materials engineered to identify qualities of a subset of its members during a screening process?"@en ;
rdfs:subClassOf obo:OBI_0000047 .
obo:STATO_0000042 a rdfs:Class ;
rdfs:label "Anderson-Darling test"@en ;
rdfs:comment "The Anderson–Darling test is a statistical test of whether a given sample of data is drawn from a given probability distribution."@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000191 .
obo:STATO_0000121 a rdfs:Class ;
rdfs:label "association between categorical variables testing objective"@en ;
rdfs:comment "the objective of a data transformation to evaluate a null hypothesis of absence of linkage between variables."@en ;
rdfs:subClassOf obo:OBI_0000675 .
obo:OBI_0001879 a rdfs:Class ;
rdfs:label "reagent"@en ;
rdfs:comment "A biological or chemical entity that bears a reagent role in virtue of it being intended for application in a scientific technique to participate in (or have molecular parts that participate in) a chemical reaction that facilitates the generation of data about some distinct entity, or the generation of some distinct material specified output." ;
rdfs:subClassOf obo:BFO_0000040 , obo:OBI_0000047 .
obo:BFO_0000023 a rdfs:Class ;
rdfs:label "role"@en ;
rdfs:comment "A realizable entity the manifestation of which brings about some result or end that is not essential to a continuant in virtue of the kind of thing that it is but that can be served or participated in by that kind of continuant in some kinds of natural, social or institutional contexts."@en ;
rdfs:subClassOf obo:BFO_0000017 .
obo:STATO_0000716 a rdfs:Class ;
rdfs:label "non-inferiority testing" ;
rdfs:comment "a type of between group comparison where the intent is to compare two or more interventions or exposures and to determine that any difference in effects is below a prespecified value representing a threshold between a meaningful difference and absence of a meaningful difference" ;
rdfs:subClassOf obo:STATO_0000715 .
obo:STATO_0000483 a rdfs:Class ;
rdfs:label "Bayes A"@en ;
rdfs:comment "Bayes A is a data transformation used in the context of estimating breeding value, which relies on a Bayesian model and treats the prior probability π that a SNP has zero effect as unknown (i.e π=0)" ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000119 , obo:STATO_0000337 .
obo:STATO_0000530 a rdfs:Class ;
rdfs:label "Bayesian model" ;
rdfs:comment "a Bayesian model is a statistical model where inference is based on using Bayes theorem to obtain a posterior distribution for a quantity (or quantities) of interest for some model (such as parameter values) based on some prior distribution for the relevant unknown parameters and the likelihood from the model."@en ;
rdfs:subClassOf obo:STATO_0000107 .
obo:OBI_0000838 a rdfs:Class ;
rdfs:label "material maintenance" ;
rdfs:comment "a process with that achieves the objective to maintain some or all of the characteristics of an input material over time" ;
rdfs:subClassOf obo:OBI_0000011 .
obo:STATO_0000295 a rdfs:Class ;
rdfs:label "absence of positive difference hypothesis"@en ;
rdfs:comment "absence of negative difference hypothesis is a hypothesis which assumes that a difference significantly greater than a threshold does not exist."@en ;
rdfs:subClassOf obo:STATO_0000065 .
obo:STATO_0000701 a rdfs:Class ;
rdfs:label "Chi-square test for homogeneity"@en ;
rdfs:comment "a statistical test which test for homogeneity of proportions, which is used when comparing proportions observed across multiple groups. It relies on frequencies calculated in contingency tables. It determines is proportions are consistent." ;
rdfs:subClassOf obo:STATO_0000247 , obo:STATO_0000697 .
obo:STATO_0000461 a rdfs:Class ;
rdfs:label "O'brien-Flemming boundary analysis"@en ;
rdfs:comment """the O'brien-Flemming boundary analysis is a kind of interim-analysis method implemented by O'brien and Flemming to account for the
As all frequentist methods of the same type, it focuses on controlling the type I error rate as the repeated hypothesis testing of accumulating data increases the type I error rate of a clinical trial."""@en ;
rdfs:subClassOf obo:STATO_0000460 .
obo:GO_0003674 a rdfs:Class ;
rdfs:label "molecular_function" ;
rdfs:comment "A molecular process that can be carried out by the action of a single macromolecular machine, usually via direct physical interactions with other molecular entities. Function in this sense denotes an action, or activity, that a gene product (or a complex) performs. These actions are described from two distinct but related perspectives: (1) biochemical activity, and (2) role as a component in a larger system/process." ;
rdfs:subClassOf obo:BFO_0000015 .
obo:STATO_0000269 a rdfs:Class ;
rdfs:label "polychoric correlation coefficient"@en ;
rdfs:comment "polychoric correlation coefficient is a correlation coefficient which is computed over 2 variables to characterise an association by proxy with 2 (latent) variables which are assumed to be continuous and normally distributed."@en ;
rdfs:subClassOf obo:STATO_0000142 .
obo:STATO_0000683 a rdfs:Class ;
rdfs:label "simple chance-corrected agreement coefficient"@en ;
rdfs:comment "A Kappa statistic in which the expected agreement by chance is based on an assumption that all possible categories for assignment are equally likely."@en ;
rdfs:subClassOf obo:STATO_0000682 .
obo:OBI_0000471 a rdfs:Class ;
rdfs:label "study design execution" ;
rdfs:comment "a planned process that carries out a study design" ;
rdfs:subClassOf obo:OBI_0000011 .
obo:BFO_0000016 a rdfs:Class ;
rdfs:label "disposition"@en ;
rdfs:subClassOf obo:BFO_0000017 .
obo:STATO_0000311 a rdfs:Class ;
rdfs:label "central composite design"@en ;
rdfs:comment """a central composite design is a study design which contains an imbedded factorial or fractional factorial design with center points that is augmented with a group of so-called 'star points' that allow estimation of curvature.
A CCD design with k factors has 2k star points."""@en ;
rdfs:subClassOf obo:OBI_0500000 .
obo:STATO_0000187 a rdfs:Class ;
rdfs:label "Tukey HSD for Post-Hoc Analysis"@en ;
rdfs:comment """Tukey Honestly Significant Difference (HSD) test is a statistical test used following an ANOVA test yielding a statistically significant p-value in order to determine which means are different, to a given level of significance. The Tukey HSD test relies on the q-distribution.
The procedure is conservative, meaning that if sample sizes (the sizes of different study groups) are equal, the risk of a Type I error is exactly α, and if sample sizes are unequal it’s less than α."""@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000133 .
obo:GO_0008150 a rdfs:Class ;
rdfs:label "biological_process" ;
rdfs:comment "A biological process represents a specific objective that the organism is genetically programmed to achieve. Biological processes are often described by their outcome or ending state, e.g., the biological process of cell division results in the creation of two daughter cells (a divided cell) from a single parent cell. A biological process is accomplished by a particular set of molecular functions carried out by specific gene products (or macromolecular complexes), often in a highly regulated manner and in a particular temporal sequence." ;
rdfs:subClassOf obo:BFO_0000015 .
obo:OBI_0000984 a rdfs:Class ;
rdfs:label "dose" ;
rdfs:comment "A measurement datum that measures the quantity of something that may be administered to an organism or that an organism may be exposed to. Quantities of nutrients, drugs, vaccines and toxins are referred to as doses." ;
rdfs:subClassOf obo:IAO_0000109 .
obo:OBI_0000889 a rdfs:Class ;
rdfs:label "survival curve"@en ;
rdfs:comment "A survival curve is a report graph which is a graphical representation of data where the percentage of survival is plotted as a function of time."@en ;
rdfs:subClassOf obo:IAO_0000027 , obo:IAO_0000573 .
obo:STATO_0000014 a rdfs:Class ;
rdfs:label "spherical coordinate system"@en ;
rdfs:comment "In mathematics, a spherical coordinate system is a coordinate system for three-dimensional space where the position of a point is specified by three numbers: the radial distance of that point from a fixed origin, its polar angle measured from a fixed zenith direction, and the azimuth angle of its orthogonal projection on a reference plane that passes through the origin and is orthogonal to the zenith, measured from a fixed reference direction on that plane."@en ;
rdfs:subClassOf obo:STATO_0000010 .
obo:STATO_0000104 a rdfs:Class ;
rdfs:label "z-score"@en ;
rdfs:comment "A z-score (also known as z-value, standard score, or normal score) is a measure of the divergence of an individual experimental result from the most probable result, the mean. Z is expressed in terms of the number of standard deviations from the mean value."@en ;
rdfs:subClassOf obo:STATO_0000609 .
obo:STATO_0000139 a rdfs:Class ;
rdfs:label "subject pairing"@en ;
rdfs:comment "a subject pairing is a planned process which executes a pairing rule and results in the creation of sets of 2 subjects meeting the pairing criteria"@en ;
rdfs:subClassOf obo:OBI_0600015 .
obo:STATO_0000102 a rdf:Property ;
rdfs:label "executes" ;
rdfs:comment "relationship between a planned process and the plan specification that it carries out; it is defined as equivalent to the composed relationship (realizes o concretizes)"@en ;
rdfs:range .
obo:OBI_0000662 a rdfs:Class ;
rdfs:label "error corrected data set"@en ;
rdfs:comment "A data set that is produced as the output of an error correction data transformation and consists of producing a data set which has had erroneous contributions from the input to the data transformation removed (corrected for)."@en ;
rdfs:subClassOf obo:IAO_0000100 .
obo:STATO_0000454 a rdfs:Class ;
rdfs:label "multivariate analysis of variance"@en ;
rdfs:comment """\"The multivariate analysis of variance, or MANOVA, is a procedure for comparing multivariate sample means. As a multivariate procedure, it is used when there are two or more dependent variables, and is typically followed by significance tests involving individual dependent variables separately.
It helps to answer:
1. Do changes in the independent variable(s) have significant effects on the dependent variables?
2. What are the relationships among the dependent variables?
3. What are the relationships among the independent variables?\""""@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:OBI_0200201 .
obo:OBI_0001034 a rdfs:Class ;
rdfs:label "environmental control device" ;
rdfs:comment "An environmental control device is a device which has the function to control some aspect of the environment such as temperature, or humidity." ;
rdfs:subClassOf obo:OBI_0000968 .
obo:STATO_0000025 a rdfs:Class ;
rdfs:label "one dimensional cartesian spatial coordinate origin"@en ;
rdfs:comment "A cartesian spatial coordinate datum chosen as a fixed point of reference in a one dimensional spatial region."@en ;
rdfs:subClassOf obo:STATO_0000026 .
obo:STATO_0000176 a rdfs:Class ;
rdfs:label "t-statistic"@en ;
rdfs:comment "t-statistic is a statistic computed from observations and used to produce a p-value in statistical test when compared to a Student's t distribution."@en ;
rdfs:subClassOf obo:STATO_0000039 .
obo:STATO_0000154 a rdfs:Class ;
rdfs:label "violin plot" ;
rdfs:comment """a violin plot is a plot combining the features of box plot and kernel density plot. The violin plot is therefore similar to box plot but it incorporated in the display the probability density of the data at different values.
Typically violin plots will include a marker for the median of the data and a box indicating the interquartile range, as in standard box plots."""@en ;
rdfs:subClassOf obo:IAO_0000038 .
obo:STATO_0000512 a rdfs:Class ;
rdfs:label "chain-referral sampling"@en ;
rdfs:comment "Snowball sampling (or chain sampling, chain-referral sampling, referral sampling) is a non-probability sampling technique where existing study subjects recruit future subjects from among their acquaintances. Thus the sample group is said to grow like a rolling snowball."@en ;
rdfs:subClassOf obo:STATO_0000502 .
obo:STATO_0000416 a rdfs:Class ;
rdfs:label "precision"@en ;
rdfs:comment """precision or positive predictive value is defined as the proportion of the true positives against all the positive results (both true positives and false positives)
A proportion in which the numerator represents the correctly detected items within the denominator that represents all items detected."""@en ;
rdfs:subClassOf obo:STATO_0000607 .
obo:STATO_0000082 a rdfs:Class ;
rdfs:label "fixed effect model"@en ;
rdfs:comment "a fixed effect model is a statistical model which represents the observed quantities in terms of explanatory variables that are treated as if the quantities were non-random."@en ;
rdfs:subClassOf obo:STATO_0000107 .
obo:OBI_0001271 a rdfs:Class ;
rdfs:label "RNA-seq assay"@en ;
rdfs:comment "An assay in which sequencing technology (e.g. Solexa/454) is used to generate RNA sequence, analyse the transcibed regions of the genome, and or to quantitate transcript abundance"@en ;
rdfs:subClassOf obo:OBI_0000424 , obo:OBI_0001177 , obo:OBI_0600047 .
obo:STATO_0000545 a rdfs:Class ;
rdfs:label "narrow sense heritability" ;
rdfs:comment """A particularly important component of the genetic variance is the additive variance, Var(A), which is the variance due to the average effects (additive effects) of the alleles. Since each parent passes a single allele per locus to each offspring, parent-offspring resemblance depends upon the average effect of single alleles. Additive variance represents, therefore, the genetic component of variance responsible for parent-offspring resemblance. The additive genetic portion of the phenotypic variance is known as Narrow-sense heritability and is defined as:
h2 = Var(A)/Var(P)"""@en ;
rdfs:subClassOf obo:STATO_0000184 .
obo:OBI_0000131 a rdfs:Class ;
rdfs:label "molecular feature identification objective"@en ;
rdfs:comment "Molecular_feature_identification_objective is a biological_feature_identification_objective role describing a study designed to examine or characterize molecular features of a biological system, e.g. expression profiling, copy number of molecular components, epigenetic modifications."@en ;
rdfs:subClassOf obo:OBI_0000015 .
obo:STATO_0000178 a rdfs:Class ;
rdfs:label "kurtosis"@en ;
rdfs:comment "Kurtosis is a data item which denotes the degree of peakedness of a distribution. It is defined as a normalized form of the fourth central moment of a distribution."@en ;
rdfs:subClassOf obo:STATO_0000039 .
obo:OBI_0000751 a rdfs:Class ;
rdfs:label "study design dependent variable"@en ;
rdfs:comment "dependent variable specification is part of a study design. The dependent variable is the event studied and expected to change when the independent variable varies."@en ;
rdfs:subClassOf obo:IAO_0000033 , obo:STATO_0000258 .
obo:STATO_0000664 a rdfs:Class ;
rdfs:label "mean of differences" ;
rdfs:comment "A mean of values in which each value is the subtraction of one quantity from another."@en ;
rdfs:subClassOf obo:STATO_0000573 .
obo:OBI_0000427 a rdfs:Class ;
rdfs:label "enzyme"@en ;
rdfs:comment """(protein or rna) or has_part (protein or rna) and
has_function some GO:0003824 (catalytic activity)"""@en ;
rdfs:subClassOf obo:BFO_0000040 .
obo:STATO_0000059 a rdfs:Class ;
rdfs:label "Student's t distribution"@en ;
rdfs:comment "the Student's t distribution is a continuous probability distribution which arises when estimating the mean of a normally distributed population in situations where the sample size is small and population standard deviation is unknown."@en ;
rdfs:subClassOf obo:STATO_0000067 , obo:STATO_0000329 .
obo:OBI_0600014 a rdfs:Class ;
rdfs:label "material component separation"@en ;
rdfs:comment "a material processing in which components of an input material become segregated in space"@en ;
rdfs:subClassOf obo:OBI_0000094 .
obo:STATO_0000322 a rdfs:Class ;
rdfs:label "contrast weight"@en ;
rdfs:comment "a contrast weight is a coefficient which multiplies a group mean, part of a linear combinaison defining a constrast as a weighted sum of group means, giving a 'weight' to a specific group mean hence the name."@en ;
rdfs:subClassOf obo:IAO_0000027 .
obo:STATO_0000019 a rdfs:Class ;
rdfs:label "normal distribution hypothesis"@en ;
rdfs:comment "normal distribution hypothesis is a goodness of fit hypothesis stating that the distribution computed from the sample population fits a normal distribution."@en ;
rdfs:subClassOf obo:STATO_0000058 .
obo:STATO_0000255 a rdfs:Class ;
rdfs:label "between group comparison objective"@en ;
rdfs:comment "the objective of a data transformation to test a null hypothesis of absence of difference withing subject holds."@en ;
rdfs:subClassOf obo:OBI_0000675 .
obo:OBI_0001051 a rdfs:Class ;
rdfs:label "DNA extract" ;
rdfs:comment "The output of an extraction process in which DNA molecules are purified in order to exclude DNA from organellas." ;
rdfs:subClassOf obo:OBI_0001010 .
obo:STATO_0000374 a rdfs:Class ;
rdfs:label "feasible generalized least squares estimation"@en ;
rdfs:comment "the feasible generalized least squares estimation is a model parameter estimation which is a practical implementation of Generalised Least Squares, where the covariance of the errors is estimated from the residuals of the regression model, providing the information needed to whiten the data and model. Each successive estimate of the whitening matrix improves the estimation of the regression parameters, which in turn are used to compute residuals and update the whitening matrix." ;
rdfs:subClassOf obo:STATO_0000372 .
obo:STATO_0000363 a rdfs:Class ;
rdfs:label "heterogeneous compound symmetry covariance structure"@en ;
rdfs:comment "heterogenous compound symmetry structure is a compound symmetry covariance structure which has a different variance parameter for each diagonal element, and it uses the square roots of these parameters in the off-diagonal entries."@en ;
rdfs:subClassOf obo:STATO_0000362 .
obo:OBI_0000401 a rdfs:Class ;
rdfs:label "environment control function"@en ;
rdfs:comment "An environmental control function is a function that regulates a contained environment within specified parameter ranges. For example the control of light exposure, humidity and temperature."@en ;
rdfs:subClassOf obo:BFO_0000034 .
obo:STATO_0000729 a rdfs:Class ;
rdfs:label "date Time variable" ;
rdfs:comment "An interval variable for which allowable values represent a point in time on a calendar, with a year, month, and day, and on a clock, with hours, minutes, and seconds." ;
rdfs:subClassOf obo:STATO_0000727 .
obo:STATO_0000628 a rdfs:Class ;
rdfs:label "F1 score" ;
rdfs:comment """A ratio representing the harmonic mean of recall and precision.
The F1-score is used as a measure of quality for classification algorithms and information retrieval strategies, where 1 represents the best precision and recall and 0 represents the worst precision and recall.
A harmonic mean of a set of quantities is the reciprocal of the arithmetic mean of the reciprocals of each quantity. The F score is thus calculated as 1 / (the arithmetic mean of the reciprocals), or:
F = 1 / ( ( (1/recall) + (1/precision) ) / 2 )
F = 2*( (precision*recall) / (precision+recall) )
Recall is sensitivity STATO:0000233
Precision (PPV) is STATO:0000416""" ;
rdfs:subClassOf obo:STATO_0000663 .
obo:STATO_0000368 a rdfs:Class ;
rdfs:label "Mallows' Cp" ;
rdfs:comment """Mallows' Cp is a data item which compares the precision and bias of the full model to models with a subset of the predictors thus helping to choose between multiple regression models.
the mallows cp is a function of the number of parameter used in the model relying on the residuals sum of squares to compute a score.
the smaller Cp is, the better the model fit is.""" ;
rdfs:subClassOf obo:STATO_0000039 .
obo:OBI_0000370 a rdfs:Class ;
rdfs:label "contain function"@en ;
rdfs:comment "A contain function is a function to constrain a material entities location in space"@en ;
rdfs:subClassOf obo:BFO_0000034 .
obo:STATO_0000212 a rdfs:Class ;
rdfs:label "tetrachoric correlation coefficient"@en ;
rdfs:comment "a tetrachoric correlation coefficient is a polychoric correlation coefficient for 2 dichotomous variables used as proxy for correlation between 2 continuous latent variables."@en ;
rdfs:subClassOf obo:STATO_0000269 .
obo:OBI_0000419 a rdfs:Class ;
rdfs:label "reverse transcriptase"@en ;
rdfs:comment """enzyme and has_function some GO:0003964 (RNA-directed DNA polymerase
activity)"""@en ;
rdfs:subClassOf obo:OBI_0000427 .
obo:OBI_0600064 a rdfs:Class ;
rdfs:label "recombinant vector cloning"@en ;
rdfs:comment "a planned process with the objective to insert genetic material into a cloning vector for future replication of the inserted material"@en ;
rdfs:subClassOf obo:OBI_0000094 .
obo:STATO_0000223 a rdfs:Class ;
rdfs:label "group assignment based on blocking variable specification"@en ;
rdfs:comment "group assignment based on blocking variable specification is a kind of group assignment process which takes into account the levels assumed by a blocking variable to allocate subjects or experimental units to a treatment group"@en ;
rdfs:subClassOf obo:OBI_0600015 .
obo:STATO_0000392 a rdfs:Class ;
rdfs:label "Pareto type-I probability distribution"@en ;
rdfs:comment """The Pareto distribution is a continuous probability distribution, which is defined by the follwoing probability density (1) function and distribution function (2)
(1): P(x)=(ab^a)/(x^(a+1))\t
(2): D(x)=1-(b/x)^a\t
defined over the interval x>=b."""@en ;
rdfs:subClassOf obo:STATO_0000067 .
obo:STATO_0000308 a rdfs:Class ;
rdfs:label "sum contrast"@en ;
rdfs:comment "the sum contrast is a contrast in which each coefficient compares the corresponding level of the factor to the average of the other levels"@en ;
rdfs:subClassOf obo:STATO_0000290 .
obo:STATO_0000117 a rdfs:Class ;
rdfs:label "discrete probability distribution"@en ;
rdfs:comment "a discrete probability distribution is a probability distribution which is defined by a probability mass function where the random variable can only assume a finite number of values or infinitely countable values"@en ;
rdfs:subClassOf obo:STATO_0000225 .
obo:STATO_0000604 a rdfs:Class ;
rdfs:label "alpha investing procedure" ;
rdfs:comment "a type of sequential multiple testing correction method" ;
rdfs:subClassOf obo:STATO_0000602 .
obo:OBI_0000272 a rdfs:Class ;
rdfs:label "protocol"@en ;
rdfs:comment "A plan specification which has sufficient level of detail and quantitative information to communicate it between investigation agents, so that different investigation agents will reliably be able to independently reproduce the process."@en ;
rdfs:subClassOf obo:IAO_0000104 .
obo:STATO_0000189 a rdfs:Class ;
rdfs:label "mixed effect model"@en ;
rdfs:comment "A mixed model is a statistical model containing both fixed effects and random effects. These models are useful in a wide variety of disciplines in the physical, biological and social sciences. They are particularly useful in settings where repeated measurements are made on the same statistical units (longitudinal study), or where measurements are made on clusters of related statistical units. Because of their advantage in dealing with missing values, mixed effects models are often preferred over more traditional approaches such as repeated measures ANOVA."@en ;
rdfs:subClassOf obo:STATO_0000107 .
obo:UBERON_0000477 a rdfs:Class ;
rdfs:label "anatomical cluster" ;
rdfs:comment "Anatomical group that has its parts adjacent to one another." ;
rdfs:subClassOf obo:BFO_0000040 .
obo:STATO_0000266 a rdfs:Class ;
rdfs:label "Bayes factor"@en ;
rdfs:comment """Bayes factor is a ratio between 2 probabilities of observing data according 2 distinct models. It is used in Bayes model selection to evaluate which model best explains the data. if K<0, the model used in the denominator term is supported, if K>1, the model used in the numerator term is supported.
The Bayes factor is about the plausibility of 2 different models"""@en ;
rdfs:subClassOf obo:STATO_0000184 .
obo:IAO_0000030 a rdfs:Class ;
rdfs:label "information content entity"@en ;
rdfs:comment "A generically dependent continuant that is about some thing."@en ;
rdfs:subClassOf obo:BFO_0000031 .
obo:STATO_0000438 a rdfs:Class ;
rdfs:label "log normal distribution"@en ;
rdfs:comment "a log-normal (or lognormal) distribution is a continuous probability distribution of a random variable whose logarithm is normally distributed. Thus, if the random variable {\\displaystyle X} X is log-normally distributed, then {\\displaystyle Y=\\ln(X)} Y=\\ln(X) has a normal distribution. Likewise, if {\\displaystyle Y} Y has a normal distribution, then {\\displaystyle X=\\exp(Y)} X=\\exp(Y) has a log-normal distribution. A random variable which is log-normally distributed takes only positive real values. The distribution is occasionally referred to as the Galton distribution or Galton's distribution, after Francis Galton."@en ;
rdfs:subClassOf obo:STATO_0000067 .
obo:STATO_0000523 a rdfs:Class ;
rdfs:label "k-nearest neighbour data imputation" ;
rdfs:comment "k-nearest neighbour imputation is a data imputation which uses the k-nearest neighbour algorithm to compute a substitution value for the missing values. For every observation to be imputed, it identifies ‘k’ closest observations based on the euclidean distance and computes the weighted average (weighted based on distance) of these ‘k’ obs." ;
rdfs:subClassOf obo:STATO_0000518 .
obo:OBI_0200089 a rdfs:Class ;
rdfs:label "multiple testing correction method"@en ;
rdfs:comment "A multiple testing correction method is a hypothesis test performed simultaneously on M > 1 hypotheses. Multiple testing procedures produce a set of rejected hypotheses that is an estimate for the set of false null hypotheses while controlling for a suitably define Type I error rate" ;
rdfs:subClassOf obo:OBI_0000668 .
obo:STATO_0000352 a rdfs:Class ;
rdfs:label "spatial exponential geometric anisotropic covariance structure"@en ;
rdfs:comment "spatial exponential geometric anisotropic covariance structure is a type of covariance structure characterized by its anisotropy, i.e., the variation of properties can be different in directions x and y, which is this case give exponential features."@en ;
rdfs:subClassOf obo:STATO_0000346 .
obo:STATO_0000016 a rdfs:Class ;
rdfs:label "polar coordinate system"@en ;
rdfs:comment "In mathematics, the polar coordinate system is a two-dimensional coordinate system in which each point on a plane is determined by a distance from a fixed point and an angle from a fixed direction." ;
rdfs:subClassOf obo:STATO_0000010 .
obo:STATO_0000331 a rdfs:Class ;
rdfs:label "histogram distribution"@en ;
rdfs:comment "Probability distribution estimated empirically on the data following a binning process"@en ;
rdfs:subClassOf obo:STATO_0000225 .
obo:STATO_0000385 a rdfs:Class ;
rdfs:label "standard error of a contrast estimate"@en ;
rdfs:comment "an estimate of the standard deviation of a contrast estimate sampling distribution."@en ;
rdfs:subClassOf obo:STATO_0000562 .
obo:OBI_0000740 a rdfs:Class ;
rdfs:label "material sample role" ;
rdfs:comment "A material sample role is a specimen role borne by a material entity that is the output of a material sampling process." ;
rdfs:subClassOf obo:OBI_0000112 .
obo:OBI_0001912 a rdfs:Class ;
rdfs:label "cell freezing medium"@en ;
rdfs:comment "A processed material that serves as a liquid vehicle for freezing cells for long term quiescent stroage, which contains chemicls needed to sustain cell viability across freeze-thaw cycles. " ;
rdfs:subClassOf obo:OBI_0000047 .
obo:NCBITaxon_7742 a rdfs:Class ;
rdfs:label "Vertebrata " ;
rdfs:subClassOf obo:NCBITaxon_33213 .
obo:STATO_0000528 a rdfs:Class ;
rdfs:label "G matrix" ;
rdfs:comment "A matrix of relationships among a group of individuals, which can be used to predict breeding values, to manage inbreeding and in genetic conservation. It can be calculated from the pedigree, but it is also possible to calculate the relationship matrix from genotypes at genetic markers such as single-nucleotide polymorphisms (SNPs). Elements of the genomic relationship matrix are estimates of the realized proportion of the genome that two individuals share, whereas the pedigree-derived relationship matrix is the expectation of this proportion."@en ;
rdfs:subClassOf obo:STATO_0000642 .
obo:STATO_0000165 a rdfs:Class ;
rdfs:label "pie chart"@en ;
rdfs:comment "a pie chart is a graph in which a circular graph is divided into sector illustrating numerical proportion, meaning that the arc length of each sector (and consequently its central angle and area), is proportional to the quantity it represents."@en ;
rdfs:subClassOf obo:IAO_0000038 .
obo:STATO_0000560 a rdfs:Class ;
rdfs:label "Rao's score" ;
rdfs:comment "the Rao-Scott score is a statistic which is used to test the hypothesis that all coefficients associated with a particular regression term are zero (or have some other specified values). the LRT uses a linear combination of chi-squared distributions" ;
rdfs:subClassOf obo:STATO_0000039 .
obo:STATO_0000449 a rdfs:Class ;
rdfs:label "sub sub-plot number"@en ;
rdfs:comment """a 'sub sub-plot number' is a data item used to count and identify the actual piece of land located within a 'sub plot', in the case of real field based trials using a split-split-plot design, and received completely randomized treatments corresponding to the factor levels combinations of the remainder factors declared in the experiment.
in the case of 'split-split plot design', sub-plots also receive treatments corresponding to a factor whose randomization is restriction. In such configuration, each 'sub-plot' is itself divided into 'sub sub-plot', which then received the remainder of the treatments in completely randomized fashion.
In the case of non-field based trials, the notion 'sub sub-plot' is a metaphor."""@en ;
rdfs:subClassOf obo:IAO_0000027 .
obo:STATO_0000128 a rdfs:Class ;
rdfs:label "Altman box and whisker plot" ;
rdfs:comment "Altman Box and Whisker plot is a variation of Tukey Box and Whisker plot which use the criteria of Altman to create the 'whisker' of the plot."@en ;
rdfs:subClassOf obo:STATO_0000243 .
obo:STATO_0000258 a rdfs:Class ;
rdfs:label "variable"@en ;
rdfs:comment "a variable is a data item which can assume any of a set of values, either as determined by an agent or as randomly occuring through observation."@en ;
rdfs:subClassOf obo:STATO_0000741 .
obo:OBI_0002089 a rdfs:Class ;
rdfs:label "physical store"@en ;
rdfs:comment "A container with an environmental control function."@en ;
rdfs:subClassOf obo:OBI_0000967 , obo:OBI_0001034 .
obo:STATO_0000472 a rdfs:Class ;
rdfs:label "degree of freedom approximation"@en ;
rdfs:comment "An estimate of the number of degrees of freedom."@en ;
rdfs:subClassOf obo:OBI_0200000 .
obo:STATO_0000097 a rdfs:Class ;
rdfs:label "statistical test power analysis"@en ;
rdfs:comment "A stastical test power analysis is a data transformation which aims to determine the size of a statistical sample required to reach a desired significance level given a particular statistical test"@en ;
rdfs:subClassOf obo:OBI_0200000 .
obo:GO_0043234 a rdfs:Class ;
rdfs:label "protein complex" ;
rdfs:comment "A stable macromolecular complex composed (only) of two or more polypeptide subunits along with any covalently attached molecules (such as lipid anchors or oligosaccharide) or non-protein prosthetic groups (such as nucleotides or metal ions). Prosthetic group in this context refers to a tightly bound cofactor. The component polypeptide subunits may be identical." ;
rdfs:subClassOf obo:BFO_0000040 .
obo:STATO_0000653 a rdfs:Class ;
rdfs:label "Hosmer-Lemeshow goodness-of-fit test" ;
rdfs:comment """The Hosmer-Lemeshow test is a statistical test used to assess the goodness of fit of a logistic regression model. It evaluates how well the predicted probabilities from the model match the observed outcomes in the data. The test helps determine whether the logistic regression model adequately captures the relationship between the predictor variables and the binary outcome variable.
The test statistic follows a chi-square distribution with degrees of freedom equal to the number of groups minus the number of parameters estimated in the logistic regression model.""" ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000191 .
obo:STATO_0000692 a rdfs:Class ;
rdfs:label "probability distribution mean"@en ;
rdfs:comment "A probability distribution attribute that represents the expected value of a variable that has that distribution."@en ;
rdfs:subClassOf obo:STATO_0000573 .
obo:STATO_0000357 a rdfs:Class ;
rdfs:label "Toeplitz covariance structure"@en ;
rdfs:comment "The Toeplitz covariance structure has homogenous variances and heterogenous correlations between elements. The correlation between adjacent elements is homogenous across pairs of adjacent elements. The correlation between elements separated by a third is again homogenous, and so on."@en ;
rdfs:subClassOf obo:STATO_0000346 .
obo:OBI_0000673 a rdfs:Class ;
rdfs:label "statistical hypothesis test"@en ;
rdfs:comment "A statistical hypothesis test data transformation is a data transformation that has objective statistical hypothesis test."@en ;
rdfs:seeAlso ;
rdfs:subClassOf obo:OBI_0200000 .
obo:STATO_0000239 a rdfs:Class ;
rdfs:label "high throughput screening"@en ;
rdfs:comment "high throughput screening is a kind of investigation which uses a standardized assays (cell based, enzymatic or chemometric) to test the effect of substances (RNAi or small molecules) held in libraries on a very specific and measureable outcome (e.g fluorence intensity). it relies on robotic handling to ensure fast and high-throughput in assay performance, data acquisition and hit selection."@en ;
rdfs:subClassOf obo:OBI_0000066 .
obo:STATO_0000599 a rdfs:Class ;
rdfs:label "point estimate"@en ;
rdfs:comment "a point estimate is a data item which provides a particular value evaluating a population parameter"@en ;
rdfs:subClassOf obo:STATO_0000471 .
obo:IAO_0000414 a rdfs:Class ;
rdfs:label "mass measurement datum"@en ;
rdfs:comment "A scalar measurement datum that is the result of measurement of mass quality"@en ;
rdfs:subClassOf obo:IAO_0000032 .
obo:STATO_0000299 a rdfs:Class ;
rdfs:label "statistical inference"@en ;
rdfs:comment "Statistical inference is the process of deducing properties of an underlying probability distribution by analysis of data."@en ;
rdfs:subClassOf obo:OBI_0000011 , obo:OBI_0001834 .
obo:STATO_0000675 a rdfs:Class ;
rdfs:label "density"@en ;
rdfs:comment "A ratio in which the numerator represents any quantity and the denominator represents an interval of space (distance, area, or volume)."@en ;
rdfs:subClassOf obo:STATO_0000184 .
obo:STATO_0000370 a rdfs:Class ;
rdfs:label "ordinary least squares estimation"@en ;
rdfs:comment "the ordinary least squares estimation is a model parameter estimation for a linear regression model when the errors are uncorrelated and equal in variance. Is the Best Linear Unbiased Estimation (BLUE) method under these assumptions, Uniformly Minimum-Variance Unbiased Estimator (UMVUE) with addition of a Gaussian assumption."@en ;
rdfs:subClassOf obo:STATO_0000119 .
obo:IAO_0000184 a rdfs:Class ;
rdfs:label "scatter plot"@en ;
rdfs:comment "A scatterplot is a graph which uses Cartesian coordinates to display values for two variables for a set of data. The data is displayed as a collection of points, each having the value of one variable determining the position on the horizontal axis and the value of the other variable determining the position on the vertical axis."@en ;
rdfs:subClassOf obo:IAO_0000038 .
obo:STATO_0000367 a rdfs:Class ;
rdfs:label "Ante-dependence covariance structure"@en ;
rdfs:comment "Ante-dependence covariance structure is a covariance structure which specifies that the covariance between two time points is a function of the product of variances at both points (hence allowing hetrogenity of error variance across measures to affect the correlation) and the product of the correlations at the distances up to the one chosen."@en ;
rdfs:subClassOf obo:STATO_0000346 .
obo:OBI_0000435 a rdfs:Class ;
rdfs:label "genotyping assay"@en ;
rdfs:comment """an assay which generates data about a genotype from a specimen of genomic DNA. A variety of
techniques and instruments can be used to produce information about sequence variation at particular genomic positions."""@en ;
rdfs:subClassOf obo:OBI_0000443 .
obo:OBI_0000967 a rdfs:Class ;
rdfs:label "container" ;
rdfs:comment "A device that can be used to restrict the location of material entities over time" ;
rdfs:subClassOf obo:OBI_0000968 .
obo:STATO_0000358 a rdfs:Class ;
rdfs:label "Huynh-Feldt covariance structure"@en ;
rdfs:comment "a form of covariance structure used to provide analysis ground s in the context of repeated measures datasets (longitudinal, time series)"@en ;
rdfs:subClassOf obo:STATO_0000346 .
obo:STATO_0000315 a rdfs:Class ;
rdfs:label "lower confidence limit"@en ;
rdfs:comment "lower confidence limit is a data item which is a lowest value bounding a confidence interval"@en ;
rdfs:subClassOf obo:STATO_0000633 .
obo:OBI_0000338 a rdfs:Class ;
rdfs:label "drawing a conclusion based on data"@en ;
rdfs:comment "A planned process in which data gathered in an investigation is evaluated in the context of existing knowledge with the objective to generate more general conclusions or to conclude that the data does not allow one to draw general conclusion"@en ;
rdfs:subClassOf obo:OBI_0000011 .
obo:STATO_0000143 a rdfs:Class ;
rdfs:label "Bayesian model selection"@en ;
rdfs:comment "A Bayesian model selection is a data transformation which is based on Bayesian statistics to compute Bayes factor in order to evaluate which model best explains data."@en ;
rdfs:subClassOf obo:STATO_0000328 .
obo:OBI_0200049 a rdfs:Class ;
rdfs:label "Benjamini and Yekutieli false discovery rate correction method"@en ;
rdfs:comment "A data transformation in which the Benjamini and Yekutieli method is applied with the aim of correcting false discovery rate" ;
rdfs:subClassOf obo:OBI_0200163 .
obo:STATO_0000581 a rdfs:Class ;
rdfs:label "singular value decomposition" ;
rdfs:comment """a data transformation which compute the singular-value decomposition of a rectangular matrix.
The singular-value decomposition is very general in the sense that it can be applied to any m × n matrix whereas eigenvalue decomposition can only be applied to certain classes of square matrices.""" ;
rdfs:subClassOf obo:OBI_0200000 .
obo:BFO_0000001 a rdfs:Class ;
rdfs:label "entity"@en .
obo:STATO_0000182 a rdfs:Class ;
rdfs:label "odds ratio" ;
rdfs:comment """Odds ratio is a ratio that measures effect size, that is the strength of association between 2 dichotomous variables, one describing an exposure and one describing an outcome.
It represents the odds that an outcome will occur given a particular exposure, compared to the odds of the outcome occurring in the absence of that exposure ( the probability of the event occuring divided by the probability of an event not occurring). The odds ratio is a ratio of describing the strength of association or non-independence between two binary data values by forming the ratio of the odds for the first group and the odds for the second group. Odds ratio are used when one wants to compare the odds of something occurring to two different groups.""" ;
rdfs:subClassOf obo:STATO_0000085 , obo:STATO_0000300 , obo:STATO_0000622 .
obo:GO_0003824 a rdfs:Class ;
rdfs:label "catalytic activity" ;
rdfs:comment "Catalysis of a biochemical reaction at physiological temperatures. In biologically catalyzed reactions, the reactants are known as substrates, and the catalysts are naturally occurring macromolecular substances known as enzymes. Enzymes possess specific binding sites for substrates, and are usually composed wholly or largely of protein, but RNA that has catalytic activity (ribozyme) is often also regarded as enzymatic." ;
rdfs:subClassOf obo:GO_0003674 .
obo:STATO_0000213 a rdfs:Class ;
rdfs:label "continuous variable discretization"@en ;
rdfs:comment "discretization as a processing converting a continuous variable into a polychotomous variable by concretizing a set of discretization rules"@en ;
rdfs:subClassOf obo:OBI_0200000 .
obo:STATO_0000598 a rdfs:Class ;
rdfs:label "number of false negative"@en ;
rdfs:comment "the number of false negative is a count which denotes how many elements known to be having a feature are wrongly classified as being devoided of it (e.g. being given an all clear while being actually infected and carrier of a pathogen)" ;
rdfs:subClassOf obo:STATO_0000047 .
obo:STATO_0000108 a rdfs:Class ;
rdfs:label "linear regression for analysis of continuous dependent variable"@en ;
rdfs:comment """linear regression model is a model which attempts to explain data distribution associated with response/dependent variable in terms of values assumed by the independent variable uses a linear function or linear combination of the regression parameters and the predictor/independent variable(s).
linear regression modeling makes a number of assumptions, which includes homoskedasticity (constance of variance)"""@en ;
rdfs:subClassOf obo:OBI_0200102 .
obo:BFO_0000026 a rdfs:Class ;
rdfs:label "one-dimensional spatial region"@en ;
rdfs:subClassOf obo:BFO_0000006 .
obo:STATO_0000556 a rdfs:Class ;
rdfs:label "number of orthogonal components" ;
rdfs:comment "number of orthogonal components is a count used as input to the orthogonal partial least square discriminant analysis (OPLS-DA)" ;
rdfs:subClassOf obo:STATO_0000047 .
obo:NCBITaxon_9606 a rdfs:Class ;
rdfs:label "Homo sapiens" ;
rdfs:subClassOf obo:NCBITaxon_314146 .
obo:OBI_0000846 a rdf:Property ;
rdfs:label "is member of organization"@en ;
rdfs:comment "Relating a legal person or organization to an organization in the case where the legal person or organization has a role as member of the organization." ;
rdfs:range obo:OBI_0000245 ;
rdfs:subPropertyOf obo:STATO_0000114 .
obo:STATO_0000427 a rdfs:Class ;
rdfs:label "restricted maximum likelihood estimation"@en ;
rdfs:comment "restricted maximum likelihood estimation is a kind of maximum likelihood estimation data transformation which estimates the variance components of random-effects in univariate and multivariate meta-analysis. in contrast to 'maximum likelihood estimation', reml can produce unbiased estimates of variance and covariance parameters."@en ;
rdfs:subClassOf obo:STATO_0000428 .
obo:IAO_0000584 a rdfs:Class ;
rdfs:label "time sampled measurement data set"@en ;
rdfs:comment "A data set that is an aggregate of data recording some measurement at a number of time points. The time series data set is an ordered list of pairs of time measurement data and the corresponding measurement data acquired at that time."@en ;
rdfs:subClassOf obo:IAO_0000100 .
obo:OBI_0600038 a rdfs:Class ;
rdfs:label "addition of molecular label"@en ;
rdfs:comment "a material processing technique intended to add a molecular label to some input material entity, to allow detection of the molecular target of this label in a detection of molecular label assay"@en ;
rdfs:subClassOf obo:OBI_0000094 .
obo:STATO_0000055 a rdfs:Class ;
rdfs:label "chromosome coordinate system"@en ;
rdfs:comment "chromosome coordinate system is a genomic coordinate which uses chromosome of a particular assembly build process to define start and end positions. This coordinate system is unstable and will change with each new genome sequence assembly build."@en ;
rdfs:subClassOf obo:STATO_0000197 .
obo:OBI_0002444 a rdfs:Class ;
rdfs:label "measurand role"@en ;
rdfs:comment "A role borne by a material entity and realized in an assay which achieves the objective to measure the magnitude/concentration/amount of the measurand in the entity bearing evaluant role." ;
rdfs:subClassOf obo:BFO_0000023 .
obo:STATO_0000539 a rdfs:Class ;
rdfs:label "discrete multivariate probability distribution" ;
rdfs:comment "a discrete multivariate probability distribution is a discrete probability distribution which describes the possible values, and corresponding probabilities, of two or more (usually three or more) associated random variables." ;
rdfs:subClassOf obo:STATO_0000117 .
obo:STATO_0000288 a rdfs:Class ;
rdfs:label "absence of difference hypothesis"@en ;
rdfs:comment "A null hypothesis which states that no difference exists between 2 or more groups being considered."@en ;
rdfs:subClassOf obo:STATO_0000065 .
obo:STATO_0000015 a rdfs:Class ;
rdfs:label "cylindrical coordinate system"@en ;
rdfs:comment "A cylindrical coordinate system is a three-dimensional coordinate system that specifies point positions by the distance from a chosen reference axis, the direction from the axis relative to a chosen reference direction, and the distance from a chosen reference plane perpendicular to the axis. The latter distance is given as a positive or negative number depending on which side of the reference plane faces the point."@en ;
rdfs:subClassOf obo:STATO_0000010 .
obo:OBI_0000399 a rdfs:Class ;
rdfs:label "solid support function"@en ;
rdfs:comment "A solid support function is a function of a device on which an entity is kept in a defined position and prevented in its movement"@en ;
rdfs:subClassOf obo:BFO_0000034 .
obo:STATO_0000623 a rdfs:Class ;
rdfs:label "measure of agreement" ;
rdfs:comment "A measure of association of two variables representing measurements of the same attribute of an entity." ;
rdfs:subClassOf obo:STATO_0000610 .
obo:STATO_0000457 a rdfs:Class ;
rdfs:label "mean difference"@en ;
rdfs:comment """The mean difference, or difference in means, measures the absolute difference between the mean value in two different groups.
The mean difference is a subtraction of one mean from another.
The primary use of this term is in analyzing between-group differences"""@en ;
rdfs:subClassOf obo:STATO_0000614 .
obo:STATO_0000379 a rdfs:Class ;
rdfs:label "focused information criterion"@en ;
rdfs:comment "The focused information criterion is a measurement data item which aims at facilitating model selection. It was published in 2003 by Claeskens, G. and Hjort, N.L. (2003). \"The focused information criterion\"."@en ;
rdfs:subClassOf obo:IAO_0000109 .
obo:STATO_0000268 a rdfs:Class ;
rdfs:label "Gamma distribution"@en ;
rdfs:comment "A gamma distribution is a general type of continous statistical distribution (related to the beta distribution) that arises naturally in processes for which the waiting times between Poisson distributed events are relevant. Gamma distributions have two free parameters shape k and scale denoted theta ."@en ;
rdfs:subClassOf obo:STATO_0000067 .
obo:STATO_0000672 a rdfs:Class ;
rdfs:label "event rate"@en ;
rdfs:comment "The number of occurrences per unit of time."@en ;
rdfs:subClassOf obo:STATO_0000645 .
obo:OBI_0000845 a rdfs:Class ;
rdfs:label "primary structure of RNA molecule" ;
rdfs:comment "The primary structure of an RNA molecule that is completely defined by the set of its nucleic residue parts and the linear order induced by the peptide bonds that hold them together" ;
rdfs:subClassOf obo:SO_0000001 .
obo:STATO_0000207 a rdfs:Class ;
rdfs:label "specifying null and alternate hypothesis"@en ;
rdfs:comment "a planned process which etablishes and states the different hypothesis to be evaluated during a null hypothesis statistical test"@en ;
rdfs:subClassOf obo:OBI_0000011 .
obo:STATO_0000544 a rdfs:Class ;
rdfs:label "heritability" ;
rdfs:comment """In a planned experiment where to covariance (genotype x environment) can be controlled and held at 0, the heritability is defined as the ratio of the variance of the genotypic variables to the variance of the phenotypic variables.
H2 = Var(G)/Var(P)
H2 is the broad-sense heritability. This reflects all the genetic contributions to a population's phenotypic variance including additive, dominant, and epistatic (multi-genic interactions), as well as maternal and paternal effects, where individuals are directly affected by their parents' phenotype, for example, milk production in mammals.""" ;
rdfs:subClassOf obo:STATO_0000184 .
obo:STATO_0000326 a rdfs:Class ;
rdfs:label "corrected Akaike information criterion"@en ;
rdfs:comment "corrected Akaike information criteria is a modified version of the Akaike information criterion."@en ;
rdfs:subClassOf obo:STATO_0000325 .
obo:STATO_0000661 a rdfs:Class ;
rdfs:label "p-value for one-sided test"@en ;
rdfs:comment "A p-value which represents the probability of obtaining a result at least as far, in one direction, from the value actually obtained as the value expected, assuming the null hypothesis is true."@en ;
rdfs:subClassOf obo:OBI_0000071 .
obo:OBI_0000374 a rdfs:Class ;
rdfs:label "excitation function"@en ;
rdfs:comment "A excitation function is a function to inject energy by bombarding a material with energetic particles (e.g., photons) thereby imbuing internal material components such as electrons with additional energy. These internal, 'excited' particles may lead to the rupturing of covalent chemical bonds or may quickly relax back to there unexcited state with an exponential time course thereby locally emitting energy in the form of photons."@en ;
rdfs:subClassOf obo:BFO_0000034 .
obo:STATO_0000707 a rdfs:Class ;
rdfs:label "frequentist inference" ;
rdfs:comment "A statistical inference paradigm in which the assumptions are that probabilities reflect relative frequencies of events and that the probability of observing data are governed by fixed yet unknown population parameters." ;
rdfs:subClassOf obo:STATO_0000299 .
obo:STATO_0000396 a rdfs:Class ;
rdfs:label "geometric mean"@en ;
rdfs:comment "The geometric mean is defined as the nth root of the product of n numbers, i.e., for a set of numbers \\{x_i\\}_{i=1}^N, the geometric mean is defined as \\left(\\prod_{i=1}^N x_i\\right)^{1/N}."@en ;
rdfs:subClassOf obo:STATO_0000029 .
obo:STATO_0000277 a rdfs:Class ;
rdfs:label "hit selection"@en ;
rdfs:comment "hit selection is a planned process which in screening processes such as high-throughput screening, lead to the identification of perturbing agent which cause the typical signal generated by a standardized assay to significantly differ from the negative control. The selection hitself results from meeting or exceeding selection threshold (for instance 6 sigma from the mean or SSMD value beyond 5 when compared to positive controls or below -5 when compared to negative controls"@en ;
rdfs:subClassOf obo:OBI_0000011 .
obo:STATO_0000612 a rdfs:Class ;
rdfs:label "Goodman and Kruskal's gamma" ;
rdfs:comment "A measure of correlation, ranging from -1 to 1, that measures the strength and direction of the relationship between ranks by value of two ordinal or continuous variables, and is calculated based on the difference in the number of concordant and discordant pairs of rankings divided by the total number of pairs of rankings, where ties are not counted among the pairs of rankings." ;
rdfs:subClassOf obo:STATO_0000142 .
obo:STATO_0000066 a rdfs:Class ;
rdfs:label "Cleveland dot plot" ;
rdfs:comment "Cleveland dot plot is a dot plot which plots points that each belong to one of several categories. They are an alternative to bar charts or pie charts, and look somewhat like a horizontal bar chart where the bars are replaced by a dots at the values associated with each category. Compared to (vertical) bar charts and pie charts, Cleveland argues that dot plots allow more accurate interpretation of the graph by readers by making the labels easier to read, reducing non-data ink (or graph clutter) and supporting table look-up.which"@en ;
rdfs:subClassOf obo:IAO_0000037 .
obo:STATO_0000132 a rdfs:Class ;
rdfs:label "Hotelling T2 distribution"@en ;
rdfs:comment """Hotelling T squared distribution is a probability distribution used in multivariate hypothesis testing, which is a univariate distribution proportional to the F-distribution and arises importantly as the distribution of a set of statistics which are natural generalizations of the statistics underlying Student's t-distribution.
In particular, the distribution arises in multivariate statistics in undertaking tests of the differences between the (multivariate) means of different populations, where tests for univariate problems would make use of a t-test.
The distribution is named for Harold Hotelling, who developed it[1] as a generalization of Student's t-distribution.
This distribution is commonly used to describe the sample Mahalanobis distance between two populations."""@en ;
rdfs:subClassOf obo:STATO_0000225 .
obo:STATO_0000468 a rdfs:Class ;
rdfs:label "model fixed effect term"@en ;
rdfs:comment "a model fixed effect term is a model term which accounts for variation explained by an independent variable and its levels." ;
rdfs:subClassOf obo:STATO_0000466 .
obo:OBI_0000424 a rdfs:Class ;
rdfs:label "transcription profiling assay"@en ;
rdfs:comment "An assay which aims to provide information about gene expression and transcription activity using ribonucleic acids collected from a material entity using a range of techniques and instrument such as DNA sequencers, DNA microarrays, Northern Blot"@en ;
rdfs:subClassOf obo:OBI_0000070 , obo:OBI_0000443 .
obo:STATO_0000567 a rdfs:Class ;
rdfs:label "factor analysis"@en ;
rdfs:comment "Factor analysis is a dimension reduction data transformation that is used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved variables called factors. Factor analysis is related to principal component analysis (PCA), but the two are not identical. Both PCA and factor analysis aim to reduce the dimensionality of a set of data, but the approaches taken to do so are different for the two techniques. Factor analysis is clearly designed with the objective to identify certain unobservable factors from the observed variables, whereas PCA does not directly address this objective; at best, PCA provides an approximation to the required factors."@en ;
rdfs:subClassOf obo:OBI_0200050 .
obo:IAO_0000007 a rdfs:Class ;
rdfs:label "action specification"@en ;
rdfs:comment "a directive information entity that describes an action the bearer will take"@en ;
rdfs:subClassOf obo:IAO_0000033 .
obo:STATO_0000686 a rdfs:Class ;
rdfs:label "mean calibration"@en ;
rdfs:comment "A measure of calibration that is the average of a function of the difference between the expected values and the observed values."@en ;
rdfs:subClassOf obo:STATO_0000685 .
obo:STATO_0000405 a rdfs:Class ;
rdfs:label "unstructured covariance structure"@en ;
rdfs:comment "A covariance structure where no restrictions are made on the covariance between any pair of measurements."@en ;
rdfs:subClassOf obo:STATO_0000346 .
obo:STATO_0000500 a rdfs:Class ;
rdfs:label "probability distribution location parameter"@en ;
rdfs:comment "a probability distribution location parameter is a data item which is set by the operator when selecting a parametric probability distribution and which dictates the way the location but not the profile or size of the distribution plot looks like."@en ;
rdfs:subClassOf obo:IAO_0000027 , obo:STATO_0000742 .
obo:OBI_0000744 a rdfs:Class ;
rdfs:label "material sampling process" ;
rdfs:comment "A specimen gathering process with the objective to obtain a specimen that is representative of the input material entity" ;
rdfs:subClassOf obo:OBI_0000659 .
obo:STATO_0000605 a rdfs:Class ;
rdfs:label "alpha spending procedure" ;
rdfs:comment "a type of sequential multiple testing correction" ;
rdfs:subClassOf obo:STATO_0000602 .
obo:STATO_0000650 a rdfs:Class ;
rdfs:label "sampling distribution variance" ;
rdfs:comment """sampling variance refers to the variability in the estimates of a population parameter that arises from random sampling.
sampling variance is a variance of the sampling distribution of a random variable and estimates the dispersion of sample estimates about their expected value in hypothetical repetitions of the sample.""" ;
rdfs:subClassOf obo:STATO_0000113 , obo:STATO_0000471 .
obo:STATO_0000369 a rdfs:Class ;
rdfs:label "repeated measure analysis"@en ;
rdfs:comment "repeated measure analysis is a kind of data transformation which deals with signals measured in the same experimental units at different times and, possibly, under different conditions over a period of time. Data produced by longitudinal studies qualify for such analysis. Since measurements are made on the same experimental units a number of times, they are likely to be correlated. Repeated measure analysis usually takes into consideration the possibility of correlation with time. It does so by specifying covariance structure in the analysis"@en ;
rdfs:subClassOf obo:OBI_0200000 .
obo:STATO_0000629 a rdfs:Class ;
rdfs:label "Scott's pi" ;
rdfs:comment """A Kappa statistic where the expected agreement between two raters is expressed in terms of the square of arithmetic means of marginal proportions of each assessment category.
Scott's pi is a kappa statistic for two raters that assumes the likelihood of each category for assignment is based on the same distribution of rater responses, leading to the use of squared arithmetic means of the marginal proportion of each assessment category as its estimate of \"chance agreement.\"
Pr(expected) is calculated using squared \"joint proportions\" which are squared arithmetic means of the marginal proportions of each assessment category, in contrast to Cohen's Kappa which uses squared geometric means.
Scott's pi = ( p[a] - p[e] ) / ( 1 - p[e] ) where p[a] is the observed percent agreement and p[e] is the expected chance agreement expressed as the squared joint proportions of the marginal sums.""" ;
rdfs:subClassOf obo:STATO_0000682 .
obo:STATO_0000356 a rdfs:Class ;
rdfs:label "banded Toeplitz covariance structure"@en ;
rdfs:comment "A banded Toeplitz structure, defined by parameter q, can be viewed as a moving-average structure with order q-1."@en ;
rdfs:subClassOf obo:STATO_0000346 .
obo:STATO_0000304 a rdfs:Class ;
rdfs:label "two sample t-test with unequal variance"@en ;
rdfs:comment "Welch t-test is a two sample t-test used when the variances of the 2 populations/samples are thought to be unequal (homoskedasticity hypothesis not verified). In this version of the two-sample t-test, the denominator used to form the t-statistics, does not rely on a 'pooled variance' estimate."@en ;
rdfs:subClassOf obo:OBI_0000739 , obo:OBI_0200000 , obo:STATO_0000279 .
obo:STATO_0000618 a rdfs:Class ;
rdfs:label "Cohen's d"@en ;
rdfs:comment """A standardized mean difference which is calculated as a difference between two means, divided by a square root of an average of the variances of the two groups.
In Cohen's d statistic, the statistical measure of dispersion is specified as the square root of an average of the variances of the two groups being compared. The variances of the two groups are based on within-group standard deviations.
For sample sizes < 50, a correction factor is used."""@en ;
rdfs:subClassOf obo:STATO_0000100 .
obo:STATO_0000257 a rdfs:Class ;
rdfs:label "family"@en ;
rdfs:comment "A domestic group, or a number of domestic groups linked through descent (demonstrated or stipulated) from a common ancestor, marriage, or adoption."@en ;
rdfs:subClassOf obo:OBI_0000181 .
obo:OBI_0001479 a rdfs:Class ;
rdfs:label "specimen from organism"@en ;
rdfs:comment "A specimen that derives from an anatomical part or substance arising from an organism. Examples of tissue specimen include tissue, organ, physiological system, blood, or body location (arm)." ;
rdfs:subClassOf obo:OBI_0100051 .
obo:STATO_0000600 a rdfs:Class ;
rdfs:label "interval estimate"@en ;
rdfs:comment "an interval estimate is a data item corresponding to a range of values likely to contain the population parameter of interest"@en ;
rdfs:subClassOf obo:STATO_0000471 .
obo:BFO_0000004 a rdfs:Class ;
rdfs:label "independent continuant"@en ;
rdfs:comment "A continuant that is a bearer of quality and realizable entity entities, in which other entities inhere and which itself cannot inhere in anything."@en ;
rdfs:subClassOf obo:BFO_0000002 .
obo:STATO_0000393 a rdfs:Class ;
rdfs:label "Pareto type-II probability distribution"@en ;
rdfs:comment """the Pareto type-II probability distribution is a continuous probability distribution which is defined by a probability density function characterized by 2 parameters, alpha and lambda, 2 real, strictly positive numbers. alpha is known as the shape parameter while lambda is known as the scale parameter.
the function defines the probably of a continous random variable according to the following:
p(x) = {\\alpha \\over \\lambda} \\left[{1+ {x \\over \\lambda}}\\right]^{-(\\alpha+1)}, \\qquad x \\geq 0,"""@en ;
rdfs:subClassOf obo:STATO_0000067 .
obo:IAO_0000573 a rdfs:Class ;
rdfs:label "line graph"@en ;
rdfs:comment """A line graph is a type of graph created by connecting a series of data
points together with a line."""@en ;
rdfs:subClassOf obo:IAO_0000038 .
obo:OBI_0001909 a rdfs:Class ;
rdfs:label "conclusion based on data" ;
rdfs:comment "An information content entity that is inferred from data." ;
rdfs:subClassOf obo:IAO_0000030 .
obo:STATO_0000224 a rdfs:Class ;
rdfs:label "goodness of fit testing objective"@en ;
rdfs:comment "A testing objective to ensure that the sample used in a statistical test actually follows a normal distribution." ;
rdfs:subClassOf obo:OBI_0000675 .
obo:OBI_0000423 a rdfs:Class ;
rdfs:label "extract"@en ;
rdfs:comment "an extract is a material entity which results from an extraction process"@en ;
rdfs:subClassOf obo:OBI_0000047 .
obo:STATO_0000090 a rdfs:Class ;
rdfs:label "dichotomous variable"@en ;
rdfs:comment "a dichotomous variable is a categorical variable which is defined to have only 2 categories or possible values"@en ;
rdfs:subClassOf obo:STATO_0000087 .
obo:OBI_0001442 a rdfs:Class ;
rdfs:label "q-value"@en ;
rdfs:comment """A quantitative confidence value that measures the minimum false discovery rate that is incurred when calling that test significant.
To compute q-values, it is necessary to know the p-value produced by a test and possibly set a false discovery rate level."""@en ;
rdfs:subClassOf obo:OBI_0000071 , obo:OBI_0000662 .
obo:OBI_0000736 a rdfs:Class ;
rdfs:label "single fragment library" ;
rdfs:comment "is a collection of short tags from DNA fragments, are extracted and covalently linked as single tag constructs" ;
rdfs:subClassOf obo:OBI_0000047 .
obo:STATO_0000699 a rdfs:Class ;
rdfs:label "t-score" ;
rdfs:comment """A t-score generally refers to the value resulting from standardizing a sample statistic (e.g., sample mean) in terms of the t-distribution. It quantifies how far the sample statistic is from the hypothesized population parameter in units of the estimated standard error.
A t-score is a statistic that represents a measure of the divergence of an individual experimental result from a specified mean, taking sample size into account and expressed in terms of the number of standard errors from the mean value.""" ;
rdfs:subClassOf obo:STATO_0000039 .
obo:BFO_0000015 a rdfs:Class ;
rdfs:label "process"@en ;
rdfs:comment "An occurrent that has temporal proper parts and for some time t, p s-depends_on some material entity at t."@en ;
rdfs:subClassOf obo:BFO_0000003 .
obo:STATO_0000533 a rdfs:Class ;
rdfs:label "Bayes C pi" ;
rdfs:comment """Bayes C pi is a data transformation used to compute estimated breeding values using a Bayesian model and which assesses the SNP effect using MonteCarlo Markov chain methods. Bayes C pi treats the prior probability π that a SNP has zero effect as unknown.
The method was devised to address short comings of Bayes A and Bayes B approaches""" ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000119 , obo:STATO_0000337 .
obo:STATO_0000036 a rdfs:Class ;
rdfs:label "outlier"@en ;
rdfs:comment "Outliers are deviant scores that have been legitimately gathered and are not due to equipment failures."@en ;
rdfs:subClassOf obo:IAO_0000027 .
obo:OBI_0400147 a rdfs:Class ;
rdfs:label "microarray"@en ;
rdfs:comment "A processed material that is made to be used in an analyte assay. It consists of a physical immobilisation matrix in which substances that bind the analyte are placed in regular spatial position."@en ;
rdfs:subClassOf obo:OBI_0001865 .
obo:STATO_0000617 a rdfs:Class ;
rdfs:label "median difference"@en ;
rdfs:comment "A difference that is a subtraction of one median from another."@en ;
rdfs:subClassOf obo:STATO_0000614 .
obo:NCBITaxon_33154 a rdfs:Class ;
rdfs:label "Opisthokonta" ;
rdfs:subClassOf obo:NCBITaxon_2759 .
obo:STATO_0000517 a rdfs:Class ;
rdfs:label "complete randomization" ;
rdfs:comment "complete randomization is a group randomization where experimental units are randomly assigned to the entire set of groups defined by the experimental treatments." ;
rdfs:subClassOf obo:OBI_0302900 .
obo:STATO_0000493 a rdfs:Class ;
rdfs:label "genotype matrix" ;
rdfs:comment "a genotype matrix is a kind of genomic relationship matrix in the rawest of form and which simply corresponds to a matrix of individuals genotype for a given set of markers or genomic positions. Columns are snps or markers, Rows are individuals. Each column/row cell contains a genotype expressed as, in the genome is diploid, as a pair of characters chosen from ATGC where the dominant variant is uppercased and the recessive variant is lower cased." ;
rdfs:subClassOf obo:STATO_0000642 .
obo:STATO_0000026 a rdfs:Class ;
rdfs:label "cartesian spatial coordinate origin"@en ;
rdfs:comment "A cartesian spatial coordinate datum chosen as a fixed point of reference in a spatial region."@en ;
rdfs:subClassOf obo:IAO_0000400 .
obo:STATO_0000679 a rdfs:Class ;
rdfs:label "diagnostic odd ratio"@en ;
rdfs:comment "A measure of association that is the ratio of the odds of a positive test in those with disease relative to the odds of a positive test in those without disease."@en ;
rdfs:subClassOf obo:STATO_0000184 .
obo:BFO_0000009 a rdfs:Class ;
rdfs:label "two-dimensional spatial region"@en ;
rdfs:subClassOf obo:BFO_0000006 .
obo:OBI_0000118 a rdfs:Class ;
rdfs:label "gene list"@en ;
rdfs:comment "A data set of the names or identifiers of genes that are the outcome of an analysis or have been put together for the purpose of an analysis."@en ;
rdfs:subClassOf obo:IAO_0000100 .
obo:STATO_0000741 a rdfs:Class ;
rdfs:label "statistical model component" ;
rdfs:subClassOf obo:IAO_0000027 .
obo:OBI_0000079 a rdfs:Class ;
rdfs:label "culture medium"@en ;
rdfs:comment "a processed material that provides the needed nourishment for microorganisms or cells grown in vitro." ;
rdfs:subClassOf obo:OBI_0000047 .
obo:OBI_0000722 a rdfs:Class ;
rdfs:label "paired-end library" ;
rdfs:comment "is a collection of short paired tags from the two ends of DNA fragments are extracted and covalently linked as ditag constructs" ;
rdfs:subClassOf obo:OBI_0000047 .
obo:STATO_0000319 a rdfs:Class ;
rdfs:label "Hedges's g"@en ;
rdfs:comment "Hedges's g is an estimator of effect size, which is similar to Cohen's d and is a measure based on a standardized difference. However, the denominator, corresponding to a pooled standard deviation, is computed differently from Cohen's d coefficient, by applying a correction factor (which involves a Gamma function)."@en ;
rdfs:subClassOf obo:STATO_0000100 .
obo:STATO_0000505 a rdfs:Class ;
rdfs:label "quadrat sampling"@en ;
rdfs:comment "Quadrat sampling is a classic tool for the study of ecology, especially biodiversity. In general, a series of squares (quadrats) of a set size are placed in a habitat of interest and the species within those quadrats are identified and recorded. Passive quadrat sampling (done without removing the organisms found within the quadrat) can be either done by hand, with researchers carefully sorting through each individual quadrat or, more efficiently, can be done by taking a photograph of the quadrat for future analysis."@en ;
rdfs:subClassOf obo:STATO_0000509 .
obo:STATO_0000049 a rdfs:Class ;
rdfs:label "Hardy-Weinberg equilibrium hypothesis" ;
rdfs:comment "Hardy-Weinberg equilibrium hypothesis is a good of fit hypothesis which states that allele and genotype frequencies in a population will remain constant from generation to generation in the absence of other evolutionary influences (non-random mating, mutation, selection, genetic drift, gene flow and meiotic drive)."@en ;
rdfs:subClassOf obo:STATO_0000058 .
obo:STATO_0000020 a rdfs:Class ;
rdfs:label "two dimensional cartesian spatial coordinate origin"@en ;
rdfs:comment "A cartesian spatial coordinate datum chosen as a fixed point of reference in a two dimensional spatial region."@en ;
rdfs:subClassOf obo:STATO_0000026 .
obo:OBI_0000367 a rdfs:Class ;
rdfs:label "light emission function"@en ;
rdfs:comment "A light emission function is an excitation function to excite a material to a specific excitation state that it emits light."@en ;
rdfs:subClassOf obo:OBI_0000374 .
obo:OBI_0200177 a rdfs:Class ;
rdfs:label "center calculation objective"@en ;
rdfs:comment "A center calculation objective is a data transformation objective where the aim is to calculate the center of an input data set."@en ;
rdfs:subClassOf obo:OBI_0200166 .
obo:STATO_0000552 a rdfs:Class ;
rdfs:label "Hommel false discovery rate correction" ;
rdfs:comment "A data transformation process in which the Hommel p-value procedure is applied with the aim of correcting false discovery rate" ;
rdfs:subClassOf obo:OBI_0200163 .
obo:OBI_0200166 a rdfs:Class ;
rdfs:label "data transformation objective"@en ;
rdfs:comment "An objective specification to transformation input data into output data"@en ;
rdfs:subClassOf obo:IAO_0000005 .
obo:STATO_0000475 a rdfs:Class ;
rdfs:label "between-within denominator degrees of freedom approximation"@en ;
rdfs:comment "a data transformation to determine the number of degree of freedom"@en ;
rdfs:subClassOf obo:STATO_0000472 .
obo:STATO_0000742 a rdfs:Class ;
rdfs:label "probability distribution parameter" ;
rdfs:comment "A member of a set of quantities that unambiguously defines a probability distribution function." ;
rdfs:subClassOf obo:IAO_0000027 .
obo:STATO_0000044 a rdfs:Class ;
rdfs:label "one-way ANOVA"@en ;
rdfs:comment "one-way anova is an analysis of variance where the different groups being compared are associated with the factor levels of only one independent variable. The null hypothesis is an absence of difference between the means calculated for each of the groups. The test assumes normality and equivariance of the data."@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:OBI_0200201 .
obo:OBI_0000848 a rdfs:Class ;
rdfs:label "polyA RNA extraction" ;
rdfs:comment "A RNA extraction process typically involving the use of poly dT oligomers in which the desired output material is polyA RNA." ;
rdfs:subClassOf obo:OBI_0666666 .
obo:STATO_0000171 a rdfs:Class ;
rdfs:label "Spear box and whisker plot" ;
rdfs:comment "Spear Box and Whisker plot is a variation of Tukey Box and Whisker plot which use the criteria of Spear to create the 'whisker' of the plot."@en ;
rdfs:subClassOf obo:STATO_0000243 .
obo:STATO_0000570 a rdfs:Class ;
rdfs:label "selectivity ratio" ;
rdfs:comment """The selectivity ratio (SR) is defined as the ratio of explained vexpl,i to residual variance vres,i for
the variable i on the target projection (TP) component in the context of Partial Least Squares Analysis.""" ;
rdfs:subClassOf obo:STATO_0000184 .
obo:STATO_0000731 a rdfs:Class ;
rdfs:label "time-to-event variable" ;
rdfs:comment "A ratio variable representing the duration of observation until the event occurred, conditioned on the event occurring." ;
rdfs:subClassOf obo:STATO_0000730 .
obo:STATO_0000284 a rdfs:Class ;
rdfs:label "Breusch-Pagan test"@en ;
rdfs:comment "Breusch-Pagan test is a statistical test which computes a score test of the hypothesis of constant error variance against the alternative that the error variance changes with the level of the response (fitted values), or with a linear combination of predictors."@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000137 .
obo:BFO_0000028 a rdfs:Class ;
rdfs:label "three-dimensional spatial region"@en ;
rdfs:subClassOf obo:BFO_0000006 .
obo:OBI_0001930 a rdfs:Class ;
rdfs:label "categorical value specification" ;
rdfs:comment "A value specification that is specifies one category out of a fixed number of nominal categories" ;
rdfs:subClassOf obo:OBI_0001933 .
obo:CHEBI_23367 a rdfs:Class ;
rdfs:label "molecular entity" ;
rdfs:comment "Any constitutionally or isotopically distinct atom, molecule, ion, ion pair, radical, radical ion, complex, conformer etc., identifiable as a separately distinguishable entity." ;
rdfs:subClassOf obo:BFO_0000040 .
obo:STATO_0000595 a rdfs:Class ;
rdfs:label "number of true positive"@en ;
rdfs:comment "the number of true positive is a count which denotes how many elements are correctly classified as having a feature they are actually known to be having (e.g. carrier of a pathogen)." ;
rdfs:subClassOf obo:STATO_0000047 .
obo:STATO_0000244 a rdfs:Class ;
rdfs:label "ΔRn"@en ;
rdfs:comment "(Rn +) − (Rn −), where Rn + = (emission intensity of reporter dye)/(emission intensity of passive reference dye) in PCR with template and Rn − = (emission intensity of reporter dye)/(emission intensity of passive reference dye) in PCR without template or early cycles of a real-time reaction. Ct = threshold cycle, i.e., cycle at which a statistically significant increase in ΔRn is first detected"@en ;
rdfs:subClassOf obo:IAO_0000027 .
obo:OBI_0200170 a rdfs:Class ;
rdfs:label "averaging data transformation"@en ;
rdfs:comment "An averaging data transformation is a data transformation that has objective averaging."@en ;
rdfs:subClassOf obo:OBI_0200000 .
obo:STATO_0000203 a rdfs:Class ;
rdfs:label "cohort" ;
rdfs:comment "a cohort is a study group population where the members are human beings which meet inclusion criteria and undergo a longitudinal design"@en ;
rdfs:subClassOf obo:STATO_0000193 .
obo:OBI_0000416 a rdfs:Class ;
rdfs:label "cloning insert role"@en ;
rdfs:comment "cloning insert role is a role which inheres in DNA or RNA and is realized by the process of being inserted into a cloning vector in a cloning process."@en ;
rdfs:subClassOf obo:BFO_0000023 .
obo:STATO_0000667 a rdfs:Class ;
rdfs:label "minimum possible value"@en ;
rdfs:comment "A statistic that represents the smallest value that could occur."@en ;
rdfs:subClassOf obo:STATO_0000039 .
obo:STATO_0000233 a rdfs:Class ;
rdfs:label "true positive rate"@en ;
rdfs:comment "sensitivity is a measurement datum qualifying a binary classification test and is computed by substracting the false negative rate to the integral numeral 1"@en ;
rdfs:subClassOf obo:STATO_0000184 .
obo:OBI_0000789 a rdfs:Class ;
rdfs:label "survival rate"@en ;
rdfs:comment "A rate that represents the percentage of people or animals in a study or treatment group who are alive for a given period of time after diagnosis or initiation of monitoring." ;
rdfs:subClassOf obo:IAO_0000109 , obo:STATO_0000645 .
obo:STATO_0000300 a rdfs:Class ;
rdfs:label "dimensionless ratio" ;
rdfs:comment "A ratio where the numerator and denominator are expressed in the same unit." ;
rdfs:subClassOf obo:STATO_0000184 .
obo:STATO_0000730 a rdfs:Class ;
rdfs:label "ratio variable" ;
rdfs:comment "A continuous variable with a true zero point and ordered, equally spaced units where the difference between values is meaningful." ;
rdfs:subClassOf obo:STATO_0000251 .
obo:OBI_0400110 a rdfs:Class ;
rdfs:label "hybridization chamber"@en ;
rdfs:comment "A device which is used to maintain constant contact of a liquid on an array. This can be either a glass vial or slide."@en ;
rdfs:subClassOf obo:OBI_0002089 .
obo:STATO_0000273 a rdfs:Class ;
rdfs:label "child-parents trio"@en ;
rdfs:comment "A population of two parents and a child." ;
rdfs:subClassOf obo:STATO_0000257 .
obo:OBI_0200181 a rdfs:Class ;
rdfs:label "center calculation data transformation"@en ;
rdfs:comment "A center calculation data transformation is a data transformation that has objective of center calculation."@en ;
rdfs:subClassOf obo:OBI_0200000 .
obo:STATO_0000339 a rdfs:Class ;
rdfs:label "breeding value estimation using pedigree data"@en ;
rdfs:comment "breeding value estimation is a data transformation process aiming at computing breeding value estimates of an organism given a set of pedigree information." ;
rdfs:subClassOf obo:STATO_0000337 .
obo:STATO_0000656 a rdfs:Class ;
rdfs:label "slope" ;
rdfs:comment """the slope of a line graph is a data item denoting the rate of change between the two variables represented on the graph.
the slope is used to visualize and interpret the relationship between two variables.""" ;
rdfs:subClassOf obo:IAO_0000027 .
obo:STATO_0000712 a rdfs:Class ;
rdfs:label "superiority margin"@en ;
rdfs:comment """A hypothesis testing margin of zero used in a study with a superiority goal.
The superiority margin (also sometimes called the minimal clinically important difference) defines how much better one treatment must be to be considered meaningfully superior — not just statistically different.""" ;
rdfs:subClassOf obo:STATO_0000709 .
obo:STATO_0000520 a rdfs:Class ;
rdfs:label "regression data imputation"@en ;
rdfs:comment "regression data imputation is a type of data imputation where missing values are replaced with the value of a regression function coefficient." ;
rdfs:subClassOf obo:STATO_0000518 .
obo:STATO_0000497 a rdfs:Class ;
rdfs:label "Z matrix" ;
rdfs:comment "the Z-matrix is a genomic relationship matrix which is obtained by substracted the M matrix with the P matrix. It is also known as the incidence matrix for the markers." ;
rdfs:subClassOf obo:STATO_0000642 .
obo:OBI_0000378 a rdfs:Class ;
rdfs:label "filter function"@en ;
rdfs:comment "A filter function is a function to prevent the flow of certain entities based on a quality or qualities of the entity while allowing entities which have different qualities to pass through"@en ;
rdfs:subClassOf obo:OBI_0000372 .
obo:STATO_0000033 a rdfs:Class ;
rdfs:label "mode"@en ;
rdfs:comment "The mode is a data item which corresponds to the most frequently occurring number in a set of numbers."@en ;
rdfs:subClassOf obo:OBI_0000649 , obo:STATO_0000029 , obo:STATO_0000574 .
obo:STATO_0000563 a rdfs:Class ;
rdfs:label "biplot"@en ;
rdfs:comment "Biplots are a type of exploratory graph used in statistics, a generalization of the simple two-variable scatterplot. A biplot is constructed by using the singular value decomposition (SVD) to obtain a low-rank approximation to a transformed version of the data matrix X, whose n rows are the samples (also called the cases, or objects), and whose p columns are the variables. The biplot was introduced by K. Ruben Gabriel (1971)."@en ;
rdfs:subClassOf obo:IAO_0000038 .
obo:STATO_0000160 a rdfs:Class ;
rdfs:label "exponential distribution"@en ;
rdfs:comment "The exponential distribution (a.k.a. negative exponential distribution) is the probability distribution that describes the time between events in a Poisson process, i.e. a process in which events occur continuously and independently at a constant average rate. It is the continuous analogue of the geometric distribution, and it has the key property of being memoryless."@en ;
rdfs:subClassOf obo:STATO_0000067 .
obo:STATO_0000693 a rdfs:Class ;
rdfs:label "probability distribution variance"@en ;
rdfs:comment "A distribution variance is defined as a probability distribution attribute that is the expected value of the square of the difference of the value of a variable that has that distribution from its expected value."@en ;
rdfs:subClassOf obo:STATO_0000113 .
obo:IAO_0000104 a rdfs:Class ;
rdfs:label "plan specification"@en ;
rdfs:comment "A directive information entity with action specifications and objective specifications as parts that, when concretized, is realized in a process in which the bearer tries to achieve the objectives by taking the actions specified."@en ;
rdfs:subClassOf obo:IAO_0000033 .
obo:STATO_0000038 a rdfs:Class ;
rdfs:label "matched pair of subjects"@en ;
rdfs:comment "a set of 2 subjects which result from a pairing process which assigns subject to a set based on a pairing rule/criteria"@en ;
rdfs:subClassOf obo:OBI_0000181 .
obo:OBI_0200154 a rdfs:Class ;
rdfs:label "agglomerative hierarchical clustering"@en ;
rdfs:comment "An agglomerative hierarchical clustering is a hierarchical clustering which starts with separate clusters and then successively combines these clusters until there is only one cluster remaining."@en ;
rdfs:subClassOf obo:OBI_0200042 .
obo:OBI_0600024 a rdfs:Class ;
rdfs:label "maintaining cell culture"@en ;
rdfs:comment "a protocol application in which cells are kept alive in a defined environment outside of an organism. part of cell_culturing"@en ;
rdfs:subClassOf obo:OBI_0000838 .
obo:STATO_0000723 a rdfs:Class ;
rdfs:label "discrete variable" ;
rdfs:comment "A quantitative variable for which only integer values are allowed." ;
rdfs:subClassOf obo:STATO_0000722 .
obo:OBI_0000443 a rdfs:Class ;
rdfs:label "analyte assay"@en ;
rdfs:comment "An assay with the objective to capture information about the presence, concentration, or amount of an analyte in an evaluant."@en ;
rdfs:subClassOf obo:OBI_0000070 .
obo:STATO_0000271 a rdfs:Class ;
rdfs:label "permutation numbering"@en ;
rdfs:comment "permutation numbering is a data tranformation allowing to count the number of possible permutations of elements in a set of size n, each element occurring exactly once. This number is factorial n."@en ;
rdfs:subClassOf obo:OBI_0200000 .
obo:STATO_0000444 a rdfs:Class ;
rdfs:label "split-plot design"@en ;
rdfs:comment """a split-plot design is kind of factorial design which is used when running a full factorial completely randomized design is inpractical, either for cost or practicalities (e.g. equipment, fields), in other words, when a restricted randomization has to be applied. A split-plot design is used whenever practioners fix the level of 'hard to change factor' and run all the combinations of the other factors. The hard to change factor is also refered to as the 'whole plot' factor, while the remainders of the factors are refered to as 'split plot factor'.
Performing a split-plot design therefore means fixing one factor level, and then applying the treatments formed by the cartesian products of the levels for the other factors. A mininum of 2 factors are required and one being applied before the other(s)."""@en ;
rdfs:subClassOf obo:OBI_0500000 , obo:STATO_0000586 .
obo:STATO_0000085 a rdfs:Class ;
rdfs:label "effect size estimate"@en ;
rdfs:comment "effect size estimate is a data item about the direction and strength of the consequences of a causative agent as explored by statistical methods. Those methods produce estimates of the effect size, e.g. confidence interval"@en ;
rdfs:subClassOf obo:STATO_0000471 .
obo:STATO_0000260 a rdfs:Class ;
rdfs:label "repeated measure ANOVA" ;
rdfs:comment """repeated measure ANOVA is a kind of ANOVA specifically developed for non-independent observations as found when repeated measurements on the sample experimental unit.
repeated measure ANOVA is sensitive to departure from normality (evaluation using Bartlett's test), more so in the case of unbalanced groups (i.e. different sizes of sample populations).
Departure from sphericity (evaluation using Mauchly'test) used to be an issue which is now handled robustly by modern tools such as R's lme4 or nlme, which accommodate dependence assumptions other than sphericity."""@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:OBI_0200201 , obo:STATO_0000202 .
obo:STATO_0000691 a rdfs:Class ;
rdfs:label "area under the precision-recall curve" ;
rdfs:comment "An area under the curve where the curve is the precision and the domain of interest is the recall." ;
rdfs:subClassOf obo:STATO_0000209 .
obo:STATO_0000204 a rdfs:Class ;
rdfs:label "F-distribution"@en ;
rdfs:comment "the F-distribution is a continuous probability distribution which arises in the testing of whether two observed samples have the same variance."@en ;
rdfs:subClassOf obo:STATO_0000067 .
obo:IAO_0000401 a rdfs:Class ;
rdfs:label "one dimensional cartesian spatial coordinate datum"@en ;
rdfs:comment "A cartesion spatial coordinate datum that uses one value to specify a position along a one dimensional spatial region"@en ;
rdfs:subClassOf obo:IAO_0000400 .
obo:OBI_0000181 a rdfs:Class ;
rdfs:label "population"@en ;
rdfs:comment "a population is a collection of individuals from the same taxonomic class living, counted or sampled at a particular site or in a particular area"@en ;
rdfs:subClassOf obo:BFO_0000040 .
obo:STATO_0000134 a rdfs:Class ;
rdfs:label "true negative rate"@en ;
rdfs:comment "specificity is a measurement datum qualifying a binary classification test and is computed by substracting the false positive rate to the integral numeral 1"@en ;
rdfs:subClassOf obo:STATO_0000184 .
obo:STATO_0000074 a rdfs:Class ;
rdfs:label "Cochran-Mantel-Haenzel test for repeated tests of independence"@en ;
rdfs:comment """Cochran-Mantel-Haenzel test for repeated tests of independence is a statitiscal test which allows the comparison of two groups on a dichotomous/categorical response. It is used when the effect of the explanatory variable on the response variable is influenced by covariates that can be controlled. It is often used in observational studies where random assignment of subjects to different treatments cannot be controlled, but influencing covariates can.
The null hypothesis is that the two nominal variables that are tested within each repetition are independent of each other. So there are 3 variables to consider: two categorical variables to be tested for independence of each other, and the third variable identifies the repeats."""@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000027 .
obo:STATO_0000045 a rdfs:Class ;
rdfs:label "two-way ANOVA"@en ;
rdfs:comment "two-way anova is an analysis of variance where the different groups being compared are associated the factor levels of exatly 2 independent variables. The null hypothesis is an absence of difference between the means calculated for each of the groups. The test assumes normality and equivariance of the data."@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:OBI_0200201 .
obo:STATO_0000111 a rdfs:Class ;
rdfs:label "sequence read"@en ;
rdfs:comment "a sequence read is a DNA sequence data which is generated by a DNA sequencer"@en ;
rdfs:subClassOf obo:OBI_0001573 .
obo:STATO_0000222 a rdfs:Class ;
rdfs:label "graeco-latin square design"@en ;
rdfs:comment "graeco-latin square design is_a study design which allows in its simpler form controlling 3 levels of nuisance variables (also known as blocking variables). The 3 nuisance factors are divided into a tabular grid with the property that each row and each column receive each treatment exactly once."@en ;
rdfs:subClassOf obo:OBI_0500007 .
obo:STATO_0000072 a rdfs:Class ;
rdfs:label "substrate concentration"@en ;
rdfs:comment "substrate concentration is a scalar measurement datum which denotes the amount of molecular entity involved in an enzymatic reaction (or catalytic chemical reaction) and whose role in that reaction is as substrate."@en ;
rdfs:subClassOf obo:STATO_0000704 .
obo:STATO_0000663 a rdfs:Class ;
rdfs:label "F-beta score"@en ;
rdfs:comment "The F-beta score is a measure of a model's accuracy, specifically designed to evaluate the performance of binary classification models. It is a generalized form of the F1 score, which itself is the harmonic mean of precision and recall. The F-beta score introduces a way to weigh recall more heavily than precision (or vice versa) depending on the value of beta."@en ;
rdfs:subClassOf obo:STATO_0000623 .
obo:OBI_0000011 a rdfs:Class ;
rdfs:label "planned process"@en ;
rdfs:comment "A processual entity that realizes a plan which is the concretization of a plan specification."@en ;
rdfs:subClassOf obo:BFO_0000015 .
obo:OBI_0001931 a rdfs:Class ;
rdfs:label "scalar value specification" ;
rdfs:comment "A value specification that consists of two parts: a numeral and a unit label" ;
rdfs:subClassOf obo:OBI_0001933 .
obo:STATO_0000607 a rdfs:Class ;
rdfs:label "proportion" ;
rdfs:comment "a proportion is a ratio which corresponds to the fraction of the total presenting a particular feature" ;
rdfs:subClassOf obo:STATO_0000184 .
obo:STATO_0000458 a rdfs:Class ;
rdfs:label "99% credible interval"@en ;
rdfs:comment "In Bayesian statistics context, a 99% credible interval is a credible interval which, given the data, includes the true parameter with probability of 99%."@en ;
rdfs:subClassOf obo:STATO_0000455 .
obo:STATO_0000715 a rdfs:Class ;
rdfs:label "A/B testing" ;
rdfs:comment "a type of statistical testing comparing 2 types of treatments or interventions." ;
rdfs:subClassOf obo:STATO_0000279 .
obo:STATO_0000412 a rdfs:Class ;
rdfs:label "prevalence"@en ;
rdfs:comment "A proportion in which the numerator represents all events of interest (for example, both new and preexisting cases of a disease) in the population, which is represented by the denominator."@en ;
rdfs:subClassOf obo:STATO_0000607 .
obo:STATO_0000127 a rdfs:Class ;
rdfs:label "99% confidence interval"@en ;
rdfs:comment "a confidence interval which covers 99% of the sampling distribution, meaning that there is a 1% risk of false positive (type I error)"@en ;
rdfs:subClassOf obo:STATO_0000196 .
obo:IAO_0000033 a rdfs:Class ;
rdfs:label "directive information entity"@en ;
rdfs:comment "An information content entity whose concretizations indicate to their bearer how to realize them in a process."@en ;
rdfs:subClassOf obo:IAO_0000030 .
obo:STATO_0000347 a rdfs:Class ;
rdfs:label "Matern function anisotropic covariance structure"@en ;
rdfs:comment "Given two sets of locations computes the Matern cross covariance matrix for covariances among all pairings."@en ;
rdfs:subClassOf obo:STATO_0000346 .
obo:BFO_0000002 a rdfs:Class ;
rdfs:label "continuant"@en ;
rdfs:comment "An entity that exists in full at any time in which it exists at all, persists through time while maintaining its identity and has no temporal parts."@en ;
rdfs:subClassOf obo:BFO_0000001 .
obo:STATO_0000504 a rdfs:Class ;
rdfs:label "line intercept sampling"@en ;
rdfs:comment "line intercept sampling is a sampling process by which an element in a spatial region is included in a sample if it is intersected by a line chosen by the operator."@en ;
rdfs:subClassOf obo:STATO_0000509 .
obo:IAO_0000306 a rdfs:Class ;
rdfs:label "table"@en ;
rdfs:comment "A textual entity that contains a two-dimensional arrangement of texts repeated at regular intervals across a spatial range, such that the spatial relationships among the constituent texts expresses propositions"@en ;
rdfs:subClassOf obo:IAO_0000300 .
obo:STATO_0000700 a rdfs:Class ;
rdfs:label "p-value"@en ;
rdfs:comment "A hypothesis testing measure that represents the probability of obtaining a result at least as far from the value actually obtained as the value expected, assuming the null hypothesis is true."@en ;
rdfs:subClassOf obo:OBI_0000071 .
obo:STATO_0000034 a rdfs:Class ;
rdfs:label "model parameter"@en ;
rdfs:comment "a model parameter is a data item which is part of a model and which is meant to characterize an theoritecal or unknown population. a model parameter may be estimated by considering the properties of samples presumably taken from the theoritecal population"@en ;
rdfs:subClassOf obo:IAO_0000027 .
obo:OBI_0000953 a rdfs:Class ;
rdfs:label "processed specimen" ;
rdfs:comment "A specimen that has been intentionally physically modified." ;
rdfs:subClassOf obo:OBI_0000047 , obo:OBI_0100051 .
obo:OBI_0200163 a rdfs:Class ;
rdfs:label "false discovery rate correction method"@en ;
rdfs:comment "The false discovery rate is a data transformation used in multiple hypothesis testing to correct for multiple comparisons. It controls the expected proportion of incorrectly rejected null hypotheses (type I errors) in a list of rejected hypotheses. It is a less conservative comparison procedure with greater power than familywise error rate (FWER) control, at a cost of increasing the likelihood of obtaining type I errors. ." ;
rdfs:subClassOf obo:APOLLO_SV_00000796 , obo:OBI_0200089 .
obo:OBI_0400043 a rdfs:Class ;
rdfs:label "flow cell"@en ;
rdfs:comment "Aparatus in the fluidic subsystem where the sheath and sample meet. Can be one of several types; jet-in-air, quartz cuvette, or a hybrid of the two. The sample flows through the center of a fluid column of sheath fluid in the flow cell."@en ;
rdfs:subClassOf obo:OBI_0000967 .
obo:STATO_0000632 a rdfs:Class ;
rdfs:label "misclassification rate" ;
rdfs:comment "A ratio of the number of incorrect results to the total number tested." ;
rdfs:subClassOf obo:STATO_0000623 .
obo:STATO_0000151 a rdfs:Class ;
rdfs:label "maximum observed value" ;
rdfs:comment "maximum value is a data item which denotes the largest value found in a dataset or resulting from a calculation."@en ;
rdfs:subClassOf obo:STATO_0000039 .
obo:STATO_0000738 a rdfs:Class ;
rdfs:label "alpha level as statistical test input parameter" ;
rdfs:comment "A hypothesis test parameter input that represents the probability of incorrectly rejecting the null hypothesis." ;
rdfs:subClassOf obo:IAO_0000027 .
obo:PATO_0001739 a rdfs:Class ;
rdfs:label "radiation quality" ;
rdfs:comment "A quality that inheres in an bearer by virtue of how that bearer interacts with radiation." ;
rdfs:subClassOf obo:PATO_0001018 .
obo:STATO_0000726 a rdfs:Class ;
rdfs:label "polychotomous ordinal variable" ;
rdfs:comment "An ordinal variable which is defined to have minimally 2 categories or possible values." ;
rdfs:subClassOf obo:STATO_0000087 , obo:STATO_0000228 , obo:STATO_0000252 .
obo:STATO_0000067 a rdfs:Class ;
rdfs:label "continuous probability distribution"@en ;
rdfs:comment "a continuous probability distribution is a probability distribution which is defined by a probability density function"@en ;
rdfs:subClassOf obo:STATO_0000225 .
obo:STATO_0000610 a rdfs:Class ;
rdfs:label "measure of association"@en ;
rdfs:comment "measure of association is a statistic which quantitatively represents a relationship between two or more variables"@en ;
rdfs:subClassOf obo:STATO_0000039 .
obo:OBI_0000437 a rdfs:Class ;
rdfs:label "analyte measurement objective"@en ;
rdfs:comment "an assay objective to determine the presence or concentration of an analyte in the evaluant"@en ;
rdfs:subClassOf obo:OBI_0000441 .
obo:STATO_0000105 a rdfs:Class ;
rdfs:label "log signal intensity ratio"@en ;
rdfs:comment "log signal intensity ratio is a data item which corresponding the logarithmitic base 2 of the ratio between 2 signal intensity, each corresponding to a condition."@en ;
rdfs:subClassOf obo:STATO_0000184 .
obo:OBI_0500017 a rdfs:Class ;
rdfs:label "dye swap design"@en ;
rdfs:comment "An experiment design type where the label orientations are reversed. exact synonym: flip dye, dye flip"@en ;
rdfs:subClassOf obo:OBI_0500000 , obo:STATO_0000046 .
obo:STATO_0000460 a rdfs:Class ;
rdfs:label "interim analysis"@en ;
rdfs:comment "interim analysis is a data transformation used to analyzed studies implementing a group-sequential design, to evaluate and interpret the accumulating information during a clinical trial. It means that the analysis of data that is conducted before full data collection has been completed. Clinical trials are unusual in that enrollment of patients is a continual process staggered in time. This means that if a treatment is particularly beneficial or harmful compared to the concurrent placebo group while the study is on-going, the investigators are ethically obliged to assess that difference using the data at hand and to make a deliberate consideration of terminating the study earlier than planned."@en ;
rdfs:subClassOf obo:OBI_0200000 .
obo:STATO_0000282 a rdfs:Class ;
rdfs:label "F-statistic"@en ;
rdfs:comment "F statistic is a statistic computed from observations and used to produce a p-value in statistical test when compared to a F distribution. the F statistic is the ratio of two scaled sums of squares reflecting different sources of variability"@en ;
rdfs:subClassOf obo:STATO_0000039 .
obo:STATO_0000083 a rdfs:Class ;
rdfs:label "Kolmogorov-Smirnov test"@en ;
rdfs:comment "Kolmogorov-Smirnov test is a goodness of fit test which evaluates the null hypothesis that a sample is drawn from a population that follows a specific continuous probability distribution."@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000191 .
obo:OBI_1000029 a rdfs:Class ;
rdfs:label "phage display library"@en ;
rdfs:comment "a phage display library is a collection of materials in which a mixture of genes or gene fragments is expressed and can be individually selected and amplified."@en ;
rdfs:subClassOf obo:OBI_0000731 .
obo:IAO_0000015 a rdfs:Class ;
rdfs:label "information carrier"@en ;
rdfs:comment "A quality of an information bearer that imparts the information content"@en ;
rdfs:subClassOf obo:BFO_0000019 .
obo:STATO_0000145 a rdfs:Class ;
rdfs:label "geometric distribution"@en ;
rdfs:comment """the geometric distribution is a negative binomial distribution where r is 1.
It is useful for modeling the runs of consecutive successes (or failures) in repeated independent trials of a system.
The geometric distribution models the number of successes before one failure in an independent succession of tests where each test results in success or failure.
The geometric distribution with prob = p has density
p(x) = p (1-p)^x
for x = 0, 1, 2, …, 0 < p ≤ 1.
If an element of x is not integer, the result of dgeom is zero, with a warning.
The quantile is defined as the smallest value x such that F(x) ≥ p, where F is the distribution function."""@en ;
rdfs:subClassOf obo:STATO_0000283 .
obo:STATO_0000696 a rdfs:Class ;
rdfs:label "value-time curve" ;
rdfs:comment "a value-time curve is a graph which plot time on the x-axis versus the value of a variable of interest as delivered by a process. It is used to represent the relationship there is the value and the time it takes to achieve that value. It is commonly used in project management or business analysis to evaluate and optimize how efficiently value is delivered over time."@en ;
rdfs:subClassOf obo:IAO_0000038 .
obo:STATO_0000116 a rdfs:Class ;
rdfs:label "assess statistical evidence"@en ;
rdfs:comment "the process of using statistical analysis for interpreting and communicating \"what the data say\"."@en ;
rdfs:subClassOf obo:OBI_0000011 .
obo:STATO_0000540 a rdfs:Class ;
rdfs:label "reproducing kernel Hilbert space procedure"@en ;
rdfs:comment "A data transformation that produces a reproducing kernel Hilbert space (or RKHS), which is a Hilbert space of functions in which point evaluation is a continuous linear functional."@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000119 , obo:STATO_0000337 .
obo:STATO_0000621 a rdfs:Class ;
rdfs:label "diagnostic yield" ;
rdfs:comment "diagnostic yield is a proportion in which the numerator represents the correctly detected items within the denominator that represents all items tested." ;
rdfs:subClassOf obo:STATO_0000607 .
obo:STATO_0000256 a rdfs:Class ;
rdfs:label "manhattan plot for gwas"@en ;
rdfs:comment "a manhattan plot for gwas is a kind of scatter plot used to facilitate presentation of genome-wide association study (GWAS) data. Genomic coordinates are displayed along the X-axis, with the negative logarithm of the association P-value for each single nucleotide polymorphism displayed on the Y-axis."@en ;
rdfs:subClassOf obo:IAO_0000184 .
obo:IAO_0000064 a rdfs:Class ;
rdfs:label "algorithm"@en ;
rdfs:comment "A plan specification which describes the inputs and output of mathematical functions as well as workflow of execution for achieving an predefined objective. Algorithms are realized usually by means of implementation as computer programs for execution by automata."@en ;
rdfs:subClassOf obo:IAO_0000104 .
obo:STATO_0000336 a rdfs:Class ;
rdfs:label "best linear unbiased predictor" ;
rdfs:comment "best linear unbiased prediction is a data transformation which predicts under the assumption that the variable(s) under consideration have a random effect" ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000119 , obo:STATO_0000337 .
obo:STATO_0000433 a rdfs:Class ;
rdfs:label "McNemar test"@en ;
rdfs:comment """McNemar's test is a statistical test used on paired nominal data. It is applied to 2 × 2 contingency tables with a dichotomous trait, with matched pairs of subjects, to determine whether the row and column marginal frequencies are equal (that is, whether there is \"marginal homogeneity\"). It is named after Quinn McNemar, who introduced it in 1947.
An application of the test in genetics is the transmission disequilibrium test for detecting linkage disequilibrium"""@en ;
rdfs:subClassOf obo:OBI_0000673 , obo:OBI_0200000 .
obo:OBI_0000250 a rdfs:Class ;
rdfs:label "dye role"@en ;
rdfs:comment "A molecular label role which inheres in a material entity and which is realized in the process of detecting a molecular dye that imparts color to some material of interest. " ;
rdfs:subClassOf obo:OBI_0002743 .
obo:STATO_0000524 a rdfs:Class ;
rdfs:label "Matthews correlation coefficient" ;
rdfs:comment "Matthews Correlation Coefficient (or MCC) is a correlation coefficient which is a measure of the quality of binary (two-class) classifications, introduced by biochemist Brian W. Matthews in 1975." ;
rdfs:subClassOf obo:STATO_0000142 , obo:STATO_0000622 .
obo:STATO_0000140 a rdfs:Class ;
rdfs:label "contingency table"@en ;
rdfs:comment """a contigency table is a data item which displays the (multivariate) frequency distribution of the possible values of categorical variables.
The first row of the table corresponds to categories of one categorical variable, the first column of the table corresponds to categories of the other categorical variable, the cells corresponding to each combination of categories is filled with the observed occurences in the sample being considered.
The table also contains marginal total (marginal sums) and grand total of the occurences
The term contingency table was first used by Karl Pearson in \"On the Theory of Contingency and Its Relation to Association and Normal Correlation\", part of the Drapers' Company Research Memoirs Biometric Series I published in 1904."""@en ;
rdfs:subClassOf obo:STATO_0000642 .
obo:OBI_0001444 a rdfs:Class ;
rdfs:label "genotyping design"@en ;
rdfs:comment "A study design that classifies an individual or group of individuals on the basis of alleles, haplotypes, SNPs."@en ;
rdfs:subClassOf obo:OBI_0500000 .
obo:STATO_0000211 a rdfs:Class ;
rdfs:label "odds ratio homogeneity hypothesis"@en ;
rdfs:comment "odds ratio homogeneity hypothesis is a null hypothesis stating that all odds ratio are homogenous, that is remain within the same range."@en ;
rdfs:subClassOf obo:STATO_0000065 .
obo:STATO_0000529 a rdfs:Class ;
rdfs:label "scaled t distribution" ;
rdfs:comment "a scaled t distribution is a kind of Student's t distribution which is shifted by 'mean' and scaled by standard deviation 'sd'." ;
rdfs:subClassOf obo:STATO_0000059 .
obo:STATO_0000179 a rdfs:Class ;
rdfs:label "ANCOVA" ;
rdfs:comment """ANCOVA or analysis of covariance is a data transformation which evaluates if population means of a dependent variable are equal across levels of a categorical independent variables while controlling for the effects of other continuous variable s, known as covariates. Therefore, when performing ANCOVA, we are adjusting the dependent variable means to what they would be if all groups were equal on the covariates.
It augments the ANOVA model with one or more additional quantitative variables, called covariates, which are related to the response variable. The covariates are included to reduce the variance in the error terms and provide more precise measurement of the treatment effects. ANCOVA is used to test the main and interaction effects of the factors, while controlling for the effects of the covariate"""@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000279 .
obo:OBI_0200191 a rdfs:Class ;
rdfs:label "gene list visualization" ;
rdfs:comment "Adata visualization which has input of a gene list and produces an output of a report graph which is capable of rendering data of this type." ;
rdfs:subClassOf obo:OBI_0200111 .
obo:OBI_0001755 a rdfs:Class ;
rdfs:label "selection criterion"@en ;
rdfs:comment "A directive information entity which defines and states a principle of standard by which selection process may take place."@en ;
rdfs:subClassOf obo:IAO_0000033 .
obo:STATO_0000584 a rdfs:Class ;
rdfs:label "Wald statistic" ;
rdfs:comment """the Wald statistic is a statistic is used during a Wald test, a test of significance of the regression coefficient; it is based on the asymptotic normality property of maximum likelihood estimates, and is computed as:
W = b * 1/Var(b) * b
In this formula, b stands for the parameter estimates, and Var(b) stands for the asymptotic variance of the parameter estimates. The Wald statistic is tested against the Chi-square distribution in the Wald test.""" ;
rdfs:subClassOf obo:STATO_0000039 .
obo:STATO_0000671 a rdfs:Class ;
rdfs:label "hazard rate"@en ;
rdfs:comment "A conditional instantaneous rate in which the numerator represents an incidence conditioned on survival to a specified time, and the denominator represents a time interval with a duration approaching zero."@en ;
rdfs:subClassOf obo:STATO_0000645 .
obo:STATO_0000217 a rdfs:Class ;
rdfs:label "sphericity hypothesis"@en ;
rdfs:comment "a null hypothesis which states that a given matrix is proportional to a Wishart-distributed covariance matrix"@en ;
rdfs:subClassOf obo:STATO_0000065 .
obo:STATO_0000652 a rdfs:Class ;
rdfs:label "calibration" ;
rdfs:comment "calibration in statistics refers to the process of ensuring that the predicted probabilities or scores from a statistical model accurately reflect the true probabilities or outcomes observed in the data. It is an essential aspect of predictive modeling to ensure the reliability and interpretability of model predictions, where the goal is to estimate the likelihood of certain events or outcomes." ;
rdfs:subClassOf obo:OBI_0200000 .
obo:STATO_0000184 a rdfs:Class ;
rdfs:label "ratio" ;
rdfs:comment "A ratio is a data item which is formed with two numbers r and s is written r/s, where r is the numerator and s is the denominator. The ratio of r to s is equivalent to the quotient r/s."@en ;
rdfs:subClassOf obo:STATO_0000039 .
obo:STATO_0000065 a rdfs:Class ;
rdfs:label "hypothesis"@en ;
rdfs:comment "In statistics, a statement that can be tested.[wolfram alpha]"@en ;
rdfs:subClassOf obo:IAO_0000030 .
obo:STATO_0000230 a rdfs:Class ;
rdfs:label "expected value"@en ;
rdfs:comment "the expected value (or expectation, mathematical expectation, EV, mean, or the first moment) of a random variable is a data item which corresponds to the weighted average of all possible values that this random variable can take on. The weights used in computing this average correspond to the probabilities in case of a discrete random variable, or densities in case of a continuous random variable. From a rigorous theoretical standpoint, the expected value is the integral of the random variable with respect to its probability measure."@en ;
rdfs:subClassOf obo:STATO_0000029 .
obo:STATO_0000453 a rdfs:Class ;
rdfs:label "Roy’s Maximum Root"@en ;
rdfs:comment "Roy's maximum root is a statistic used in multivariate analysis of variance to find the maximum characteristic root or eigenvalue statistic for testing equality of k p-variate normal distributions with same covariance matrix, independence between two sets of variables jointly distributed as a normal distribution, equality of covariance matrices of two p-variate normal distributions, whether the covariance matrix of a p-variabte normal distribution with unknown mean vector equals a specified matrix."@en ;
rdfs:subClassOf obo:STATO_0000039 .
obo:IAO_0000101 a rdfs:Class ;
rdfs:label "image"@en ;
rdfs:comment "An image is an affine projection to a two dimensional surface, of measurements of some quality of an entity or entities repeated at regular intervals across a spatial range, where the measurements are represented as color and luminosity on the projected on surface."@en ;
rdfs:subClassOf obo:IAO_0000308 .
obo:STATO_0000309 a rdfs:Class ;
rdfs:label "Pearson's Chi square test of goodness of fit"@en ;
rdfs:comment "Pearson's Chi-Squared test for goodnes of fit is a statistical null hypothesis test which is used to either evaluate goodness of fit of dataset to a Chi-Squared distribution"@en ;
rdfs:subClassOf obo:OBI_0200200 , obo:STATO_0000191 .
obo:CL_0000578 a rdfs:Class ;
rdfs:label "experimentally modified cell in vitro" ;
rdfs:comment "A cell in vitro that has undergone physical changes as a consequence of a deliberate and specific experimental procedure." ;
rdfs:subClassOf obo:CL_0000000 , obo:OBI_0000047 .
obo:OBI_0200073 a rdfs:Class ;
rdfs:label "family wise error rate correction method"@en ;
rdfs:comment "A family wise error rate correction method is a multiple testing procedure that controls the probability of at least one false positive." ;
rdfs:subClassOf obo:APOLLO_SV_00000796 , obo:OBI_0200089 .
obo:STATO_0000573 a rdfs:Class ;
rdfs:label "average value" ;
rdfs:comment """The arithmetic mean is defined as the sum of the numerical values of each and every observation divided by the total number of observations. S The arithmetic mean A is defined by the formula
A=sum[Ai] / n where i ranges from 1 to n and Ai represents the value of individual observations.
The arithmetic mean is significantly affected by extreme values and outliers. A better measure of central tendency is the median (http://purl.obolibrary.org/obo/STATO_0000574).""" ;
rdfs:subClassOf obo:STATO_0000029 .
obo:STATO_0000235 a rdfs:Class ;
rdfs:label "genetic association study"@en ;
rdfs:comment "A genetic association study is a kind of study whose objective is to detect associations between phenotypes, between a phenotype and a genetic polymorphism or between two genetic polymorphisms."@en ;
rdfs:subClassOf obo:OBI_0000066 .
obo:STATO_0000321 a rdfs:Class ;
rdfs:label "non-parametric distribution" ;
rdfs:comment "Probability distribution estimated empirically on the data without assumptions on the shape of the probability distribution." ;
rdfs:subClassOf obo:STATO_0000225 , obo:STATO_0000329 .
obo:STATO_0000603 a rdfs:Class ;
rdfs:label "alpha debt" ;
rdfs:comment "a sequential multiple correction procedure which does not maintain a constant false positive rate but allows it to grow controllably." ;
rdfs:subClassOf obo:STATO_0000602 .
obo:OBI_0100026 a rdfs:Class ;
rdfs:label "organism"@en ;
rdfs:comment "A material entity that is an individual living system, such as animal, plant, bacteria or virus, that is capable of replicating or reproducing, growth and maintenance in the right environment. An organism may be unicellular or made up, like humans, of many billions of cells divided into specialized tissues and organs."@en ;
rdfs:subClassOf obo:BFO_0000040 .
obo:STATO_0000626 a rdfs:Class ;
rdfs:label "relative risk difference"@en ;
rdfs:comment """A statistic that is a difference between 1 and a ratio of the two risk values being compared.
Relative Risk Difference = 1 - ( a / b ) where a and b are risk values.
The relative risk difference can also be defined as a statistic that is a ratio of the risk difference to the risk used as a reference. Relative Risk Difference = ( b - a ) / ( b ) where b is the reference risk value and a is another risk value."""@en ;
rdfs:subClassOf obo:STATO_0000615 .
obo:STATO_0000054 a rdfs:Class ;
rdfs:label "homoskedasticity hypothesis"@en ;
rdfs:comment "homoskedasticity states that all variances under consideration are homogenous."@en ;
rdfs:subClassOf obo:STATO_0000065 .
obo:OBI_0000441 a rdfs:Class ;
rdfs:label "assay objective"@en ;
rdfs:comment "an objective specification to determine a specified type of information about an evaluated entity (the material entity bearing evaluant role)"@en ;
rdfs:subClassOf obo:IAO_0000005 .
obo:STATO_0000423 a rdfs:Class ;
rdfs:label "observed risk"@en ;
rdfs:comment "the proportion of individuals in a population with the outcome of interest"@en ;
rdfs:subClassOf obo:STATO_0000620 .
obo:STATO_0000241 a rdfs:Class ;
rdfs:label "Q-Q plot"@en ;
rdfs:comment "Q-Q plot or quantile-quantile plot is the output of a graphical method for comparing two probability distributions by plotting their quantiles against each other"@en ;
rdfs:subClassOf obo:IAO_0000038 .
obo:STATO_0000375 a rdfs:Class ;
rdfs:label "residual mean square" ;
rdfs:comment "a residual mean square is a data item which is obtained by dividing the sum of squared residuals (SSR) by the number of degrees of freedom" ;
rdfs:subClassOf obo:STATO_0000039 .
obo:OBI_0500012 a rdfs:Class ;
rdfs:label "graeco latin square design"@en ;
rdfs:comment "Greco-Latin square design is a study design which relates to Latin square design"@en ;
rdfs:subClassOf obo:OBI_0500007 .
obo:STATO_0000123 a rdfs:Class ;
rdfs:label "r2 measure of linkage desequilibrium"@en ;
rdfs:comment "r2 is a correlation coefficient which is computed over the frequency of 2 dichotomous variable and is used as a measure of Linkage Disequilibrium and as input data item to the creation of an LD plot"@en ;
rdfs:subClassOf obo:STATO_0000142 .
obo:PR_000000001 a rdfs:Class ;
rdfs:label "protein" ;
rdfs:comment "An amino acid chain that is produced de novo by ribosome-mediated translation of a genetically-encoded mRNA, and any derivatives thereof." ;
rdfs:subClassOf obo:CHEBI_16670 .
obo:STATO_0000138 a rdfs:Class ;
rdfs:label "2 by 2 contingency table"@en ;
rdfs:comment "a 2x2 contingency table is a contingency table build for 2 dichotomous variables (i.e. 2 categorical variables, each with only 2 possible outcomes). It is the simplest of contingency tables"@en ;
rdfs:subClassOf obo:STATO_0000140 .
obo:STATO_0000439 a rdfs:Class ;
rdfs:label "outlier detection testing objective"@en ;
rdfs:comment "outlier detection testing objective is a statistical objective of a data transformation which aims to test a null hypothesis that an observation is not an outlier."@en ;
rdfs:subClassOf obo:OBI_0000675 .
obo:IAO_0000037 a rdfs:Class ;
rdfs:label "dot plot"@en ;
rdfs:comment "A dot plot is a report graph which is a graphical representation of data where each data point is represented by a single dot placed on coordinates corresponding to data point values in particular dimensions."@en ;
rdfs:subClassOf obo:IAO_0000038 .
obo:STATO_0000627 a rdfs:Class ;
rdfs:label "odds" ;
rdfs:comment """odds correspond to a ratio in which the numerator represents the probability that an event will occur and the denominator represents the probability that an event will not occur.
'Odds' and 'Odds ratio' are different terms. 'Odds' is a ratio of probabilities. 'Odds ratio' is a ratio of two different odds.
Odds are calculated as p / (1-p) where p is the probability of event occurrence. When p = 0, the odds = 0. When p = 1, the odds may be expressed as not calculable or as \"odds against = 0\".
Odds may be expressed as p:(1-p). Odds may be expressed as p:q where q = 1-p. Odds may be expressed as a:b where a and b are multiples of p and (1-p). Examples of different expressions of the same odds include 3:2, 3/2, 0.6:0.4, 0.6/0.4, and 1.5.
Odds may be expressed as \"odds for\" or \"odds in favor\" (e.g. 1:5 for a \"3\" on a 6-sided die) or \"odds against\" (e.g. 5:1 against a \"3\" on a 6-sided die).
The term \"betting odds\" used in gambling that involves financial amounts in the formulation is not an \"Odds\" in the definition of the Scientific Evidence Code System.""" ;
rdfs:subClassOf obo:STATO_0000184 .
obo:STATO_0000719 a rdfs:Class ;
rdfs:label "experimental unit" ;
rdfs:comment """The smallest unit of an experiment to which a treatment is *independently* applied. It is therefore the entity that receives a treatment (or condition) and whose response is assumed to be independent of other units.
The experimental unit defines how many independent pieces of information will be available for inference.
It determines the sample size (n) for hypothesis testing and confidence intervals.
Mistaking smaller components (like individual plants or students) for independent units can lead to pseudoreplication — overestimating the true sample size and producing misleadingly small p-values.""" ;
rdfs:subClassOf obo:BFO_0000004 .
obo:OBI_0000274 a rdfs:Class ;
rdfs:label "adding a material entity into a target"@en ;
rdfs:comment "is a process with the objective to place a material entity bearing the 'material to be added role' into a material bearing the 'target of material addition role'."@en ;
rdfs:subClassOf obo:OBI_0000652 .
obo:STATO_0000218 a rdfs:Class ;
rdfs:label "model fitting"@en ;
rdfs:comment "Model fitting is a data transformation process which evaluates if a model appropriately represents a dataset. A model fitting process tests the goodness of fit of the model to the data"@en ;
rdfs:subClassOf obo:OBI_0200000 .
obo:OBI_0000671 a rdfs:Class ;
rdfs:label "sample from organism" ;
rdfs:comment "a material obtained from an organism in order to be a representative of the whole" ;
rdfs:subClassOf obo:OBI_0000747 , obo:OBI_0001479 .
obo:STATO_0000296 a rdfs:Class ;
rdfs:label "absence of enrichment hypothesis"@en ;
rdfs:comment "absence of depletion difference hypothesis is a hypothesis which assumes that the representation of an element significantly greater than a threshold does not exist."@en ;
rdfs:subClassOf obo:STATO_0000295 .
obo:STATO_0000334 a rdfs:Class ;
rdfs:label "mixture distribution"@en ;
rdfs:comment "Mixture distribution is the probability distribution of a random variable that is derived from a collection of other random variables as follows: first, a random variable is selected by chance from the collection according to given probabilities of selection, and then the value of the selected random variable is realized." ;
rdfs:subClassOf obo:STATO_0000225 .
obo:OBI_0000185 a rdfs:Class ;
rdfs:label "imaging assay"@en ;
rdfs:comment "An imaging assay is an assay to produce a picture of an entity. definition_source: OBI."@en ;
rdfs:subClassOf obo:OBI_0000070 .
obo:STATO_0000491 a rdfs:Class ;
rdfs:label "Conover-Iman test of multiple comparisons using rank sums"@en ;
rdfs:comment """Conover-Iman test for stochastic dominance is a stastical test for multiple group comparisons and reports the results among multiple pairwise comparisons after a Kruskal-Wallis test for stochastic dominance among k groups (Kruskal and Wallis, 1952). The interpretation of stochastic dominance requires an assumption that the CDF of one group does not cross the CDF of the other.
The null hypothesis for each pairwise comparison is that the probability of observing a randomly selected value from the first group that is larger than a randomly selected value from the second group equals one half; this null hypothesis corresponds to that of the Wilcoxon-Mann-Whitney rank-sum test.
Like the rank-sum test, if the data can be assumed to be continuous, and the distributions are assumed identical except for a difference in location, Conover-Iman test may be understood as a test for median difference. conover.test accounts for tied ranks.
The Conover-Iman test is strictly valid if and only if the corresponding Kruskal-Wallis null hypothesis is rejected."""@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:OBI_0200089 , obo:STATO_0000279 .
obo:OBI_0200200 a rdfs:Class ;
rdfs:label "chi square test"@en ;
rdfs:comment "The chi-square test is a data transformation with the objective of statistical hypothesis testing, in which the sampling distribution of the test statistic is a chi-square distribution when the null hypothesis is true, or any in which this is asymptotically true, meaning that the sampling distribution (if the null hypothesis is true) can be made to approximate a chi-square distribution as closely as desired by making the sample size large enough." ;
rdfs:subClassOf obo:OBI_0000673 .
obo:STATO_0000587 a rdfs:Class ;
rdfs:label "percentage of variance" ;
rdfs:comment "the percentage of variance is an output of principal component analysis (PCRA), which is obtained by forming the ratio of an eigen-value divided by the sum of all eigen-values. This produces a \"percentage of variance\" for each eigen-vector." ;
rdfs:subClassOf obo:OBI_0000648 , obo:STATO_0000639 .
obo:STATO_0000428 a rdfs:Class ;
rdfs:label "maximum likelihood estimation"@en ;
rdfs:comment """maximum likelihood estimation (MLE) is a method of estimating the parameters of a statistical model, given observations. MLE attempts to find the parameter values that maximize the likelihood function, given the observations.
The method of maximum likelihood is based on the likelihood function, {\\displaystyle {\\mathcal {L}}(\\theta \\,;x)} {\\displaystyle {\\mathcal {L}}(\\theta \\,;x)}. We are given a statistical model, i.e. a family of distributions {\\displaystyle \\{f(\\cdot \\,;\\theta )\\mid \\theta \\in \\Theta \\}} {\\displaystyle \\{f(\\cdot \\,;\\theta )\\mid \\theta \\in \\Theta \\}}, where {\\displaystyle \\theta } \\theta denotes the (possibly multi-dimensional) parameter for the model. The method of maximum likelihood finds the values of the model parameter, {\\displaystyle \\theta } \\theta , that maximize the likelihood function, {\\displaystyle {\\mathcal {L}}(\\theta \\,;x)} {\\displaystyle {\\mathcal {L}}(\\theta \\,;x)}. I"""@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000119 .
obo:STATO_0000615 a rdfs:Class ;
rdfs:label "relative difference"@en ;
rdfs:comment """A statistic that is a difference between 1 and a ratio of the two quantities being compared.
Relative Difference = 1 - ( a / b ). Because 1 - ( a / b ) is not equal to 1 - ( b / a ), Relative Difference may be expressed as \"Relative Difference with respect to b\" when referring to 1 - ( a / b ).
The relative difference can also be defined as a statistic that is a ratio of the absolute difference (of the two quantities being compared) to the reference value (one of the quantities being compared). Relative Difference = ( b - a ) / ( b ) where b is the reference value and this may also be called \"Relative Difference with respect to b\"."""@en ;
rdfs:subClassOf obo:STATO_0000613 .
obo:CHEBI_16670 a rdfs:Class ;
rdfs:label "peptide" ;
rdfs:comment "Amide derived from two or more amino carboxylic acid molecules (the same or different) by formation of a covalent bond from the carbonyl carbon of one to the nitrogen atom of another with formal loss of water. The term is usually applied to structures formed from alpha-amino acids, but it includes those derived from any amino carboxylic acid. X = OH, OR, NH2, NHR, etc." ;
rdfs:subClassOf obo:CHEBI_33839 .
obo:STATO_0000518 a rdfs:Class ;
rdfs:label "data imputation" ;
rdfs:comment "Data imputation is a data transformation process whereby missing data is replaced with an estimated value for the missing element. The substituted values are intended to create a data record that does not fail edits. Various methods may be used to produce these substituted values." ;
rdfs:subClassOf obo:OBI_0200000 .
obo:STATO_0000096 a rdfs:Class ;
rdfs:label "population stratification prior to sampling" ;
rdfs:comment "stratification is a planned process which executes a stratification rule using as input a population and assign it member to mutually exclusive subpopulation based on the values defined by the stratification rule"@en ;
rdfs:subClassOf obo:OBI_0000094 .
obo:STATO_0000144 a rdfs:Class ;
rdfs:label "model parameter estimate"@en ;
rdfs:comment "a model parameter estimate is a data item which results from a model parameter estimation process and which provides a numerical value about a model parameter."@en ;
rdfs:subClassOf obo:STATO_0000471 .
obo:STATO_0000094 a rdfs:Class ;
rdfs:label "Kruskal Wallis test"@en ;
rdfs:comment """The Kruskal–Wallis test is a null hypothesis statistical testing objective which allows multiple (n>=2) groups (or conditions or treatments) to be compared, without making the assumption that values are normally distributed. The Kruskal–Wallis test is the non-parametric equivalent of the independent samples ANOVA.
The Kruskal–Wallis test is most commonly used when there is one nominal variable and one measurement variable, and the measurement variable does not meet the normality assumption of an anova."""@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000198 .
obo:STATO_0000576 a rdfs:Class ;
rdfs:label "SIMPLS"@en ;
rdfs:comment """A novel algorithm for partial least squares (PLS) regression, SIMPLS, is proposed which calculates the PLS factors directly as linear combinations of the original variables. The PLS factors are determined such as to maximize a covariance criterion, while obeying certain orthogonality and normalization restrictions. This approach follows that of other traditional multivariate methods. The construction of deflated data matrices as in the nonlinear iterative partial least squares (NIPALS)-PLS algorithm is avoided. For univariate y SIMPLS is equivalent to PLS1 and closely related to existing bidiagonalization algorithms. This follows from an analysis of PLS1 regression in terms of Krylov sequences. For multivariate Y there is a slight difference between the SIMPLS approach and NIPALS-PLS2. In practice the SIMPLS algorithm appears to be fast and easy to interpret as it does not involve a breakdown of the data sets.
The acronym SIMPLS comes from 'straightforward implementation of a statistically inspired modification of the PLS method'"""@en ;
rdfs:subClassOf obo:OBI_0200000 .
obo:STATO_0000417 a rdfs:Class ;
rdfs:label "pretest probability"@en ;
rdfs:comment "The probability of a patient having the target disorder before a diagnostic test result is known"@en ;
rdfs:subClassOf obo:STATO_0000184 .
obo:STATO_0000168 a rdfs:Class ;
rdfs:label "real time quantitative pcr plot"@en ;
rdfs:comment "a real time quantitative pcr plot is a line graph which plots the signal fluorescence intensity as a function of the number of PCR cycle"@en ;
rdfs:subClassOf obo:IAO_0000573 .
obo:STATO_0000513 a rdfs:Class ;
rdfs:label "voluntary sampling"@en ;
rdfs:comment "The voluntary sampling method is a type of non-probability sampling. A voluntary sample is made up of people who self-select into the survey. Often, these subjects have a strong interest in the main topic of the survey. Volunteers may be invited through advertisements on Social Media Sites"@en ;
rdfs:subClassOf obo:STATO_0000502 .
obo:STATO_0000149 a rdfs:Class ;
rdfs:label "binomial logistic regression for analysis of dichotomous dependent variable"@en ;
rdfs:comment "binomial logistic regression model is a model which attempts to explain data distribution associated with *dichotomous* response/dependent variable in terms of values assumed by the independent variable uses a function of predictor/independent variable(s): the function used in this instance of regression modeling is logistic function."@en ;
rdfs:subClassOf obo:OBI_0200102 .
obo:STATO_0000228 a rdfs:Class ;
rdfs:label "ordinal variable"@en ;
rdfs:comment "ordinal variable is a categorical variable where the discrete possible values are ordered or correspond to an implicit ranking"@en ;
rdfs:subClassOf obo:STATO_0000252 .
obo:STATO_0000112 a rdfs:Class ;
rdfs:label "Funnel plot"@en ;
rdfs:comment """a Funnel plot is a scatter plot of treatment effect versus a measure of study size and aims to provide a visual aid to detecting bias or systematic heterogeneity. A symmetric inverted funnel shape arises from a ‘well-behaved’ data set, in which publication bias is unlikely. An asymmetric funnel indicates a relationship between treatment effect and study size.
Known caveats: If high precision studies really are different from low precision studies with respect to effect size (e.g., due to different populations examined) a funnel plot may give a wrong impression of publication bias. The appearance of the funnel plot can change quite dramatically depending on the scale on the y-axis — whether it is the inverse square error or the trial size.
Funnel plot was introduced by Light and Palmer in 1984."""@en ;
rdfs:subClassOf obo:IAO_0000184 .
obo:STATO_0000682 a rdfs:Class ;
rdfs:label "kappa"@en ;
rdfs:comment "A measure of agreement among categorical assessments, corrected for chance agreement."@en ;
rdfs:subClassOf obo:STATO_0000623 .
obo:STATO_0000056 a rdfs:Class ;
rdfs:label "absence of association hypothesis"@en ;
rdfs:comment "a null hypothesis which states that no linkage exists between 2 categorical variables"@en ;
rdfs:subClassOf obo:STATO_0000065 .
obo:STATO_0000487 a rdfs:Class ;
rdfs:label "additive genetic inheritance model"@en ;
rdfs:comment "an additive genetic model is a data item which refers to the contributions to the final phenotype from more than one gene, or from alleles of a single gene (in heterozygotes), that combine in such a way that the sum of their effects in unison is equal to the sum of their effects individually."@en ;
rdfs:subClassOf obo:STATO_0000534 .
obo:OBI_0400065 a rdfs:Class ;
rdfs:label "light source"@en ;
rdfs:comment "A light source is an optical subsystem that provides light for use in a distant area using a delivery system (e.g., fiber optics). Light sources may include one of a variety of lamps (e.g., xenon, halogen, mercury). Most light sources are operated from line power, but some may be powered from batteries. They are mostly used in endoscopic, microscopic, and other examination and/or in surgical procedures. The light source is part of the optical subsystem. In a flow cytometer the light source directs high intensity light at particles at the interrogation point. The light source in a flow cytometer is usually a laser."@en ;
rdfs:subClassOf obo:OBI_0001032 .
obo:OBI_0200111 a rdfs:Class ;
rdfs:label "data visualization"@en ;
rdfs:comment "An planned process that creates images, diagrams or animations from the input data."@en ;
rdfs:subClassOf obo:OBI_0000011 .
obo:OBI_0200083 a rdfs:Class ;
rdfs:label "survival analysis objective"@en ;
rdfs:comment "A data transformation objective which has the data transformation aims to model time to event data (where events are e.g. death and or disease recurrence); the purpose of survival analysis is to model the underlying distribution of event times and to assess the dependence of the event time on other explanatory variables" ;
rdfs:subClassOf obo:OBI_0200166 .
obo:STATO_0000310 a rdfs:Class ;
rdfs:label "Barnard's test"@en ;
rdfs:comment "Barnard's test is an exact statistical test used to determine if there are non-random associations between two categorical variables. It was developed in 1949 by Barnard and is a test which is, most times, more powerful that the Fisher exact test"@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000027 .
obo:BFO_0000019 a rdfs:Class ;
rdfs:label "quality"@en ;
rdfs:subClassOf obo:BFO_0000020 .
obo:STATO_0000133 a rdfs:Class ;
rdfs:label "post-hoc analysis"@en ;
rdfs:comment "A post-hoc analysis is a statistical test carried out following an analysis of variance which ruled out the null hypothesis of absence of difference between group which allows identifying which groups differ."@en ;
rdfs:subClassOf obo:STATO_0000279 .
obo:STATO_0000592 a rdfs:Class ;
rdfs:label "Rand index"@en ;
rdfs:comment "the Rand index is a ratio, related to the notion of accuracy (STATO_0000415), which is used to compare the similarity of two clustering outcomes."@en ;
rdfs:subClassOf obo:STATO_0000184 .
obo:STATO_0000246 a rdfs:Class ;
rdfs:label "Woolf's test"@en ;
rdfs:comment "Woolf's test is a statistical test which evaluates the null hypothesis that odds ratio are the same accross all strata of population under investigation"@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000247 , obo:STATO_0000697 .
obo:STATO_0000459 a rdfs:Class ;
rdfs:label "group sequential design"@en ;
rdfs:comment "group sequential design is a study design used in clinical trial settings in which interim analyses of the data are conducted after groups of patients are recruited. After each interim analysis, the trial may stop early if the evidence so far shows the new treatment is particularly effective or ineffective. Such designs are ethical and cost-effective, and so are of great interest in practice."@en ;
rdfs:subClassOf obo:OBI_0500000 .
obo:STATO_0000616 a rdfs:Class ;
rdfs:label "count difference"@en ;
rdfs:comment """A statistic that is a subtraction of one count from another.
The term Count Difference is used to specify the Absolute Difference is with respect to a count or number of items (such as number of events, platelet counts, sample size e.g. number of people in the group) to distinguish from differences in other types of statistics (mean difference, median difference, risk difference, etc.)"""@en ;
rdfs:subClassOf obo:STATO_0000614 .
obo:OBI_0000434 a rdfs:Class ;
rdfs:label "adding material objective"@en ;
rdfs:comment "is the specification of an objective to add a material into a target material. The adding is asymmetric in the sense that the target material largely retains its identity"@en ;
rdfs:subClassOf obo:OBI_0000686 .
obo:OBI_0000115 a rdfs:Class ;
rdfs:label "intervention design"@en ;
rdfs:comment "An intervention design is a study design in which a controlled process applied to the subjects (the intervention) serves as the independent variable manipulated by the experimentalist. The treatment (perturbation or intervention) defined can be defined as a combination of values taken by independent variable manipulated by the experimentalists are applied to the recruited subjects assigned (possibly by applying specific methods) to treatment groups. The specificity of intervention design is the fact that independent variables are being manipulated and a response of the biological system is evaluated via response variables as monitored by possibly a series of assays."@en ;
rdfs:subClassOf obo:OBI_0500000 .
obo:STATO_0000346 a rdfs:Class ;
rdfs:label "covariance structure"@en ;
rdfs:comment "a covariance structure is a data item which is part of a regression model and which indicates a pattern in the covariance matrix. The nature of covariance structure is specified before the regression analysis and various covariance structure may be tested and evaluated using information criteria to help choose the most suiteable model"@en ;
rdfs:subClassOf obo:IAO_0000027 , obo:STATO_0000107 .
obo:UO_0000001 a rdfs:Class ;
rdfs:label "length unit" ;
rdfs:comment "A unit which is a standard measure of the distance between two points." ;
rdfs:subClassOf obo:IAO_0000003 .
obo:STATO_0000252 a rdfs:Class ;
rdfs:label "categorical variable"@en ;
rdfs:comment "a categorical variable is a variable which that can only assume a finite number of value and cast observation in a small number of categories"@en ;
rdfs:subClassOf obo:STATO_0000258 .
obo:STATO_0000267 a rdfs:Class ;
rdfs:label "grouped bar chart" ;
rdfs:comment "grouped bar chart is a kind of bar chart which juxtaposes the discrete values for each of the possible value of a given categorical variable, thus providing within group comparison. Grouped bar charts are good for comparing between each element in the categories, and comparing elements across categories. However, the grouping can make it harder to tell the difference between the total of each group."@en ;
rdfs:subClassOf obo:STATO_0000166 .
obo:OBI_0200051 a rdfs:Class ;
rdfs:label "principal components analysis dimensionality reduction"@en ;
rdfs:comment "A principal components analysis dimensionality reduction is a dimensionality reduction achieved by applying principal components analysis and by keeping low-order principal components and excluding higher-order ones."@en ;
rdfs:subClassOf obo:OBI_0200050 .
obo:OBI_0001834 a rdfs:Class ;
rdfs:label "drawing a conclusion" ;
rdfs:comment "A planned process in which new information is inferred from existing information." ;
rdfs:subClassOf obo:OBI_0000011 .
obo:STATO_0000157 a rdfs:Class ;
rdfs:label "Least significance different test"@en ;
rdfs:comment "the LSD test is a statistical test for multiple comparisons of treatments by means of least significant difference following an ANOVA analysis" ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000133 .
obo:OBI_1110108 a rdfs:Class ;
rdfs:label "material to be added" ;
rdfs:comment "a material that is added to another one in a material combination process" ;
rdfs:subClassOf obo:BFO_0000040 .
obo:STATO_0000173 a rdfs:Class ;
rdfs:label "homogeneity test objective"@en ;
rdfs:comment """homogeneity testing objective is the objective of a data transformation to test a null hypothesis that two or more sub-groups of a population share the same distribution of a single categorical variable.
For example, do people of different countries have the same proportion of smokers to non-smokers"""@en ;
rdfs:subClassOf obo:OBI_0000675 .
obo:IAO_0000582 a rdfs:Class ;
rdfs:label "time stamped measurement datum"@en ;
rdfs:subClassOf obo:IAO_0000109 .
obo:STATO_0000109 a rdfs:Class ;
rdfs:label "multinomial logistic regression for analysis of dichotomous dependent variable"@en ;
rdfs:comment "multinomial logistic regression model is a model which attempts to explain data distribution associated with *polychotomous* response/dependent variable in terms of values assumed by the independent variable uses a function of predictor/independent variable(s): the function used in this instance of regression modeling is logistic function."@en ;
rdfs:subClassOf obo:OBI_0200102 .
obo:STATO_0000197 a rdfs:Class ;
rdfs:label "genomic coordinate system"@en ;
rdfs:comment "a genomic coordinate system is a coordinate system to describe position of sequence on a genomic scaffold (assembly of chromosome, contig....)"@en ;
rdfs:subClassOf obo:STATO_0000010 .
obo:STATO_0000397 a rdfs:Class ;
rdfs:label "harmonic mean"@en ;
rdfs:comment """The harmonic mean is a kind of mean which is calculated by dividing the total number of observations by the reciprocal of each number in a series.
Harmonic Mean = N/(1/a1+1/a2+1/a3+1/a4+.......+1/aN)
where a(i)= Individual score and N = Sample size (Number of scores)"""@en ;
rdfs:subClassOf obo:STATO_0000029 .
obo:STATO_0000464 a rdfs:Class ;
rdfs:label "linear mixed model"@en ;
rdfs:comment """A lnear mixed model is a mixed model containing both fixed effects and random effects and in which factors and covariates are assumed to have a linear relationship to the dependent variable. These models are useful in a wide variety of disciplines in the physical, biological and social sciences. They are particularly useful in settings where repeated measurements are made on the same statistical units (longitudinal study), or where measurements are made on clusters of related statistical units. Because of their advantage in dealing with missing values, mixed effects models are often preferred over more traditional approaches such as repeated measures ANOVA.
Fixed-effects factors are generally considered to be the variables whose values of interest are all represented in the data file.
Random-effects factors are variables whose values correspond to unwanted variation. They are useful when trying to understand variability in the dependent variable which was not anticipated and exceeds what was expected.
Linear mixed models also allow to specify specific interactions between factors, and allow the evaluation of the various linear effect that a particular combination of factor levels may have on a response variable.
Finally, linear mixed models allow to specify variance components in order to describe the relation between various random effects levels."""@en ;
rdfs:subClassOf obo:STATO_0000189 .
obo:STATO_0000279 a rdfs:Class ;
rdfs:label "between group comparison statistical test" ;
rdfs:comment "between group comparison statistical test is a statistical test which aims to detect difference between the means computing for each of the study group populations"@en ;
rdfs:subClassOf obo:OBI_0000673 .
obo:STATO_0000135 a rdfs:Class ;
rdfs:label "strictly standardized mean difference"@en ;
rdfs:comment """strictly standardized mean difference (SSMS) is a standardized mean difference which corresponds to the ratio of mean to the standard deviation of the difference between two groups.
SSMD directly measures the magnitude of difference between two groups.
SSMD is widely used in High Content Screen for hit selection and quality control.
When the data is preprocessed using log-transformation as normally done in HTS experiments, SSMD is the mean of log fold change divided by the standard deviation of log fold change with respect to a negative reference.
In other words, SSMD is the average fold change (on the log scale) penalized by the variability of fold change (on the log scale).
For quality control, one index for the quality of an HTS assay is the magnitude of difference between a positive control and a negative reference in an assay plate. For hit selection, the size of effects of a compound (i.e., a small molecule or an siRNA) is represented by the magnitude of difference between the compound and a negative reference. SSMD directly measures the magnitude of difference between two groups. Therefore, SSMD can be used for both quality control and hit selection in HTS experiments."""@en ;
rdfs:subClassOf obo:STATO_0000100 .
obo:OBI_0000411 a rdfs:Class ;
rdfs:label "cloning vector role"@en ;
rdfs:comment "A material to be added role played by a small, self-replicating DNA or RNA molecule - usually a plasmid or chromosome - and realized in a process whereby foreign DNA or RNA is inserted into the vector during the process of cloning."@en ;
rdfs:subClassOf obo:OBI_0000319 .
obo:RO_0000052 a rdf:Property ;
rdfs:label "inheres in"@en ;
rdfs:comment "a relation between a specifically dependent continuant (the dependent) and an independent continuant (the bearer), in which the dependent specifically depends on the bearer for its existence"@en ;
rdfs:range .
obo:STATO_0000234 a rdfs:Class ;
rdfs:label "residual"@en ;
rdfs:comment "a residual is a data item which is the output of an error estimate or model fitting process and which is an observable estimate of the unobservable error"@en ;
rdfs:subClassOf obo:STATO_0000039 .
obo:STATO_0000330 a rdfs:Class ;
rdfs:label "empirical distribution"@en ;
rdfs:comment "Probability distribution estimated empirically from all acquired data"@en ;
rdfs:subClassOf obo:STATO_0000225 .
obo:STATO_0000126 a rdfs:Class ;
rdfs:label "volcano plot"@en ;
rdfs:comment """volcano plot is a kind of scatter plot which graphs the negative log of the p-value (significance) on the y-axis versus log2 of fold-change between 2 conditions on the x-axis.
It is a popular method for visualizing differential occurence of variables between 2 conditions."""@en ;
rdfs:subClassOf obo:IAO_0000184 .
obo:STATO_0000305 a rdfs:Class ;
rdfs:label "Helmert contrast"@en ;
rdfs:comment "A Helmert contrast is a contrast in which the coefficients for the Helmert regressors compare each level with the average of the “preceding” ones"@en ;
rdfs:subClassOf obo:STATO_0000290 .
obo:STATO_0000274 a rdfs:Class ;
rdfs:label "receiver operational characteristics curve"@en ;
rdfs:comment "receiver operational characteristics curve is a graphical plot which illustrates the performance of a binary classifier system as its discrimination threshold (aka cut-off point) is varied by plotting sensitivity vs (1 − specificity)"@en ;
rdfs:subClassOf obo:IAO_0000038 .
obo:STATO_0000619 a rdfs:Class ;
rdfs:label "negative predictive value" ;
rdfs:comment "A proportion in which the numerator represents the correctly non-detected items within the denominator that represents all items not detected." ;
rdfs:subClassOf obo:STATO_0000607 .
obo:STATO_0000577 a rdfs:Class ;
rdfs:label "PLS1" ;
rdfs:comment "a partial least square regression applied when there is only one variable in Y (the matrix of response variables), or it is desirable to model and optimize separately the performance of each of the variables in Y. This case is usually referred to as PLS1 regression (J = 1)." ;
rdfs:subClassOf obo:STATO_0000571 .
obo:STATO_0000450 a rdfs:Class ;
rdfs:label "Wilk's Lambda"@en ;
rdfs:comment "\"Wilks' lambda is a test statistic used in multivariate analysis of variance (MANOVA) to test whether there are differences between the means of identified groups of subjects on a combination of dependent variables.\""@en ;
rdfs:subClassOf obo:STATO_0000039 .
obo:NCBITaxon_32523 a rdfs:Class ;
rdfs:label "Tetrapoda" ;
rdfs:subClassOf obo:NCBITaxon_117571 .
obo:STATO_0000095 a rdfs:Class ;
rdfs:label "paired t-test"@en ;
rdfs:comment "paired t-test is a statistical test which is specifically designed to analysis differences between paired observations in the case of studies realizing repeated measures design with only 2 repeated measurements per subject (before and after treatment for example)"@en ;
rdfs:subClassOf obo:OBI_0000739 , obo:OBI_0200000 , obo:STATO_0000202 .
obo:STATO_0000498 a rdfs:Class ;
rdfs:label "numerator degrees of freedom" ;
rdfs:comment "The degree of freedom numerator is the number of degrees of freedom that the estimate of variance used in the numerator is based on. It is one of the parameters for the F-distribution used to compute probabilities in analysis of variance." ;
rdfs:subClassOf obo:STATO_0000069 .
obo:STATO_0000285 a rdfs:Class ;
rdfs:label "hypergeometric test"@en ;
rdfs:comment "hypergeometric test is a null hypothesis test which evaluates if a random variable follows a hypergeometric distribution. It is a test of goodness of fit to that distribution. The test is suited for situation aimed at assessing cases of sampling from a finite set without replacements. For instance, testing for enrichment or depletion of elements (e.g GO categories, genes)"@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000191 , obo:STATO_0000287 .
obo:STATO_0000245 a rdfs:Class ;
rdfs:label "relative risk" ;
rdfs:comment "Relative risk is a measurement datum which denotes the risk of an 'event' relative to an 'exposure'. Relative risk is calculated by forming the ratio of the probability of the event occurring in the exposed group versus the probability of this event occurring in the non-exposed group." ;
rdfs:subClassOf obo:STATO_0000085 , obo:STATO_0000620 .
obo:STATO_0000166 a rdfs:Class ;
rdfs:label "bar chart"@en ;
rdfs:comment "the bart chart is a graph resulting from plotting rectangular bars with lengths proportional to the values that they represent." ;
rdfs:subClassOf obo:IAO_0000038 .
obo:STATO_0000534 a rdfs:Class ;
rdfs:label "genetic inheritance model"@en ;
rdfs:comment "genetic inheritance model is a data item defining the assumption used by a breeding value estimation method to consider when running the calculations." ;
rdfs:subClassOf obo:STATO_0000107 .
obo:OBI_0302903 a rdfs:Class ;
rdfs:label "nucleic acid hybridization"@en ;
rdfs:comment "a planned process by which totally or partially complementary, single-stranded nucleic acids are combined into a single molecule called heteroduplex or homoduplex to an extent depending on the amount of complementarity."@en ;
rdfs:subClassOf obo:OBI_0000094 .
obo:STATO_0000040 a rdfs:Class ;
rdfs:label "MA plot"@en ;
rdfs:comment "an MA plot is a scatter plot of the log intensity ratios M = log_2(T/R) versus the average log intensities A = log_2(T*T)/2, where T and R represent the signal intensities in the test and reference channels respectively."@en ;
rdfs:subClassOf obo:IAO_0000184 .
obo:OBI_0200201 a rdfs:Class ;
rdfs:label "ANOVA"@en ;
rdfs:comment "ANOVA or analysis of variance is a data transformation in which a statistical test of whether the means of several groups are all equal." ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000279 .
obo:STATO_0000079 a rdfs:Class ;
rdfs:label "Barlett's test"@en ;
rdfs:comment """Bartlett's test (see Snedecor and Cochran, 1989) is used to test if k samples are from populations with equal variances. Equal variances across samples is called homoscedasticity or homogeneity of variances. Some statistical tests, for example the analysis of variance, assume that variances are equal across groups or samples. The Bartlett test can be used to verify that assumption.
Bartlett's test is sensitive to departures from normality. That is, if the samples come from non-normal distributions, then Bartlett's test may simply be testing for non-normality. Levene's test and the Brown–Forsythe test are alternatives to the Bartlett test that are less sensitive to departures from normality."""@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000137 , obo:STATO_0000191 .
obo:STATO_0000010 a rdfs:Class ;
rdfs:label "coordinate system"@en ;
rdfs:comment "In geometry, a coordinate system is a system which uses one or more numbers, or coordinates, to uniquely determine the position of a point or other geometric element on a manifold such as Euclidean space." ;
rdfs:subClassOf obo:IAO_0000030 .
obo:STATO_0000588 a rdfs:Class ;
rdfs:label "scaled identity covariance structure" ;
rdfs:comment "the scaled identity covariance structure is a type of covariance structure which has constant variance. The assumption is that there is no correlation between any elements." ;
rdfs:subClassOf obo:STATO_0000346 .
obo:STATO_0000708 a rdfs:Class ;
rdfs:label "Cochran-Armitage Chi-Square Statistic for Trend" ;
rdfs:comment """A chi-square statistic used to test whether a dichotomous variable and an ordinal variable are related.
The statistic is calculated using a weighted sum of the differences between observed and expected frequencies, where the weights are based on the scores assigned to the ordered categories. Mathematically, it's often expressed as:
Z = ∑(wi(Oi-Ei)/sqr( wi^2.Ei(1-Ei))
where wi are the scores, Oi observed frequencies, and Ei expected frequencies.""" ;
rdfs:subClassOf obo:STATO_0000030 .
obo:STATO_0000386 a rdfs:Class ;
rdfs:label "scree plot" ;
rdfs:comment "A scree plot is a graphical display of the variance of each component in the dataset which is used to determine how many components should be retained in order to explain a high percentage of the variation in the data"@en ;
rdfs:subClassOf obo:IAO_0000038 .
obo:STATO_0000660 a rdfs:Class ;
rdfs:label "posterior predictive value"@en ;
rdfs:comment "A hypothesis testing measure that is the predictive probability that a statistic is equal to or more extreme than that observed under the assumptions of the model."@en ;
rdfs:subClassOf obo:OBI_0000071 .
obo:STATO_0000316 a rdfs:Class ;
rdfs:label "root-mean-square standardized effect"@en ;
rdfs:comment "root-mean-square standardized effect is a statistic which denotes effect size in the context of analysis of variance and corresponds to the square root of the arithmetic average of p standardized effects (effects normalized to be expressed in standard deviation units)."@en ;
rdfs:subClassOf obo:STATO_0000039 , obo:STATO_0000085 .
obo:OBI_0001265 a rdfs:Class ;
rdfs:label "FWER adjusted p-value"@en ;
rdfs:comment "A quantitative confidence value resulting from a multiple testing error correction method which adjusts the p-value used as input to control for Type I error in the context of multiple pairwise tests"@en ;
rdfs:subClassOf obo:OBI_0000071 , obo:OBI_0000662 .
obo:STATO_0000647 a rdfs:Class ;
rdfs:label "standard error of the proportion"@en ;
rdfs:comment """A measure of dispersion applied to proportions across hypothetical repeated random samples.
A standard error is used to quantify the uncertainty around a statistical estimate due to random sampling error."""@en ;
rdfs:seeAlso ;
rdfs:subClassOf obo:STATO_0000562 .
obo:STATO_0000021 a rdfs:Class ;
rdfs:label "90% confidence interval"@en ;
rdfs:comment "a confidence interval which covers 90% of the sampling distribution, meaning that there is a 90% risk of false positive (type I error)"@en ;
rdfs:subClassOf obo:STATO_0000196 .
obo:OBI_0000686 a rdfs:Class ;
rdfs:label "material combination objective" ;
rdfs:comment "is an objective to obtain an output material that contains several input materials." ;
rdfs:subClassOf obo:OBI_0000456 .
obo:OBI_0302900 a rdfs:Class ;
rdfs:label "group randomization"@en ;
rdfs:comment "A group assignment which relies on chance to assign materials to a group of materials in order to avoid bias in experimental set up."@en ;
rdfs:subClassOf obo:OBI_0600015 .
obo:IAO_0000144 a rdfs:Class ;
rdfs:label "conclusion textual entity"@en ;
rdfs:comment "A textual entity that expresses the results of reasoning about a problem, for instance as typically found towards the end of scientific papers."@en ;
rdfs:subClassOf obo:IAO_0000300 , obo:OBI_0001909 .
obo:STATO_0000406 a rdfs:Class ;
rdfs:label "Yuen t-Test with trimmed means"@en ;
rdfs:comment """The Yuen's t-test is a two sample t-test with populations of unequal variance which provides a more robust t-test procedure under normal distribution and long tailed distributions.
The test computes a t statistics not using 'arithmetic means' but using 'trimmed means' instead as well as winsorized variances."""@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000279 .
obo:CHEBI_33696 a rdfs:Class ;
rdfs:label "nucleic acid" ;
rdfs:comment "A macromolecule made up of nucleotide units and hydrolysable into certain pyrimidine or purine bases (usually adenine, cytosine, guanine, thymine, uracil), D-ribose or 2-deoxy-D-ribose and phosphoric acid." ;
rdfs:subClassOf obo:CHEBI_33839 .
obo:OBI_0000737 a rdfs:Class ;
rdfs:label "cloning vector" ;
rdfs:comment "A cloning vector is an engineered material that is used as an input material for a recombinant vector cloning process to carry inserted nucleic acids. It contains an origin of replication for a specific destination host organism, encodes for a selectable gene product and contains a cloning site." ;
rdfs:subClassOf obo:BFO_0000040 , obo:OBI_0000047 , obo:OBI_1110108 .
obo:STATO_0000106 a rdfs:Class ;
rdfs:label "probit regression for analysis of polychotomous dependent variable"@en ;
rdfs:comment "probit regression model is a model which attempts to explain data distribution associated with *dichotomous* response/dependent variable in terms of values assumed by the independent variable uses a function of predictor/independent variable(s): the function used in this instance of regression modeling is the probit function aka the quantile function, i.e., the inverse cumulative distribution function (CDF), associated with the standard normal distribution."@en ;
rdfs:subClassOf obo:OBI_0200102 .
obo:STATO_0000137 a rdfs:Class ;
rdfs:label "homoskedasticity test"@en ;
rdfs:comment "an homoskedasticity test is a statistical test aiming at evaluate if the variances from several random samples are similar"@en ;
rdfs:subClassOf obo:OBI_0000673 .
obo:STATO_0000327 a rdfs:Class ;
rdfs:label "Bayesian information criterion"@en ;
rdfs:comment """Bayesian information criterion or Schwartz's Bayesian information criterion is a criterion for model selection among a finite set of models. It is based, in part, on the likelihood function and it is closely related to the Akaike information criterion (AIC).
Given any two estimated models, the model with the lower value of BIC is the one to be preferred. The BIC is an increasing function of sigma_e^2 and an increasing function of k. That is, unexplained variation in the dependent variable and the number of explanatory variables increase the value of BIC. Hence, lower BIC implies either fewer explanatory variables, better fit, or both."""@en ;
rdfs:subClassOf obo:IAO_0000109 .
obo:STATO_0000188 a rdfs:Class ;
rdfs:label "average log signal intensity"@en ;
rdfs:comment "average log signal intensity is a data time which corresponds to the sum of 2 distinct logarithm base 2 transformed signal intensity, each corresponding to a distinct condition of signal acquisition, divided by 2."@en ;
rdfs:subClassOf obo:IAO_0000109 , obo:OBI_0000451 .
obo:STATO_0000445 a rdfs:Class ;
rdfs:label "split split plot design"@en ;
rdfs:comment "a split split plot design is a study design where restricted randomization affect 2 study factors (and not 1 as in split-plot design). Such design is only possible if at least 3 independent variables are present."@en ;
rdfs:subClassOf obo:OBI_0500000 , obo:STATO_0000444 .
obo:OBI_0001137 a rdfs:Class ;
rdfs:label "protein sequencer" ;
rdfs:comment "An device that is used to determine the order of amino acids in protein sequences." ;
rdfs:subClassOf obo:OBI_0000832 .
obo:STATO_0000353 a rdfs:Class ;
rdfs:label "spatial exponential anisotropic covariance structure"@en ;
rdfs:comment "spatial exponential anisotropic covariance structure is a type of covariance structure characterized by its anisotropy, i.e., the variation of properties can be different in directions x and y, which is this case give exponential features."@en ;
rdfs:subClassOf obo:STATO_0000346 .
obo:STATO_0000685 a rdfs:Class ;
rdfs:label "mesure of calibration"@en ;
rdfs:comment "A measure of association between a variable representing known or true values and a variable representing measured or predicted values."@en ;
rdfs:subClassOf obo:STATO_0000039 .
obo:STATO_0000434 a rdfs:Class ;
rdfs:label "Cochran's q test for heterogeneity"@en ;
rdfs:comment """Cochran's Q test is a statistical test used for unreplicated randomized block design experiments with a binary response variable and paired data.
In the analysis of two-way randomized block designs where the response variable can take only two possible outcomes (coded as 0 and 1), Cochran's Q test is a non-parametric statistical test to verify whether k treatments have identical effects."""@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000027 .
obo:NCBITaxon_2759 a rdfs:Class ;
rdfs:label "Eukaryota" ;
rdfs:subClassOf obo:OBI_0100026 .
obo:STATO_0000734 a rdfs:Class ;
rdfs:label "statistically significant"@en ;
rdfs:comment "a conclusion based on the outcome of statistical test that means the result of a hypothesis test supports rejection of the null hypothesis at the specified alpha level." ;
rdfs:subClassOf obo:OBI_0001909 .
obo:STATO_0000674 a rdfs:Class ;
rdfs:label "frequency"@en ;
rdfs:comment "A ratio in which the numerator represents a count and the denominator represents a count (without involving an interval of time)."@en ;
rdfs:subClassOf obo:STATO_0000184 .
obo:STATO_0000335 a rdfs:Class ;
rdfs:label "survival distribution"@en ;
rdfs:comment "Probability distribution estimated empirically from a censored lifetime data"@en ;
rdfs:subClassOf obo:STATO_0000330 .
obo:OBI_0600015 a rdfs:Class ;
rdfs:label "group assignment"@en ;
rdfs:comment "group assignment is a process which has an organism as specified input and during which a role is assigned"@en ;
rdfs:subClassOf obo:OBI_0000011 .
obo:STATO_0000177 a rdfs:Class ;
rdfs:label "beta distribution" ;
rdfs:comment "the beta distribution is a continuous probability distributions defined on the interval [0, 1] parametrized by two positive shape parameters, denoted by α and β, that appear as exponents of the random variable and control the shape of the distribution"@en ;
rdfs:subClassOf obo:STATO_0000067 .
obo:CHEBI_33839 a rdfs:Class ;
rdfs:label "macromolecule" ;
rdfs:comment "A macromolecule is a molecule of high relative molecular mass, the structure of which essentially comprises the multiple repetition of units derived, actually or conceptually, from molecules of low relative molecular mass." ;
rdfs:subClassOf obo:CHEBI_23367 .
obo:STATO_0000503 a rdfs:Class ;
rdfs:label "simple random sampling"@en ;
rdfs:comment "Simple random sampling is a statistical sampling process which creates a sample of a size n entirely by chance. In such process, each unit has the same probability of being selected. Depending on the size of the population being sampled, the sampling process may be done with or without replacement"@en ;
rdfs:subClassOf obo:STATO_0000502 .
obo:STATO_0000297 a rdfs:Class ;
rdfs:label "absence of depletion hypothesis"@en ;
rdfs:comment "absence of depletion difference hypothesis is a hypothesis which assumes that the representation of an element significantly less than a threshold does not exist."@en ;
rdfs:subClassOf obo:STATO_0000294 .
obo:OBI_0400148 a rdfs:Class ;
rdfs:label "DNA microarray"@en ;
rdfs:comment "A DNA-microarray is a microarray that is used as a physical 2D immobilisation matrix for DNA sequences. DNA microarray-bound DNA fragments are used as targets for a hybridising probed sample."@en ;
rdfs:subClassOf obo:OBI_0400147 .
obo:OBI_0000066 a rdfs:Class ;
rdfs:label "investigation"@en ;
rdfs:comment "a planned process that consists of parts: planning, study design execution, documentation and which produce conclusion(s)."@en ;
rdfs:subClassOf obo:OBI_0000011 .
obo:STATO_0000148 a rdfs:Class ;
rdfs:label "Cochran-Armitage test for trend"@en ;
rdfs:comment """The Cochran-Armitage test is a statistical test used in categorical data analysis when the aim is to assess for the presence of an association between a dichotomous variable (variable with two categories) and a polychotomous variable (a variable with k categories).
The two-level variable represents the response, and the other represents an explanatory variable with ordered levels. The null hypothesis is the hypothesis of no trend, which means that the binomial proportion is the same for all levels of the explanatory variable
For example, doses of a treatment can be ordered as 'low', 'medium', and 'high', and we may suspect that the treatment benefit cannot become smaller as the dose increases. The trend test is often used as a genotype-based test for case-control genetic association studies."""@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000027 .
obo:BFO_0000020 a rdfs:Class ;
rdfs:label "specifically dependent continuant"@en ;
rdfs:comment "A continuant that inheres in or is borne by other entities. Every instance of A requires some specific instance of B which must always be the same."@en ;
rdfs:subClassOf obo:BFO_0000002 .
obo:STATO_0000364 a rdfs:Class ;
rdfs:label "first order autoregressive moving average covariance structure"@en ;
rdfs:comment "first order autoregressive moving average covariance structure is a type of covariance structure which is used in the context of time series analysis"@en ;
rdfs:subClassOf obo:STATO_0000346 .
obo:APOLLO_SV_00000796 a rdfs:Class ;
rdfs:label "dataset creating"@en ;
rdfs:comment "A planned process that has a data set as its specified output."@en ;
rdfs:subClassOf obo:OBI_0000011 .
obo:OBI_0200066 a rdfs:Class ;
rdfs:label "Holm-Bonferroni family-wise error rate correction method"@en ;
rdfs:comment "a data transformation that performs more than one hypothesis test simultaneously, a closed-test procedure, that controls the familywise error rate for all the k hypotheses at level α in the strong sense. Objective: multiple testing correction" ;
rdfs:subClassOf obo:OBI_0200073 .
obo:IAO_0000578 a rdfs:Class ;
rdfs:label "centrally registered identifier"@en ;
rdfs:comment "An information content entity that consists of a CRID symbol and additional information about the CRID registry to which it belongs."@en ;
rdfs:subClassOf obo:IAO_0000030 .
obo:STATO_0000263 a rdfs:Class ;
rdfs:label "Galbraith plot"@en ;
rdfs:comment """Galbraith (Radial) plot is a scatter plot which can be used in the meta-analytic context to examine the data for heterogeneity. For a fixed-effects model, the plot shows the inverse of the standard errors on the horizontal axis against the individual observed effect sizes or outcomes standardized by their corresponding standard errors on the vertical axis.
Radial plots were introduced by Rex Galbraith (1988a, 1988b, 1994)."""@en ;
rdfs:subClassOf obo:IAO_0000184 .
obo:STATO_0000290 a rdfs:Class ;
rdfs:label "contrast"@en ;
rdfs:comment "A contrast is the weighted sum of group means, the c_j coefficients represent the assigned weights of the means (these must sum to 0 for orthogonal contrasts)"@en ;
rdfs:subClassOf obo:IAO_0000027 .
obo:STATO_0000162 a rdfs:Class ;
rdfs:label "experimental unit role"@en ;
rdfs:comment "the role played by an entity part of study group as defined by an experimental design and realized in a data analysis and data interpretation"@en ;
rdfs:subClassOf obo:BFO_0000023 .
obo:STATO_0000400 a rdfs:Class ;
rdfs:label "quadratic mean"@en ;
rdfs:comment """The root mean square (abbreviated RMS or rms), also known as the quadratic mean, in statistics is a statistical measure of central tendency defined as the square root of the mean of the squares of a sample.
( To find the root mean square of a set of numbers, square all the numbers in the set and then find the arithmetic mean of the squares. Take the square root of the result. This is the root mean square.)"""@en ;
rdfs:subClassOf obo:STATO_0000029 .
obo:STATO_0000208 a rdfs:Class ;
rdfs:label "alternative hypothesis"@en ;
rdfs:comment "An alternative hypothesis is an hypothesis defined in a statistical test that is the opposite of the null hypothesis."@en ;
rdfs:subClassOf obo:STATO_0000065 .
obo:STATO_0000494 a rdfs:Class ;
rdfs:label "MAF matrix" ;
rdfs:comment "the MAF matrix is a genomic relationship matrix which is obtained from the genotype matrix by counting the number of minor alleles at each locus"@en ;
rdfs:subClassOf obo:STATO_0000642 .
obo:STATO_0000562 a rdfs:Class ;
rdfs:label "standard error of estimate" ;
rdfs:comment """The standard error is a measure of dispersion applied to estimates across hypothetical repeated random samples.
It is a measure of how precise an estimate of a statistical parameter is.
The standard error is the estimated standard deviation of an estimate.
It measures the uncertainty associated with the estimate. Compared with the standard deviations of the underlying distribution, which are usually unknown, standard errors can be calculated from observed data.""" ;
rdfs:seeAlso ;
rdfs:subClassOf obo:STATO_0000028 , obo:STATO_0000471 .
obo:STATO_0000249 a rdfs:Class ;
rdfs:label "DNA microarray hybridization"@en ;
rdfs:comment "a DNA microarray hybridization is an assay relying on nucleic acid hybridization , which uses a DNA microarray device and a nucleic acid as input. It precedes a data acquisition process"@en ;
rdfs:subClassOf obo:OBI_0000070 .
obo:OBI_0000963 a rdfs:Class ;
rdfs:label "categorical label" ;
rdfs:comment "A label that is part of a categorical datum and that indicates the value of the data item on the categorical scale." ;
rdfs:subClassOf obo:IAO_0000009 .
obo:STATO_0000631 a rdfs:Class ;
rdfs:label "modified Cohen’s kappa for more than 2 raters" ;
rdfs:comment """A Kappa statistic in which the expected agreement by chance is based on an assumption that the likelihood of each category for assignment is based on the proportion observed, and the number of raters is more than 2.
A Kappa statistic is a measure of agreement among categorical assessments, corrected for chance agreement.
In the modified Cohen's kappa for more than 2 raters, the expected chance agreement is modeled as the summation of the differences, between the square of the expected probability of the category and the quotient of its variance divided by the number of raters, for each category.
The modified Cohen's kappa for more than 2 raters is calculated as ( p[a] - p[e] ) / ( 1 - p[e] ) where p[a] is the observed percent agreement and p[e] is the expected chance agreement.""" ;
rdfs:subClassOf obo:STATO_0000682 .
obo:STATO_0000289 a rdfs:Class ;
rdfs:label "design matrix"@en ;
rdfs:comment """a design matrix is an information content entity which denotes a study design. The design matrix is a n by m matrix where n the number of rows, corresponds to the number of observations (4 rows if quadruplicates) and where m, the number of columns corresponds to the number of independent variables. Each element in the matrix correspond to a discretized value representing one of the factor levels for a given factor.
A design matrix can be used as input to statistical modeling or statistical analysis.
The design matrix contains data on the independent variables (also called explanatory variables) in statistical models which attempt to explain observed data on a response variable (often called a dependent variable) in terms of the explanatory variables. The theory relating to such models makes substantial use of matrix manipulations involving the design matrix: see for example linear regression. A notable feature of the concept of a design matrix is that it is able to represent a number of different experimental designs and statistical models, e.g., ANOVA, ANCOVA, and linear regression"""@en ;
rdfs:subClassOf obo:IAO_0000027 , obo:STATO_0000642 .
obo:STATO_0000122 a rdfs:Class ;
rdfs:label "pedigree chart"@en ;
rdfs:comment "a pedigree chart is a graph which plots parent child relations"@en ;
rdfs:subClassOf obo:IAO_0000038 .
obo:GO_0032991 a rdfs:Class ;
rdfs:label "protein-containing complex" ;
rdfs:comment "A stable assembly of two or more macromolecules, i.e. proteins, nucleic acids, carbohydrates or lipids, in which at least one component is a protein and the constituent parts function together." ;
rdfs:subClassOf obo:BFO_0000040 .
obo:STATO_0000440 a rdfs:Class ;
rdfs:label "Dixon Q test"@en ;
rdfs:comment "Dixon test is a statistical test used to detect outliers in a univariate data set assumed to come from a normally distributed population."@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000443 .
obo:STATO_0000711 a rdfs:Class ;
rdfs:label "equivalence margin"@en ;
rdfs:comment """A hypothesis testing margin used in a study with an equivalence goal.
The equivalence margin is a predefined threshold that specifies how large a difference between two treatments (or groups) can be and still be considered practically the same. It defines the range of differences that are not clinically or practically meaningful.""" ;
rdfs:subClassOf obo:STATO_0000709 .
obo:STATO_0000469 a rdfs:Class ;
rdfs:label "model interaction effect term"@en ;
rdfs:comment "a model interaction effect term is a model term which accounts for variation explained by the combined effects of the factor levels of more than one (usually 2) independent variables." ;
rdfs:subClassOf obo:STATO_0000466 .
obo:STATO_0000238 a rdfs:Class ;
rdfs:label "high-content screening"@en ;
rdfs:comment "high content screening is a kind of investigation which uses a standardized cellular assays to test the effect of substances (RNAi or small molecules) held in libraries on a cellular phenotype. it relies on microscopy imaging and or flow-cytometry, robotic handling to ensure fast and high-throughput."@en ;
rdfs:subClassOf obo:OBI_0000066 , obo:STATO_0000239 .
obo:STATO_0000704 a rdfs:Class ;
rdfs:label "concentration" ;
rdfs:comment """A concentration is the measure of the amount of solute dissolved in a unit quantity of solvent or solution. It describes the strength or intensity of a solution in terms of its solute content.
It is therefore a ratio in which the numerator is a measure of the solute and the denominator is a measure of the solvent.""" ;
rdfs:subClassOf obo:IAO_0000032 .
obo:OBI_0200036 a rdfs:Class ;
rdfs:label "Benjamini and Hochberg false discovery rate correction method"@en ;
rdfs:comment "A data transformation process in which the Benjamini and Hochberg method sequential p-value procedure is applied with the aim of correcting false discovery rate" ;
rdfs:subClassOf obo:OBI_0200163 .
obo:STATO_0000411 a rdfs:Class ;
rdfs:label "positive likelihood ratio"@en ;
rdfs:comment "the likelihood ratio of positive results is a ratio which is form by dividing the sensitivity value of a test by the difference between 1 and specificity of the test. This can be expressed also as dividing the probability of the test giving a positive result when testing an affected subject versus the probability of the test giving a positive result when a subject is not affected."@en ;
rdfs:subClassOf obo:STATO_0000409 .
obo:STATO_0000051 a rdfs:Class ;
rdfs:label "Poisson distribution"@en ;
rdfs:comment """Poisson distribution is a probability distribution used to model the number of events occurring within a given time interval. It is defined by a real number (λ) and an integer k representing the number of events and a function.
The expected value of a Poisson-distributed random variable is equal to λ and so is its variance."""@en ;
rdfs:subClassOf obo:STATO_0000117 .
obo:OBI_0100060 a rdfs:Class ;
rdfs:label "cultured cell population" ;
rdfs:comment "A processed material comprised of a collection of cultured cells that has been continuously maintained together in culture and shares a common propagation history." ;
rdfs:subClassOf obo:OBI_0000047 .
obo:STATO_0000011 a rdfs:Class ;
rdfs:label "cartesian coordinate axis"@en ;
rdfs:comment "a cartesian axis is one of 3 the axis in a cartesian coordinate system defining a referential in 3 dimensions. each of the axis is orthogonal to the other 2"@en ;
rdfs:subClassOf obo:STATO_0000007 .
obo:OBI_0000245 a rdfs:Class ;
rdfs:label "organization"@en ;
rdfs:comment "An entity that can bear roles, has members, and has a set of organization rules. Members of organizations are either organizations themselves or individual people. Members can bear specific organization member roles that are determined in the organization rules. The organization rules also determine how decisions are made on behalf of the organization by the organization members."@en ;
rdfs:subClassOf obo:BFO_0000040 .
obo:OBI_0001688 a rdf:Property ;
rdfs:label "has organization member"@en ;
rdfs:comment "Relating an organization to a legal person or organization." ;
rdfs:domain obo:OBI_0000245 ;
rdfs:range ;
rdfs:subPropertyOf obo:STATO_0000115 .
obo:STATO_0000551 a rdfs:Class ;
rdfs:label "Holm false discovery rate correction" ;
rdfs:comment "A data transformation process in which the Holm p-value procedure is applied with the aim of correcting false discovery rate" ;
rdfs:subClassOf obo:OBI_0200163 .
obo:STATO_0000170 a rdfs:Class ;
rdfs:label "third quartile"@en ;
rdfs:comment "the first quartile is a quartile which splits the 75 % of the data"@en ;
rdfs:subClassOf obo:STATO_0000152 .
obo:STATO_0000636 a rdfs:Class ;
rdfs:label "number needed to screen to prevent" ;
rdfs:comment """A statistic that represents the number of units that needs to be tested to prevent one additional adverse outcome, assuming that positive testing will lead to preventive intervention. The Number Needed to Screen to Prevent is calculated as the Number Needed to Treat divided by the prevalence.
Comment for application:
The Number Needed to Screen (NNS) value is often rounded up to the next highest whole integer. The Number Needed to Screen to Detect is distinct from the Number Needed to Screen to Prevent as the formulas to calculate are different, even though both may be abbreviated as NNS.
The formula may be adjusted for test performance characteristics (e.g. dividing by the sensitivity) or assumptions regarding acceptance or adherence of interventions.""" ;
rdfs:subClassOf obo:STATO_0000634 .
obo:STATO_0000155 a rdfs:Class ;
rdfs:label "meta analysis"@en ;
rdfs:comment "meta-analysis is a data transformation which uses the effect size estimates from several independent quantitative scientific studies addressing the same question in order to assess finding consistency."@en ;
rdfs:subClassOf obo:OBI_0200000 .
obo:STATO_0000519 a rdfs:Class ;
rdfs:label "last observation carried forward data imputation"@en ;
rdfs:comment "last observation carried forward data imputation is a type of data imputation which uses a very simple, self explanatory method for substituted a missing value for an observation. It should be noted that this method gives a biased estimate of the treatment effect and underestimates the variability of the estimated result and should be used cautiously." ;
rdfs:subClassOf obo:STATO_0000518 .
obo:STATO_0000278 a rdfs:Class ;
rdfs:label "pairing rule"@en ;
rdfs:comment "pairing rule is a rule which specifies the criteria for deciding on how to associated any 2 entities."@en ;
rdfs:subClassOf obo:IAO_0000055 .
obo:OBI_0000444 a rdfs:Class ;
rdfs:label "target of material addition role"@en ;
rdfs:comment "target of material addition role is a role realized by an entity into which a material is added in a material addition process" ;
rdfs:subClassOf obo:BFO_0000023 .
obo:STATO_0000722 a rdfs:Class ;
rdfs:label "quantitative variable" ;
rdfs:comment "A variable that can assume numerical values, with or without units of measure." ;
rdfs:subClassOf obo:STATO_0000258 .
obo:IAO_0000003 a rdfs:Class ;
rdfs:label "measurement unit label"@en ;
rdfs:comment "A measurement unit label is as a label that is part of a scalar measurement datum and denotes a unit of measure."@en ;
rdfs:subClassOf obo:IAO_0000009 .
obo:STATO_0000084 a rdfs:Class ;
rdfs:label "multinomial probit regression for analysis of polychotomous dependent variable"@en ;
rdfs:comment "multinomial logistic regression model is a model which attempts to explain data distribution associated with *polychotomous* response/dependent variable in terms of values assumed by the independent variable uses a function of predictor/independent variable(s): the function used in this instance of regression modeling is probit function."@en ;
rdfs:subClassOf obo:OBI_0200102 .
obo:STATO_0000360 a rdfs:Class ;
rdfs:label "no diagonal Factor Analytic covariance structure"@en ;
rdfs:comment "no diagonal factor-analytic covariance structure is a type of factor analytic covariance structure specified for q factors, which does not include a diagonal component for repeated measures."@en ;
rdfs:subClassOf obo:STATO_0000361 .
obo:STATO_0000642 a rdfs:Class ;
rdfs:label "matrix" ;
rdfs:comment "a matrix is a rectangular array of numbers, which are called entries of the matrix." ;
rdfs:subClassOf obo:IAO_0000030 .
obo:OBI_0200050 a rdfs:Class ;
rdfs:label "dimensionality reduction"@en ;
rdfs:comment "A dimensionality reduction is data partitioning which transforms each input m-dimensional vector (x_1, x_2, ..., x_m) into an output n-dimensional vector (y_1, y_2, ..., y_n), where n is smaller than m."@en ;
rdfs:subClassOf obo:APOLLO_SV_00000796 , obo:OBI_0200175 .
obo:STATO_0000668 a rdfs:Class ;
rdfs:label "absolute value"@en ;
rdfs:comment "A statistic that represents the distance of a value from zero."@en ;
rdfs:subClassOf obo:STATO_0000039 .
obo:STATO_0000568 a rdfs:Class ;
rdfs:label "loadings"@en ;
rdfs:comment "In factor analysis, factor loadings express the relationship of each variable to the underlying factor."@en ;
rdfs:subClassOf obo:OBI_0000648 , obo:STATO_0000034 .
obo:STATO_0000073 a rdfs:Class ;
rdfs:label "Fisher's exact test"@en ;
rdfs:comment "Fisher's exact test is a statistical test used to determine if there are nonrandom associations between two categorical variables."@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000027 .
obo:OBI_0000339 a rdfs:Class ;
rdfs:label "planning"@en ;
rdfs:comment "a process of creating or modifying a plan specification"@en ;
rdfs:subClassOf obo:BFO_0000015 .
obo:STATO_0000062 a rdfs:Class ;
rdfs:label "absence of within subject difference hypothesis"@en ;
rdfs:comment "is a null hypothesis stating that there are no difference observed across a series of measurements made one same subject."@en ;
rdfs:subClassOf obo:STATO_0000065 .
obo:STATO_0000181 a rdfs:Class ;
rdfs:label "Hardy-Weinberg equilibrium testing"@en ;
rdfs:comment "Hardy-Weinberg equilibrium test is a statistical test which aims to evaluate if a population's proportion of allele is stable or not. It is used as means of quality control to evaluate possibility of genotyping error or population structure."@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000191 .
obo:STATO_0000422 a rdfs:Class ;
rdfs:label "L'Abbe plot"@en ;
rdfs:comment """The L’Abbé plot was introduced in 1987 in the context of meta-analyses of clinical trials with dichotomous (binary) outcomes, as a plot of observed risks in the treatment group against observed risks in the control group.
Another formulation is that it plots the event rate in the experimental (intervention) group against the event rate in the control group, as an aid to exploring the heterogeneity of effect estimates within a meta-analysis.
It is diagram used in meta-analysis that compares the risks observed in the experimental and control arms of clinical trials. Each trial is located in the space of a diagram where the sizes of the circles indicate the sizes of the trials. Trials in which the experimental treatment had a higher risk than the control will be in the upper left of the plot. If risk in the both groups is the same the circle will fall on the line of equality. If the control treatment has a higher risk than the experimental treatment then the point will be in the lower right of the plot. It is often used as an indicator of heterogeneity and hence as an indicator of the likelihood that results from different trials can be validly combined. Named after Kristin L'Abbé."""@en ;
rdfs:subClassOf obo:IAO_0000038 .
obo:STATO_0000293 a rdfs:Class ;
rdfs:label "percentile"@en ;
rdfs:comment "a percentile is a quantile which splits data into sections accrued of 1% of data, so the first percentile delineates 1% of the data, the second quartile delineates 2% of the data and the 99th percentile, 99 % of the data"@en ;
rdfs:subClassOf obo:STATO_0000291 .
obo:STATO_0000022 a rdfs:Class ;
rdfs:label "one dimensional cartesian coordinate system"@en ;
rdfs:comment "A one dimensional cartesian coordinate system is a cartesian coordinate system which defines a one dimensional axis and which may be used to describe a one dimensional spatial region, i.e. a straight line. It is defined by a point O, the origin, a unit of length and the orientation for the one dimensional space."@en ;
rdfs:subClassOf obo:STATO_0000009 .
obo:OBI_0000806 a rdfs:Class ;
rdfs:label "material maintenance objective" ;
rdfs:comment "An objective specification maintains some or all of the qualities of a material over time." ;
rdfs:subClassOf obo:IAO_0000005 .
obo:OBI_0400103 a rdfs:Class ;
rdfs:label "DNA sequencer"@en ;
rdfs:comment "A DNA sequencer is an instrument that determines the order of deoxynucleotides in deoxyribonucleic acid sequences."@en ;
rdfs:subClassOf obo:OBI_0000832 .
obo:PATO_0001296 a rdfs:Class ;
rdfs:label "luminous flux" ;
rdfs:comment "A scalar optical quality which obtains by the magnitude of the light emitted by the bearer." ;
rdfs:subClassOf obo:PATO_0001300 .
obo:STATO_0000174 a rdfs:Class ;
rdfs:label "Forest plot"@en ;
rdfs:comment "A forest plot is a graph designed to illustrate the relative strength of treatment effects in multiple quantitative scientific studies addressing the same question."@en ;
rdfs:subClassOf obo:IAO_0000038 .
obo:IAO_0000109 a rdfs:Class ;
rdfs:label "measurement datum"@en ;
rdfs:comment "A measurement datum is an information content entity that is a recording of the output of a measurement such as produced by a device."@en ;
rdfs:subClassOf obo:IAO_0000027 .
obo:STATO_0000023 a rdfs:Class ;
rdfs:label "studentized range distribution"@en ;
rdfs:comment """The studentized range (q) distribution is a probability distribution used by the Tukey Honestly Significant Difference test.
The distribution of the statistic
[x̄(k)- x̄(1)]/(s/√n)
where random samples of size n have been taken from k independent and identically distributed normal populations, with x̄(1) and x̄(k) being, respectively, the smallest and largest of the k sample means, and s2 being the pooled estimate of the common variance. This statistic is particularly used in multiple comparison tests."""@en ;
rdfs:subClassOf obo:STATO_0000067 .
obo:STATO_0000490 a rdfs:Class ;
rdfs:label "Dunn’s multiple comparison test"@en ;
rdfs:comment "Dunn’s Multiple Comparison Test is a post hoc (i.e. it’s run after an ANOVA) non parametric test (a “distribution free” test that doesn’t assume your data comes from a particular distribution). It is one of the least powerful of the multiple comparisons tests and can be a very conservative test–especially for larger numbers of comparisons. The Dunn is an alternative to the Tukey test when you only want to test for differences in a small subset of all possible pairs; For larger numbers of pairwise comparisons, use Tukey’s instead. Use Dunn’s when you choose to test a specific number of comparisons before you run the ANOVA and when you are not comparing to controls. If you are comparing to a control group, use the Dunnett test instead."@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:OBI_0200089 , obo:STATO_0000279 .
obo:STATO_0000525 a rdfs:Class ;
rdfs:label "covariance matrix"@en ;
rdfs:comment "a covariance matrix is a square matrix that contains the variances and covariances associated with several variables. The diagonal elements of the matrix contain the variances of the variables and the off-diagonal elements contain the covariances between all possible pairs of variables."@en ;
rdfs:subClassOf obo:STATO_0000642 .
obo:OBI_0001501 a rdfs:Class ;
rdfs:label "fluorescence detection assay" ;
rdfs:comment "An assay in which a material's fluorescence is determined." ;
rdfs:subClassOf obo:OBI_0000070 .
obo:OBI_0300311 a rdfs:Class ;
rdfs:label "observation design"@en ;
rdfs:comment "observation design is a study design in which subjects are monitored in the absence of any active intervention by experimentalists."@en ;
rdfs:subClassOf obo:OBI_0500000 .
obo:STATO_0000306 a rdfs:Class ;
rdfs:label "polynomial contrast"@en ;
rdfs:comment "a polynomial contrast is a contrast which..."@en ;
rdfs:subClassOf obo:STATO_0000290 .
obo:STATO_0000687 a rdfs:Class ;
rdfs:label "calibration slope"@en ;
rdfs:comment "A measure of calibration that is the rate of change in the appropriately transformed value per unit change of the correspondingly transformed predicted value."@en ;
rdfs:subClassOf obo:STATO_0000685 .
obo:OBI_0001364 a rdfs:Class ;
rdfs:label "genetic alteration information"@en ;
rdfs:comment "a genetic characteristics information that is about known changes or the lack thereof from the genetic background, including allele information, duplication, insertion, deletion, etc."@en ;
rdfs:subClassOf obo:OBI_0001404 .
obo:STATO_0000432 a rdfs:Class ;
rdfs:label "meta analysis by Hunter-Schmidt method"@en ;
rdfs:comment """a meta analysis which relies on the computation of the Hunter and Schmidt estimator as a measure of heterogeneity over a set of studies by considering the weighted mean of the raw correlation coefficient. Hunter and Schmidt developed what is commonly termed validity generalization procedures (Schmidt and Hunter, 1977). These involve correcting the effect sizes in the meta-analysis for sampling, and measurement error
and range restriction."""@en ;
rdfs:subClassOf obo:STATO_0000155 .
obo:OGMS_0000023 a rdfs:Class ;
rdfs:label "phenotype" ;
rdfs:comment "A (combination of) quality(ies) of an organism determined by the interaction of its genetic make-up and environment that differentiates specific instances of a species from other instances of the same species."@en ;
rdfs:subClassOf obo:BFO_0000019 .
obo:OBI_0000731 a rdfs:Class ;
rdfs:label "recombinant vector" ;
rdfs:comment "A recombinant vector is created by a recombinant vector cloning process, and contains nucleic acids that can be amplified. It retains functions of the original cloning vector." ;
rdfs:subClassOf obo:BFO_0000040 , obo:OBI_0000047 .
obo:STATO_0000018 a rdfs:Class ;
rdfs:label "three dimensional cartesian spatial coordinate origin"@en ;
rdfs:comment "A cartesian spatial coordinate datum chosen as a fixed point of reference in a three dimensional spatial region."@en ;
rdfs:subClassOf obo:STATO_0000026 .
obo:STATO_0000350 a rdfs:Class ;
rdfs:label "spatial spherical geometric anisotropic covariance structure"@en ;
rdfs:comment "spatial spherical geometric anisotropic covariance structure is a type of covariance structure characterized by its anisotropy, i.e., the variation of properties can be different in directions x and y, which is this case give spherical features."@en ;
rdfs:subClassOf obo:STATO_0000346 .
obo:IAO_0000038 a rdfs:Class ;
rdfs:label "graph"@en ;
rdfs:comment "A diagram that presents one or more tuples of information by mapping those tuples in to a two dimensional space in a non arbitrary way."@en ;
rdfs:subClassOf obo:IAO_0000309 .
obo:STATO_0000387 a rdfs:Class ;
rdfs:label "scatterplot matrix"@en ;
rdfs:comment "A scatterplot matrix contains all the pairwise scatter plots of a set of variables on a single page in a matrix format."@en ;
rdfs:subClassOf obo:IAO_0000038 .
obo:STATO_0000231 a rdfs:Class ;
rdfs:label "95% confidence interval"@en ;
rdfs:comment "a confidence interval which covers 95% of the sampling distribution, meaning that there is a 5% risk of false positive (type I error). If the number of observations made is large enough, the sampling distribution can be assumed to be normal, which entails that 95% of the sampling distributions falls within roughly2 (1.96) standard deviations from the mean."@en ;
rdfs:subClassOf obo:STATO_0000196 .
obo:STATO_0000644 a rdfs:Class ;
rdfs:label "sign test" ;
rdfs:comment """The sign test is a non-parametric hypothesis test used to assess whether the median of a single population is equal to a specified value, typically referred to as the null hypothesis. The sign test is particularly useful when the data are not normally distributed or when the assumptions required for parametric tests are not met.
Note that the 'sign test' is related but different from the \"Wilcoxon signed rank test'.
Sign test: It does not assume any specific distribution for the data. It only requires paired data and makes no assumptions about the shape of the underlying distribution.
Wilcoxon signed-rank test: It assumes that the differences between paired observations come from a symmetric distribution. It's also more powerful than the sign test when the distribution is continuous and symmetric.""" ;
rdfs:subClassOf obo:OBI_0000673 , obo:OBI_0200000 .
obo:OBI_0200041 a rdfs:Class ;
rdfs:label "k-means clustering"@en ;
rdfs:comment "A k-means clustering is a data transformation which achieves a class discovery or partitioning objective, which takes as input a collection of objects (represented as points in multidimensional space) and which partitions them into a specified number k of clusters. The algorithm attempts to find the centers of natural clusters in the data. The most common form of the algorithm starts by partitioning the input points into k initial sets, either at random or using some heuristic data. It then calculates the mean point, or centroid, of each set. It constructs a new partition by associating each point with the closest centroid. Then the centroids are recalculated for the new clusters, and the algorithm repeated by alternate applications of these two steps until convergence, which is obtained when the points no longer switch clusters (or alternatively centroids are no longer changed)."@en ;
rdfs:subClassOf obo:APOLLO_SV_00000796 , obo:OBI_0200171 , obo:OBI_0200175 .
obo:IAO_0000102 a rdfs:Class ;
rdfs:label "data about an ontology part"@en ;
rdfs:comment "Data about an ontology part is a data item about a part of an ontology, for example a term"@en ;
rdfs:subClassOf obo:IAO_0000027 .
obo:OBI_0000648 a rdfs:Class ;
rdfs:label "clustered data set"@en ;
rdfs:comment "A data set that is produced as the output of a class discovery data transformation and consists of a data set with assigned discovered class labels."@en ;
rdfs:subClassOf obo:IAO_0000100 .
obo:STATO_0000029 a rdfs:Class ;
rdfs:label "measure of central tendency"@en ;
rdfs:comment "a measure of central tendency is a data item which attempts to describe a set of data by identifying the value of its centre."@en ;
rdfs:subClassOf obo:STATO_0000039 .
obo:OBI_0400044 a rdfs:Class ;
rdfs:label "flow cytometer"@en ;
rdfs:comment "A flow_cytometer is an instrument for counting, examining and sorting microscopic particles in suspension. It allows simultaneous multiparametric analysis of the physical and/or chemical characteristics of single cells flowing through an optical and/or electronic detection apparatus. A flow cytometer is an instrument that can be used to quantitatively measure the properties of individual cells in a flowing medium."@en ;
rdfs:subClassOf obo:OBI_0400137 .
obo:STATO_0000221 a rdfs:Class ;
rdfs:label "random variable"@en ;
rdfs:comment "a random variable (or aleatory variable or stochastic variable) in probability and statistics, is a variable whose value is subject to variations due to chance (i.e. randomness, in a mathematical sense)"@en ;
rdfs:subClassOf obo:STATO_0000258 .
obo:STATO_0000390 a rdfs:Class ;
rdfs:label "regression model"@en ;
rdfs:comment "A regression model is a statistical model used in a type of analysis knowns as regression analysis, whereby a function is used to determine the relation between a response variable and an independent variable , with a set of unknown parameters."@en ;
rdfs:subClassOf obo:STATO_0000107 .
obo:STATO_0000424 a rdfs:Class ;
rdfs:label "risk difference"@en ;
rdfs:comment """The risk difference is the difference between the observed risks (proportions of individuals with the outcome of interest) in the two groups.
The risk difference is straightforward to interpret: it describes the actual difference in the observed risk of events between experimental and control interventions."""@en ;
rdfs:subClassOf obo:STATO_0000614 .
obo:STATO_0000488 a rdfs:Class ;
rdfs:label "additive dominant genetic inheritance model"@en ;
rdfs:comment "an additive genetic model is a data item which refer to the contributions to the final phenotype from more than one gene, or from alleles of a single gene (in heterozygotes), that combine in such a way that the sum of their effects in unison is equal to the sum of their individual effects and their dominance effect (of alleles at a single locus)."@en ;
rdfs:subClassOf obo:STATO_0000534 .
obo:STATO_0000495 a rdfs:Class ;
rdfs:label "M matrix" ;
rdfs:comment """the M matrix is a genomic relationship matrix which is obtained by subtracting 1 to every value of the MAF matrix (gene content matrix). The values of the M matrix are only -1, 0 or 1 and makes computation easier.
M = MAF-1""" ;
rdfs:subClassOf obo:STATO_0000642 .
obo:STATO_0000620 a rdfs:Class ;
rdfs:label "risk" ;
rdfs:comment "A proportion in which the numerator represents the cases in which an event or characteristic occurs and the denominator represents all possible cases." ;
rdfs:subClassOf obo:STATO_0000607 .
obo:STATO_0000526 a rdfs:Class ;
rdfs:label "numerator relationship matrix"@en ;
rdfs:comment "the numerator relationship matrix is the matrix of *expected* additive genetic relationships between individuals. This matrix was originally used by Henderson (Henderson, C.R. 1976. A simple method for computing the inverse of a numerator relationship matrix used in prediction of breeding values. Biometrics 32:69-83.) to account for covariances between random effects, and therefore to use information from relatives in estimation of breeding value. Among the properties of the NRM matrix (also known as the A matrix), it is symmetric, the diagonal value correspond to 1+ the inbreeding coefficient for an individual." ;
rdfs:subClassOf obo:STATO_0000642 .
obo:OBI_0200186 a rdfs:Class ;
rdfs:label "error correction objective"@en ;
rdfs:comment "An error correction objective is a data transformation objective where the aim is to remove (correct for) erroneous contributions arising from the input data, or the transformation itself."@en ;
rdfs:subClassOf obo:OBI_0200168 .
obo:OBI_0000675 a rdfs:Class ;
rdfs:label "statistical hypothesis test objective"@en ;
rdfs:comment "is a data transformation objective where the aim is to estimate statistical significance with the aim of proving or disproving a hypothesis by means of some data transformation " ;
rdfs:subClassOf obo:OBI_0200166 .
obo:STATO_0000532 a rdfs:Class ;
rdfs:label "posterior probability distribution" ;
rdfs:comment "a posterior probability distribution is a probability distribution computed in a Bayesian model approach given a prior distribution and a set of events/observations." ;
rdfs:subClassOf obo:IAO_0000027 , obo:STATO_0000225 .
obo:STATO_0000214 a rdfs:Class ;
rdfs:label "50% confidence interval"@en ;
rdfs:comment "a confidence interval which covers 50% of the sampling distribution, meaning that there is a 50% risk of false positive (type I error)"@en ;
rdfs:subClassOf obo:STATO_0000196 .
obo:STATO_0000515 a rdfs:Class ;
rdfs:label "Brewer sampling"@en ;
rdfs:comment "Brewer's sampling is a statistical sampling method which was proposed by Brewer in 1975 and uses unequal probabibility sampling technique"@en ;
rdfs:subClassOf obo:STATO_0000509 .
obo:OBI_0500013 a rdfs:Class ;
rdfs:label "hyper graeco latin square design"@en ;
rdfs:comment "PRS to do"@en ;
rdfs:subClassOf obo:OBI_0500000 , obo:OBI_0500007 .
obo:OBI_0400082 a rdfs:Class ;
rdfs:label "photodetector"@en ;
rdfs:comment "A photodetector is a device used to detect and measure the intensity of radiant energy through photoelectric action. In a cytometer, photodetectors measure either the number of photons of laser light scattered on impact with a cell (for example), or the flourescence emitted by excitation of a fluorescent dye."@en ;
rdfs:subClassOf obo:OBI_0000832 .
obo:OBI_0200044 a rdfs:Class ;
rdfs:label "complete linkage hierarchical clustering"@en ;
rdfs:comment "an agglomerative hierarchical clustering which generates successive clusters based on a distance measure, where the distance between two clusters is calculated as the maximum distance between objects from the first cluster and objects from the second cluster."@en ;
rdfs:subClassOf obo:OBI_0200154 .
obo:OBI_0000924 a rdfs:Class ;
rdfs:label "labeled specimen" ;
rdfs:comment "A specimen that has been modified in order to be able to detect it in future experiments" ;
rdfs:subClassOf obo:OBI_0000953 , obo:OBI_0001936 , obo:OBI_0100051 .
a rdfs:Class ;
rdfs:label "sum"@en ;
rdfs:comment "A statistic that represents the result of adding all the values in a collection of values."@en ;
rdfs:subClassOf obo:STATO_0000039 .
obo:STATO_0000452 a rdfs:Class ;
rdfs:label "Hotelling-Lawley trace"@en ;
rdfs:comment "\"The Lawley–Hotelling trace is used to test the equality of mean vectors of k p‐variate normal distributions with common but unknown covariance matrix. The explicit form of the null distribution of T$_{0}^{2}$equation image is the F distribution. The asymptotic null distribution is the chi‐square distribution. The power function of the test is described and its power is compared with the likelihood ratio test. \""@en ;
rdfs:subClassOf obo:STATO_0000039 .
obo:STATO_0000012 a rdfs:Class ;
rdfs:label "z-axis"@en ;
rdfs:comment "z-axis is a cartesian coordinate axis which is orthogonal to the x-axis and the y-axis"@en ;
rdfs:subClassOf obo:STATO_0000011 .
obo:STATO_0000463 a rdfs:Class ;
rdfs:label "Haybittle-Peto boundary analysis"@en ;
rdfs:comment """The Haybittle–Peto boundary analysis is an interim analysis where a rule for deciding when to stop a clinical trial prematurely is defined. It is named for John Haybittle and Richard Peto.
The Haybittle–Peto boundary is one such stopping rule, and it states that if an interim analysis shows a probability of equal to, or less than 0.001 that a difference as extreme or more between the treatments is found, given that the null hypothesis is true, then the trial should be stopped early. The final analysis is still evaluated at the normal level of significance (usually 0.05).[3][4] The main advantage of the Haybittle–Peto boundary is that the same threshold is used at every interim analysis, unlike the O'Brien–Fleming boundary, which changes at every analysis. Also, using the Haybittle–Peto boundary means that the final analysis is performed using a 0.05 level of significance as normal, which makes it easier for investigators and readers to understand. The main argument against the Haybittle–Peto boundary is that some investigators believe that the Haybittle–Peto boundary is too conservative and makes it too difficult to stop a trial.
As all frequentist methods of the same type, it focuses on controlling the type I error rate as the repeated hypothesis testing of accumulating data increases the type I error rate of a clinical trial."""@en ;
rdfs:subClassOf obo:STATO_0000460 .
obo:OBI_0000015 a rdfs:Class ;
rdfs:label "biological feature identification objective"@en ;
rdfs:comment "Biological_feature_identification_objective is an objective role carried out by the proposition defining the aim of a study designed to examine or characterize a particular biological feature."@en ;
rdfs:subClassOf obo:IAO_0000005 .
obo:STATO_0000477 a rdfs:Class ;
rdfs:label "partial least square weight"@en ;
rdfs:comment "PLS weight (or Partial Least Square weight) is a information content entity which is generated when performing a Partial Least Square analysis"@en ;
rdfs:subClassOf obo:IAO_0000027 .
obo:STATO_0000633 a rdfs:Class ;
rdfs:label "cutoff" ;
rdfs:comment "a cutoff is an information content entity that represents or sets the boundary at which something changes." ;
rdfs:subClassOf obo:IAO_0000030 .
obo:STATO_0000737 a rdfs:Class ;
rdfs:label "correction factor for multiple testing" ;
rdfs:comment "a data item used as input to a multiple testing correction method that means the alpha level is adjusted for multiple comparisons." ;
rdfs:subClassOf obo:IAO_0000027 .
obo:STATO_0000113 a rdfs:Class ;
rdfs:label "variance"@en ;
rdfs:comment "variance is a data item about a random variable or probability distribution. it is equivalent to the square of the standard deviation. It is one of several descriptors of a probability distribution, describing how far the numbers lie from the mean (expected value).The variance is the second moment of a distribution."@en ;
rdfs:subClassOf obo:STATO_0000028 .
obo:STATO_0000593 a rdfs:Class ;
rdfs:label "adjusted Rand index"@en ;
rdfs:comment "the adjusted Rand index is a measure which rescales the Rand index, taking into account that random chance will cause some objects to occupy the same clusters, so the Rand Index will never actually be zero."@en ;
rdfs:subClassOf obo:STATO_0000592 .
obo:STATO_0000608 a rdfs:Class ;
rdfs:label "area under the receiver operator characteristic curve"@en ;
rdfs:comment "An area under the curve where the curve is the true positive rate and the range of interest is the false positive rate."@en ;
rdfs:subClassOf obo:STATO_0000209 .
obo:SO_0000001 a rdfs:Class ;
rdfs:label "region" ;
rdfs:comment "A sequence_feature with an extent greater than zero. A nucleotide region is composed of bases and a polypeptide region is composed of amino acids." ;
rdfs:subClassOf obo:BFO_0000031 .
obo:STATO_0000324 a rdfs:Class ;
rdfs:label "contrast weight estimate"@en ;
rdfs:comment "contrast weight estimate is a model parameter estimate which results from the computation from the data and that is used as input to a model fitting process"@en ;
rdfs:subClassOf obo:STATO_0000144 .
obo:STATO_0000413 a rdfs:Class ;
rdfs:label "incidence"@en ;
rdfs:comment "A proportion in which the numerator represents new events."@en ;
rdfs:subClassOf obo:STATO_0000607 .
obo:STATO_0000596 a rdfs:Class ;
rdfs:label "number of false positive"@en ;
rdfs:comment "the number of false positive is a count which denotes how many elements known to be void of feature are wrongly classified as having it (e.g. being diagnosed with a disease when one is totally healthy)" ;
rdfs:subClassOf obo:STATO_0000047 .
obo:STATO_0000508 a rdfs:Class ;
rdfs:label "stratified sampling"@en ;
rdfs:comment "stratified sampling is a statistical sampling method which divides the population into homogenous subpopulations, which are then sampled using random or systematic sampling methods" ;
rdfs:subClassOf obo:STATO_0000502 .
obo:STATO_0000658 a rdfs:Class ;
rdfs:label "mean time-to-event" ;
rdfs:comment "A mean of values in which each value is the duration of time between the start of observation and the occurrence of an event." ;
rdfs:subClassOf obo:STATO_0000573 .
obo:STATO_0000196 a rdfs:Class ;
rdfs:label "confidence interval"@en ;
rdfs:comment "A confidence interval is a data item which defines an range of values in which a measurement or trial falls corresponding to a given probability."@en ;
rdfs:subClassOf obo:STATO_0000028 .
obo:STATO_0000514 a rdfs:Class ;
rdfs:label "convenience sampling"@en ;
rdfs:comment "Convenience sampling (also known as grab sampling, accidental sampling, or opportunity sampling) is a type of non-probability sampling that involves the sample being drawn from that part of the population that is close to hand. This type of sampling is most useful for pilot testing."@en ;
rdfs:subClassOf obo:STATO_0000502 .
obo:STATO_0000242 a rdfs:Class ;
rdfs:label "statistical error"@en ;
rdfs:comment "statistical error is an data item denoting the amount by which an observation differs from the expected value, being based on the whole statistical population from which the statistical unit was chosen randomly"@en ;
rdfs:subClassOf obo:STATO_0000039 .
obo:OBI_0001172 a rdfs:Class ;
rdfs:label "dose response curve"@en ;
rdfs:comment "A data item of paired values, one indicating the dose of a material, the other quantitating a measured effect at that dose. The dosing intervals are chosen so that effect values be interpolated by a plotting a curve. " ;
rdfs:subClassOf obo:IAO_0000573 .
obo:OBI_0000626 a rdfs:Class ;
rdfs:label "DNA sequencing assay" ;
rdfs:comment "DNA sequencing is a sequencing process which uses deoxyribonucleic acid as input and results in a the creation of DNA sequence information artifact using a DNA sequencer instrument." ;
rdfs:subClassOf obo:OBI_0600047 .
obo:STATO_0000361 a rdfs:Class ;
rdfs:label "Factor Analytic covariance structure"@en ;
rdfs:comment "factor-analytic structure is a type of heterogeneous covariance structure which is specified for q factors"@en ;
rdfs:subClassOf obo:STATO_0000346 .
obo:STATO_0000124 a rdfs:Class ;
rdfs:label "stratification rule"@en ;
rdfs:comment "a stratification rule/criteria is a criteria used to determine population strata so that a stratification process implementing the rule can result in any member of the total population being assigned to one and only one stratum"@en ;
rdfs:subClassOf obo:IAO_0000055 .
obo:STATO_0000376 a rdfs:Class ;
rdfs:label "Z-statistic" ;
rdfs:comment "Z-statistic is a statistic computed from observations and used to produce a p-value when compared to a Standard Normal Distribution in a statistical test called the Z-test." ;
rdfs:subClassOf obo:STATO_0000039 .
obo:IAO_0000032 a rdfs:Class ;
rdfs:label "scalar measurement datum"@en ;
rdfs:comment "A scalar measurement datum is a measurement datum that is composed of two parts, numerals and a unit label."@en ;
rdfs:subClassOf obo:IAO_0000109 .
obo:STATO_0000185 a rdfs:Class ;
rdfs:label "2 by n contingency table"@en ;
rdfs:comment "a 2 by n contingency table is a contingency table built for one dichotomous variable (a categorical variable with only 2 outcomes) and one polychotomous variable (a polychomotomous variable with at least 2 outcomes)"@en ;
rdfs:subClassOf obo:STATO_0000140 .
obo:STATO_0000348 a rdfs:Class ;
rdfs:label "rational quadratic anisotropic covariance structure"@en ;
rdfs:comment "The rational quadratic covariance function is used in spatial statistics, geostatistics, machine learning, image analysis, and other fields where multivariate statistical analysis is conducted on metric spaces. It is commonly used to define the statistical covariance between measurements made at two points that are d units distant from each other. Since the covariance only depends on distances between points, it is stationary. If the distance is Euclidean distance, the rational quadratic covariance function is also isotropic."@en ;
rdfs:subClassOf obo:STATO_0000346 .
obo:STATO_0000225 a rdfs:Class ;
rdfs:label "probability distribution"@en ;
rdfs:comment """A probability distribution is a information content entity that specifies the probability of the value of a random variable.
For a discrete random variable, a mathematical formula that gives the probability of each value of the variable.
For a continuous random variable, a curve described by a mathematical formula which specifies, by way of areas under the curve, the probability that the variable falls within a particular interval."""@en ;
rdfs:subClassOf obo:IAO_0000030 .
obo:STATO_0000436 a rdfs:Class ;
rdfs:label "probability distribution shape parameter"@en ;
rdfs:comment "a probability distribution shape parameter is a data item which is set by the operator when selecting a parametric probability distribution and which dictates the way the profile but not the location or size of the distribution plot looks like."@en ;
rdfs:subClassOf obo:IAO_0000027 , obo:STATO_0000742 .
obo:STATO_0000298 a rdfs:Class ;
rdfs:label "exact binomial test"@en ;
rdfs:comment "a binomial test is a statistical hypothesis test which evaluates if the observations made about a Bernoulli experiment , that is an experiment which tests the statistical significance of deviations from a theoretically expected distribution (the binomial distribution) of observations into 2 categories. It is a goodness of fit test."@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000191 .
obo:STATO_0000275 a rdfs:Class ;
rdfs:label "transmission disequilibrium test"@en ;
rdfs:comment "The transmission disequilibrium test is a statistical test for genetic linkage between genetic marker and a trait in families. The test is robust to population structure."@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000027 .
obo:STATO_0000163 a rdfs:Class ;
rdfs:label "trimmed mean"@en ;
rdfs:comment "trimmed mean or truncated mean is a measure of central tendency which involves the calculation of the mean after discarding given parts of a probability distribution or sample at the high and low end, and typically discarding an equal amount of both"@en ;
rdfs:subClassOf obo:STATO_0000029 .
obo:PATO_0000018 a rdfs:Class ;
rdfs:label "fluorescence" ;
rdfs:comment "A luminous flux quality inhering in a bearer by virtue of the bearer's emitting longer wavelength light following the absorption of shorter wavelength radiation; fluorescence is common with aromatic compounds with several rings joined together." ;
rdfs:subClassOf obo:BFO_0000016 , obo:PATO_0001296 .
obo:STATO_0000614 a rdfs:Class ;
rdfs:label "absolute difference"@en ;
rdfs:comment """A statistic that is a subtraction of one quantity from another, with no modification of the resulting value.
As a type of statistic, \"Absolute Difference\" is the actual difference between two quantities and can be positive or negative depending on the order of subtraction. The term \"Absolute Difference\" should not be confused with the mathematical term 'absolute value' which is a numerical value without a negative sign."""@en ;
rdfs:subClassOf obo:STATO_0000613 .
obo:STATO_0000146 a rdfs:Class ;
rdfs:label "presence of between group difference hypothesis"@en ;
rdfs:comment "a null hypothesis stating that there are differences observed between group of subjects"@en ;
rdfs:subClassOf obo:STATO_0000065 .
obo:OBI_0400137 a rdfs:Class ;
rdfs:label "cytometer"@en ;
rdfs:comment "A cytometer is an instrument for counting and measuring cells."@en ;
rdfs:subClassOf obo:OBI_0000832 .
obo:STATO_0000739 a rdfs:Class ;
rdfs:label "nominal alpha level" ;
rdfs:comment "An alpha level that expresses the intended overall probability cutoff without adjustment for multiple comparisons" ;
rdfs:subClassOf obo:STATO_0000738 .
obo:OBI_0001010 a rdfs:Class ;
rdfs:label "nucleic acid extract" ;
rdfs:comment "An extract that is the output of an extraction process in which nucleic acid molecules are isolated from a specimen." ;
rdfs:subClassOf obo:OBI_0000423 , obo:OBI_0000953 .
obo:OBI_0000425 a rdfs:Class ;
rdfs:label "averaging objective"@en ;
rdfs:comment "An averaging objective is a data transformation objective where the aim is to perform mean calculations on the input of the data transformation."@en ;
rdfs:subClassOf obo:OBI_0200166 .
obo:STATO_0000068 a rdfs:Class ;
rdfs:label "skewness"@en ;
rdfs:comment "Skewness is a data item indicating of the degree of asymmetry of a distribution."@en ;
rdfs:subClassOf obo:STATO_0000039 .
obo:STATO_0000337 a rdfs:Class ;
rdfs:label "breeding value estimation"@en ;
rdfs:comment "breeding value estimation is a data transformation process aiming at computing breeding value estimates of an organism given a set of genomic (SNP) observations, pedigree information and/or phenotypic observations."@en ;
rdfs:subClassOf obo:OBI_0200000 .
obo:STATO_0000481 a rdfs:Class ;
rdfs:label "genomic best linear unbiased prediction" ;
rdfs:comment "a data transformation which calculate predictions of breeding values using an animal model and a relationship matrix calculated from the genomic/genetic markers (G Matrix), in constrast to using Pedigree information as in BLUP, also known as ABLUP" ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000119 , obo:STATO_0000337 .
obo:STATO_0000714 a rdfs:Class ;
rdfs:label "type II error"@en ;
rdfs:comment "the event of incorrectly failing to reject the null hypothesis."@en ;
rdfs:subClassOf obo:STATO_0000242 .
obo:STATO_0000559 a rdfs:Class ;
rdfs:label "Wald test" ;
rdfs:comment """the Wald test is statistical test which computes a Wald chi-squared test for 1 or more coefficients, given their variance-covariance matrix.
The Wald test (also called the Wald Chi-Squared Test) is a way to find out if explanatory variables in a model are significant. “Significant” means that they add something to the model; variables that add nothing can be deleted without affecting the model in any meaningful way""" ;
rdfs:subClassOf obo:OBI_0200200 .
obo:OBI_0000112 a rdfs:Class ;
rdfs:label "specimen role"@en ;
rdfs:comment "a role borne by a material entity that is gained during a specimen collection process and that can be realized by use of the specimen in an investigation"@en ;
rdfs:subClassOf obo:BFO_0000023 .
obo:STATO_0000578 a rdfs:Class ;
rdfs:label "PLS2" ;
rdfs:comment "a partial least square regression applied to a multivariate response variable." ;
rdfs:subClassOf obo:STATO_0000571 .
obo:STATO_0000192 a rdfs:Class ;
rdfs:label "cartesian product"@en ;
rdfs:comment "a cartesian product is a data transformation which operates on a n Sets to produce a set of all possible ordered n-tuples where each element of the tuple comes from a Set" ;
rdfs:subClassOf obo:OBI_0200000 .
obo:STATO_0000443 a rdfs:Class ;
rdfs:label "generalized extreme studentized deviate test"@en ;
rdfs:comment """The Extreme Studentized Deviate Test is a statistical test used to detect outliers in a univariate data set assumed to come from a normally distributed population.
The ESD Test differs from the Grubbs' test and the Tietjen-Moore test in the sense that it contains built-in correction for multiple testing."""@en ;
rdfs:subClassOf obo:OBI_0000673 , obo:OBI_0200000 .
obo:STATO_0000470 a rdfs:Class ;
rdfs:label "model error term"@en ;
rdfs:comment "a model error term is a model term which accounts for residual variation not explained by the other components (fixed and random effect terms)" ;
rdfs:subClassOf obo:OBI_0000751 , obo:STATO_0000466 .
obo:OBI_0200167 a rdfs:Class ;
rdfs:label "data normalization objective"@en ;
rdfs:comment """A normalization objective is a data transformation objective where the aim is to remove
systematic sources of variation to put the data on equal footing in order
to create a common base for comparisons."""@en ;
rdfs:subClassOf obo:OBI_0200166 .
obo:PATO_0001291 a rdfs:Class ;
rdfs:label "electromagnetic (EM) radiation quality" ;
rdfs:comment "A physical quality that inheres in an bearer by virtue of how that bearer interacts with electromagnetic radiation." ;
rdfs:subClassOf obo:PATO_0001739 .
obo:STATO_0000676 a rdfs:Class ;
rdfs:label "number density"@en ;
rdfs:comment "A ratio in which the numerator represents a count and the denominator represents an interval of space (distance, area, or volume)." ;
rdfs:subClassOf obo:STATO_0000675 .
obo:OBI_0666666 a rdfs:Class ;
rdfs:label "RNA extraction"@en ;
rdfs:comment "A RNA extraction is a nucleic acid extraction where the desired output material is RNA"@en ;
rdfs:subClassOf obo:OBI_0666667 .
obo:STATO_0000602 a rdfs:Class ;
rdfs:label "sequential multiple testing correction method" ;
rdfs:comment "sequential multiple testing method is a multiple testing correction method which..." ;
rdfs:subClassOf obo:OBI_0200089 .
obo:STATO_0000703 a rdfs:Class ;
rdfs:label "posterior probability" ;
rdfs:comment "A statistic that represents the likelihood of a parameter of interest, after updating its prior probability with the observed data from the study." ;
rdfs:subClassOf obo:STATO_0000039 .
obo:PATO_0000125 a rdfs:Class ;
rdfs:label "mass" ;
rdfs:comment "A physical quality that inheres in a bearer by virtue of the proportion of the bearer's amount of matter." ;
rdfs:subClassOf obo:BFO_0000019 , obo:PATO_0001018 .
obo:IAO_0000300 a rdfs:Class ;
rdfs:label "textual entity"@en ;
rdfs:comment "A textual entity is a part of a manifestation (FRBR sense), a generically dependent continuant whose concretizations are patterns of glyphs intended to be interpreted as words, formulas, etc."@en ;
rdfs:subClassOf obo:IAO_0000030 .
obo:OBI_0001032 a rdfs:Class ;
rdfs:label "light emission device" ;
rdfs:comment "A device which has a function to emit light." ;
rdfs:subClassOf obo:OBI_0000968 .
obo:STATO_0000152 a rdfs:Class ;
rdfs:label "quartile"@en ;
rdfs:comment "a quartile is a quantile which splits data into sections accrued of 25% of data, so the first quartile delineates 25% of the data, the second quartile delineates 50% of the data and the third quartile, 75 % of the data"@en ;
rdfs:subClassOf obo:STATO_0000291 .
obo:OBI_0600047 a rdfs:Class ;
rdfs:label "sequencing assay"@en ;
rdfs:comment "An assay the uses chemical or biochemical means to infer the sequence of a biomaterial"@en ;
rdfs:subClassOf obo:OBI_0000070 .
obo:STATO_0000418 a rdfs:Class ;
rdfs:label "measure of heterogeneity"@en ;
rdfs:comment "a measure of heterogeneity in meta-analysis is a data item which aims to describe the variation in study outcomes between studies."@en ;
rdfs:subClassOf obo:STATO_0000028 .
obo:STATO_0000625 a rdfs:Class ;
rdfs:label "relative mean difference"@en ;
rdfs:comment """A statistic that is a difference between 1 and a ratio of the two mean values being compared.
Relative Mean Difference = 1 - ( a / b ) where a and b are mean values.
The relative mean difference can also be defined as a statistic that is a ratio of the difference in means to the reference mean value. Relative Mean Difference = ( b - a ) / ( b ) where b is the reference mean value and a is another mean value."""@en ;
rdfs:subClassOf obo:STATO_0000615 .
obo:OBI_0000010 a rdfs:Class ;
rdfs:label "fluorescent reporter intensity"@en ;
rdfs:comment "A measurement datum that represents the output of a scanner measuring the intensity value for each fluorescent reporter."@en ;
rdfs:subClassOf obo:IAO_0000109 .
obo:OBI_0200175 a rdfs:Class ;
rdfs:label "class discovery data transformation"@en ;
rdfs:comment "A class discovery data transformation (sometimes called unsupervised classification) is a data transformation that has objective class discovery."@en ;
rdfs:subClassOf obo:APOLLO_SV_00000796 , obo:OBI_0200000 .
obo:STATO_0000507 a rdfs:Class ;
rdfs:label "probability-proportional-to-size sampling"@en ;
rdfs:comment "Probability proportional to size ('PPS') sampling is a sampling method in which the selection probability for each element is set to be proportional to its size measure, up to a maximum of 1. In a simple PPS design, these selection probabilities can then be used as the basis for Poisson sampling. However, this has the drawback of variable sample size, and different portions of the population may still be over- or under-represented due to chance variation in selections."@en ;
rdfs:subClassOf obo:STATO_0000502 .
obo:BFO_0000003 a rdfs:Class ;
rdfs:label "occurrent"@en ;
rdfs:comment "An entity that has temporal parts and that happens, unfolds or develops through time."@en ;
rdfs:subClassOf obo:BFO_0000001 .
obo:STATO_0000575 a rdfs:Class ;
rdfs:label "non-iterative Partial Least Squares"@en ;
rdfs:comment "a data transformation which finds principal component by applying non-linear iterative partial least squares algorithm" ;
rdfs:subClassOf obo:OBI_0200000 .
obo:CHEBI_33250 a rdfs:Class ;
rdfs:label "atom" ;
rdfs:comment "A chemical entity constituting the smallest component of an element having the chemical properties of the element." ;
rdfs:subClassOf obo:BFO_0000040 .
obo:STATO_0000429 a rdfs:Class ;
rdfs:label "DerSimonian-Laird estimator"@en ;
rdfs:comment "DerSimonian-Laird estimator s a data item computed to estimate heterogeneity parameter (estimate of between-study variance) in a random effect model for meta analysis. The estimator is used in simple noniterative procedure for characterizing the distribution of treatment effects in a series of studies"@en ;
rdfs:subClassOf obo:STATO_0000471 .
obo:STATO_0000286 a rdfs:Class ;
rdfs:label "one tailed test"@en ;
rdfs:comment """a one-tailed test is a statistical test which, assuming an unskewed probability distribution, allocates all of the significance level to evaluate only one hypothesis to explain a difference.
The one-tailed test provides more power to detect an effect in one direction by not testing the effect in the other direction.
one-tailed test should be preceded by two-tailed test in order to avoid missing out on detecting alternate effect explaining an observed difference."""@en ;
rdfs:subClassOf obo:OBI_0000673 , obo:OBI_0200000 .
obo:CHEBI_16991 a rdfs:Class ;
rdfs:label "deoxyribonucleic acid" ;
rdfs:comment "High molecular weight, linear polymers, composed of nucleotides containing deoxyribose and linked by phosphodiester bonds; DNA contain the genetic information of organisms." ;
rdfs:subClassOf obo:CHEBI_33696 .
obo:STATO_0000681 a rdfs:Class ;
rdfs:label "standardized incidence ratio"@en ;
rdfs:comment "An incidence rate ratio in which the numerator is the incidence rate in a group and the denominator is the incidence rate for a reference population."@en ;
rdfs:subClassOf obo:STATO_0000680 .
obo:STATO_0000649 a rdfs:Class ;
rdfs:label "standard error of the difference between independent proportions"@en ;
rdfs:comment """A measure of dispersion applied to differences between proportions arising from independent groups across hypothetical repeated random samples.
A standard error is used to quantify the uncertainty around a statistical estimate due to random sampling error."""@en ;
rdfs:seeAlso ;
rdfs:subClassOf obo:STATO_0000562 .
obo:STATO_0000695 a rdfs:Class ;
rdfs:label "precision-recall curve" ;
rdfs:comment """The precision-recall curve is a graph which plots the sensitivity or recall on the X-axis and the precision on the Y-axis.
The precision-recall curves focuses on the trade-off between Precision and Recall at various thresholds. It also highlights the performance of the model for the positive class (often the minority or more important class).
It is particularly suited for for imbalanced datasets where the positive class is rare.
The PR-curve is more sensitive to class imbalance. As precision drops significantly if the model predicts too many false positives, it makesthe PR-curve better for evaluating performance on imbalanced datasets.""" ;
rdfs:subClassOf obo:IAO_0000038 .
obo:STATO_0000320 a rdfs:Class ;
rdfs:label "Glass's delta"@en ;
rdfs:comment "Glass's delta is an estimator of effect size which is similar to Cohen's d but where the denominator corresponds only to the standard deviation of the control group (or second group). It is considered less biais than the Cohen's d for estimating effect sizes based on means and distances between means."@en ;
rdfs:subClassOf obo:STATO_0000100 .
obo:NCBITaxon_33213 a rdfs:Class ;
rdfs:label "Bilateria" ;
rdfs:subClassOf obo:NCBITaxon_33154 .
obo:STATO_0000209 a rdfs:Class ;
rdfs:label "area under curve"@en ;
rdfs:comment "area under curve is a measurement datum which corresponds to the surface define by the x-axis and bound by the line graph represented in a 2 dimensional plot resulting from an integration or integrative calculus. The interpretation of this measurement datum depends on the variables plotted in the graph"@en ;
rdfs:subClassOf obo:STATO_0000039 .
obo:OBI_0200178 a rdfs:Class ;
rdfs:label "class discovery objective"@en ;
rdfs:comment "A class discovery objective (sometimes called unsupervised classification) is a data transformation objective where the aim is to organize input data (typically vectors of attributes) into classes, where the number of classes and their specifications are not known a priori. Depending on usage, the class assignment can be definite or probabilistic."@en ;
rdfs:subClassOf obo:OBI_0200166 .
obo:STATO_0000057 a rdfs:Class ;
rdfs:label "null hypothesis"@en ;
rdfs:comment """A null hypothesis is a statistical hypothesis that is tested for possible rejection under the assumption that it is true (usually that observations are the result of chance). The concept was introduced by R. A. Fisher.
The hypothesis contrary to the null hypothesis, usually that the observations are the result of a real effect, is known as the alternative hypothesis.[wolfram alpha]"""@en ;
rdfs:subClassOf obo:STATO_0000065 .
obo:STATO_0000007 a rdfs:Class ;
rdfs:label "axis"@en ;
rdfs:comment "an axis is a line graph used as reference line for the measurement of coordinates."@en ;
rdfs:subClassOf obo:IAO_0000573 .
obo:STATO_0000638 a rdfs:Class ;
rdfs:label "number needed to harm" ;
rdfs:comment "A statistic that represents the number of units that, if treated or exposed to the intervention, lead to one additional undesired outcome. The Number Needed to Harm is calculated as the reciprocal of a treatment effect estimate, where the effect estimate is expressed as a risk difference." ;
rdfs:subClassOf obo:STATO_0000634 .
obo:STATO_0000589 a rdfs:Class ;
rdfs:label "TPM-transcript per million" ;
rdfs:comment """TPM, which stands for Transcript Per Million, is a data item produced during a normilization procedure of RNA-Seq data (i.e. transcription profiling reads produced by nucleic acid sequencing) and corresponds to the count per length of transcript (kb) per million reads mapped.
-TPM considers the gene length and sequencing depth for normalization
-TPM proposed as an alternative to RPKM due to inaccuracy in RPKM measurement (Wagner et al., 2012)
-TPM is suitable for sequencing protocols where reads sequencing depends on gene length
-TPM is RPKM scaled by a constant to make sure the sum of all values is 1 million.
-TPM (transcript per million) = 1,000,000*θi/(ℓi*c), where c is a constant value, sum_[j](θj/ℓj), sum_[i]TPM=1,000,000
Recommended use:
-TPM measure is suited for gene count comparisons within a sample or between samples of the same sample group.
-TPM measure is NOT suited for Differential Expression analysis.""" ;
rdfs:subClassOf obo:STATO_0000047 .
obo:BFO_0000018 a rdfs:Class ;
rdfs:label "zero-dimensional spatial region"@en ;
rdfs:subClassOf obo:BFO_0000006 .
obo:STATO_0000670 a rdfs:Class ;
rdfs:label "incidence rate"@en ;
rdfs:comment "A rate in which the number of new events per total at risk is divided by an interval of time."@en ;
rdfs:subClassOf obo:STATO_0000645 .
obo:OBI_0000750 a rdfs:Class ;
rdfs:label "study design independent variable"@en ;
rdfs:comment "a directive information entity that is part of a study design. Independent variables are entities whose values are selected to determine its relationship to an observed phenomenon (the dependent variable). In such an experiment, an attempt is made to find evidence that the values of the independent variable determine the values of the dependent variable (that which is being measured). The independent variable can be changed as required, and its values do not represent a problem requiring explanation in an analysis, but are taken simply as given. The dependent variable on the other hand, usually cannot be directly controlled"@en ;
rdfs:subClassOf obo:IAO_0000033 , obo:STATO_0000258 .
obo:OBI_0000372 a rdfs:Class ;
rdfs:label "material separation function"@en ;
rdfs:comment "A material separation function is a function that increases the resolution between two or more material entities. The to distinction between the entities is usually based on some associated physical quality."@en ;
rdfs:subClassOf obo:BFO_0000034 .
obo:OBI_0200104 a rdfs:Class ;
rdfs:label "principal component regression"@en ;
rdfs:comment "The Principal Component Regression method is a regression analysis method that combines the Principal Component Analysis (PCA)spectral decomposition with an Inverse Least Squares (ILS) regression method to create a quantitative model for complex samples. Unlike quantitation methods based directly on Beer's Law which attempt to calculate the absorbtivity coefficients for the constituents of interest from a direct regression of the constituent concentrations onto the spectroscopic responses, the PCR method regresses the concentrations on the PCA scores."@en ;
rdfs:subClassOf obo:APOLLO_SV_00000796 , obo:OBI_0200102 , obo:OBI_0200175 .
obo:CHEBI_33697 a rdfs:Class ;
rdfs:label "ribonucleic acid" ;
rdfs:comment "High molecular weight, linear polymers, composed of nucleotides containing ribose and linked by phosphodiester bonds; RNA is central to the synthesis of proteins." ;
rdfs:subClassOf obo:CHEBI_33696 .
obo:STATO_0000103 a rdfs:Class ;
rdfs:label "multinomial distribution"@en ;
rdfs:comment "the multinomial distribution is a probability distribution which gives the probability of any particular combination of numbers of successes for various categories defined in the context of n independent trials each of which leads to a success for exactly one of k categories, with each category having a given fixed success probability."@en ;
rdfs:subClassOf obo:STATO_0000117 .
obo:OBI_0600005 a rdfs:Class ;
rdfs:label "collecting specimen from organism"@en ;
rdfs:comment "a process with the objective to obtain a material entity that was part of an organism for potential future use in an investigation"@en ;
rdfs:subClassOf obo:OBI_0000659 .
obo:OBI_0001977 a rdfs:Class ;
rdfs:label "cytometry assay" ;
rdfs:comment "An assay that counts and/or measures characteristics of cells." ;
rdfs:subClassOf obo:OBI_0000070 .
obo:STATO_0000175 a rdfs:Class ;
rdfs:label "confidence interval calculation"@en ;
rdfs:comment "confidence interval calculation is a data transformation which determines a confidence interval for a given statistical parameter"@en ;
rdfs:subClassOf obo:OBI_0200000 .
obo:STATO_0000118 a rdfs:Class ;
rdfs:label "ranking"@en ;
rdfs:comment "ranking is a data transformation which turns a non-ordinal variable into a Ordinal variable by sorting the values of the input variable and replacing their value by their position in the sorting result"@en ;
rdfs:subClassOf obo:OBI_0200000 .
obo:STATO_0000333 a rdfs:Class ;
rdfs:label "kernel mixture distribution"@en ;
rdfs:comment "kernel density estimation (KDE) is a non-parametric way to estimate the probability density function of a random variable"@en ;
rdfs:subClassOf obo:STATO_0000225 .
obo:STATO_0000565 a rdfs:Class ;
rdfs:label "regression coefficient" ;
rdfs:comment """a regression coefficient is a measure of association that is used as the coefficient of an independent variable in a regression model, of the dependent variable, which is linear in its parameters.
A value of zero means no association. The sign (positive or negative) reflects the direction of association.
a regression coefficient is a measure of association generated by a type of data transformation called a regression, which aims to model a response variable by expression the predictor variables as part of a function where variable terms are modified by a number. A regression coefficient is one such number."""@en ;
rdfs:subClassOf obo:STATO_0000610 .
obo:PATO_0001300 a rdfs:Class ;
rdfs:label "optical quality" ;
rdfs:comment "An EM radiation quality in which the EM radiation is within the fiat range of the spectrum visible deemed to be light." ;
rdfs:subClassOf obo:PATO_0001291 .
obo:STATO_0000248 a rdfs:Class ;
rdfs:label "blocking variable"@en ;
rdfs:comment "a blocking variable is a independent variable which is used in a blocking process part of an experiment with the purpose of maximizing the signal coming from the main variable." ;
rdfs:subClassOf obo:BFO_0000017 , obo:STATO_0000258 .
obo:STATO_0000502 a rdfs:Class ;
rdfs:label "statistical sampling" ;
rdfs:comment "statistical sampling is a planned process which aims at assembling a population of observation units (samples) in as an unbiaised manner as possible in order to obtain or infer information about the actual population these samples have been drawn." ;
rdfs:subClassOf obo:OBI_0000011 .
obo:OBI_0100051 a rdfs:Class ;
rdfs:label "specimen"@en ;
rdfs:comment "A material entity that has the specimen role."@en ;
rdfs:subClassOf obo:BFO_0000040 .
obo:STATO_0000480 a rdfs:Class ;
rdfs:label "ridge regression best linear unbiaised predictor" ;
rdfs:comment "RR-BLUP is a data transformation used in the context of estimating breeding value using a Bayesian ridge regression. It can be obtained from Bayes B procedure by setting pi parameter to zero ( ) and assuming that all the markers have the same variance." ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000119 , obo:STATO_0000337 .
obo:STATO_0000229 a rdfs:Class ;
rdfs:label "Chi-square probability distribution"@en ;
rdfs:comment "Chi-square probability distribution with k degrees of freedom is a theoretical probability distribution which corresponds to the distribution of a sum of the squares of k independent standard normal random variables." ;
rdfs:subClassOf obo:STATO_0000067 .
obo:STATO_0000398 a rdfs:Class ;
rdfs:label "weighted arithmetic mean"@en ;
rdfs:comment """The weighted arithmetic mean is a measure of central tendency that is the sum of the products of each observed value and their respective non-negative weights, divided by the sum of the weights, such that the contribution of each observed value to the mean may defer according to its respective weight. It is defined by the formula: A = sum(vi*wi)/sum(wi), where 'i' ranges from 1 to n, 'vi' is the value of each observation, and 'wi' is the value of the respective weight for each observed value.
The weighted arithmetic mean is a kind of mean similar to an ordinary arithmetic mean (the most common type of average), except that instead of each of the data points contributing equally to the final average, some data points are weighted, meaning they contribute more than others.
The weighted arithmetic mean is often used if one wants to combine average values from samples of the same population with different sample sizes."""@en ;
rdfs:subClassOf obo:STATO_0000029 .
obo:OBI_0000451 a rdfs:Class ;
rdfs:label "normalized data set"@en ;
rdfs:comment "A data set that is produced as the output of a normalization data transformation."@en ;
rdfs:subClassOf obo:IAO_0000100 .
obo:STATO_0000159 a rdfs:Class ;
rdfs:label "stacked bar chart" ;
rdfs:comment "Stacked bar chart is a bar which is used to compare overall quantities across items while showing the contribution of category to the total amount. Stacked bar chart can be used for highlighting the total as they visually aggregate all of the categories in a group while indicating a part to whole relationship. The downside is that it becomes harder to compare the sizes of the individual categories."@en ;
rdfs:subClassOf obo:STATO_0000166 .
obo:STATO_0000050 a rdfs:Class ;
rdfs:label "signal to noise ratio"@en ;
rdfs:comment "signal to noise ratio is a measurement datum comparing the amount of meaningful, useful or interesting data (the signal) to the amount of irrelevant or false data (the noise). Depending on the field and domain of application, different variables will be used to determinate a 'signal to noise ratio'. In statistics, the definition of signal to noise ratio is the ratio of the mean of a measurement to its standard deviation. It thus corresponds to the inverse of the coefficient of variation"@en ;
rdfs:subClassOf obo:STATO_0000184 .
obo:STATO_0000435 a rdfs:Class ;
rdfs:label "probability distribution scale parameter"@en ;
rdfs:comment "a probability distribution scale parameter is a measure of variation which is set by the operator when selecting a parametric probability distribution and which defines how spread the distribution is. The larger the value of the scale parameter is, the more spread out the distribution."@en ;
rdfs:subClassOf obo:STATO_0000028 , obo:STATO_0000742 .
obo:OBI_0500015 a rdfs:Class ;
rdfs:label "2x2 factorial design"@en ;
rdfs:comment "a factorial design which has 2 experimental factors (aka independent variables) and 2 factor levels per experimental factors"@en ;
rdfs:subClassOf obo:OBI_0500014 , obo:STATO_0000270 .
obo:STATO_0000119 a rdfs:Class ;
rdfs:label "model parameter estimation"@en ;
rdfs:comment "model parameter estimation is a data transformation that finds parameter values (the model parameter estimates) most compatible with the data as judged by the model."@en ;
rdfs:subClassOf obo:OBI_0200000 .
obo:STATO_0000061 a rdfs:Class ;
rdfs:label "absence of between group difference hypothesis"@en ;
rdfs:comment "It is a null hypothesis stating that there are no differences observed between group of subjects."@en ;
rdfs:subClassOf obo:STATO_0000065 .
obo:UO_0000002 a rdfs:Class ;
rdfs:label "mass unit" ;
rdfs:comment "A unit which is a standard measure of the amount of matter/energy of a physical object." ;
rdfs:subClassOf obo:IAO_0000003 .
obo:STATO_0000407 a rdfs:Class ;
rdfs:label "Fagan nomogram"@en ;
rdfs:comment """Fagan nomogram is a graph plotting pre-test probabilities, likelyhood ratios and post-test probabilities on 3 parallel axis. The plot was first proposed by Fagan in 1975 as a way to visualize Baye's Theorem data where
P(D) is the probability that the patient has the disease before the test. P(D|T) is the probability that the patient has the disease after the test result. P(T|D) is the probability of the test result if the patient has the disease, and P(T|D̄) is the probability of the test result if the patient does not have the disease. With this terminology the usefulness of both positive and negative test results can be assessed. A line drawn from P(D) on the right through the ratio of P(T|D) to P(T|D̄) gives P(D|T) on the left of the nomogram."""@en ;
rdfs:subClassOf obo:IAO_0000038 .
obo:STATO_0000725 a rdfs:Class ;
rdfs:label "dichotomous ordinal variable" ;
rdfs:comment "An ordinal variable which is defined to have only 2 categories or possible values." ;
rdfs:subClassOf obo:STATO_0000090 , obo:STATO_0000228 , obo:STATO_0000252 , obo:STATO_0000726 .
obo:OBI_0000456 a rdfs:Class ;
rdfs:label "material transformation objective"@en ;
rdfs:comment "an objective specifiction that creates an specific output object from input materials."@en ;
rdfs:subClassOf obo:IAO_0000005 .
obo:STATO_0000447 a rdfs:Class ;
rdfs:label "whole plot number"@en ;
rdfs:comment """a 'whole plot number' is a data item used to count and identify the actual piece of land (in the case of real field based trials) used in a split plot design experiment and receiving treatments corresponding to the levels of a factor whose randomization is restricted (these factors are known as 'hard to change' factors).
In the case of non-field based trials, the 'whole plot' is a metaphor."""@en ;
rdfs:subClassOf obo:IAO_0000027 .
obo:STATO_0000710 a rdfs:Class ;
rdfs:label "non-inferiority margin"@en ;
rdfs:comment "hypothesis testing margin used in a study with a non-inferiority goal." ;
rdfs:subClassOf obo:STATO_0000709 .
obo:OBI_0000257 a rdfs:Class ;
rdfs:label "DNA extraction"@en ;
rdfs:comment "A DNA extraction is a nucleic acid extraction where the desired output material is DNA."@en ;
rdfs:subClassOf obo:OBI_0666667 .
obo:STATO_0000317 a rdfs:Class ;
rdfs:label "eta-squared"@en ;
rdfs:comment "Eta-squared is a biased estimator of the variance explained by the model in the population (it estimates only the effect size in the sample). Eta-squared describes the ratio of variance explained in the dependent variable by a predictor while controlling for other predictors, making it analogous to the r2. This estimate shares the weakness with r2 that each additional variable will automatically increase the value of η2. In addition, it measures the variance explained of the sample, not the population, meaning that it will always overestimate the effect size, although the bias grows smaller as the sample grows larger."@en ;
rdfs:subClassOf obo:STATO_0000085 , obo:STATO_0000471 .
obo:STATO_0000237 a rdfs:Class ;
rdfs:label "standard deviation"@en ;
rdfs:comment "The standard deviation of a random variable, statistical population, data set, or probability distribution is a measure of variation which correspond to the average distance from the mean of the data set to any given point of that dataset. It also corresponds to the square root of its variance."@en ;
rdfs:subClassOf obo:STATO_0000028 .
obo:OBI_0400079 a rdfs:Class ;
rdfs:label "optical filter"@en ;
rdfs:comment "An optical filter is an optical subsystem that selectively transmits light having certain properties (often, a particular range of wavelengths, that is, range of colours of light), while blocking the remainder. They are commonly used in photography, in many optical instruments, and to colour stage lighting Optical filters can be arranged to segregate and collect light by wave length."@en ;
rdfs:subClassOf obo:OBI_0000932 .
obo:OBI_0000652 a rdfs:Class ;
rdfs:label "material combination" ;
rdfs:comment "is a material processing with the objective to combine two or more material entities as input into a single material entity as output." ;
rdfs:subClassOf obo:OBI_0000094 .
obo:STATO_0000586 a rdfs:Class ;
rdfs:label "restricted randomized design"@en ;
rdfs:comment "a restricted randomized design is a kind of study design which uses randomization to allocate observation unit to treatment but where intuitively poor allocations of treatments to experimental units are avoided, while retaining the theoretical benefits of randomization. This is often the case when so-called 'hard to change' factors are used in an experimental design."@en ;
rdfs:subClassOf obo:BFO_0000017 , obo:OBI_0500000 , obo:STATO_0000046 .
obo:STATO_0000425 a rdfs:Class ;
rdfs:label "Sidik-Jonkman estimator"@en ;
rdfs:comment "Sidik-Jonkman estimator is a data item computed to estimate heterogeneity parameter (estimate of between-study variance) in a random effect model for meta analysis."@en ;
rdfs:subClassOf obo:STATO_0000471 .
obo:STATO_0000554 a rdfs:Class ;
rdfs:label "number of cross-validation segments" ;
rdfs:comment "number of cross-validation segments is a count which is used as input parameter in a cross validation procedure to evaluate a statistical model." ;
rdfs:subClassOf obo:STATO_0000047 .
obo:STATO_0000572 a rdfs:Class ;
rdfs:label "Partial Least Square Discriminant Analysis"@en ;
rdfs:comment "a version of PLS used for classification, where the input y-block are group labels (categorical variable) rather than a continuous variable"@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:OBI_0200175 .
obo:OBI_0200078 a rdfs:Class ;
rdfs:label "descriptive statistical calculation objective"@en ;
rdfs:comment "A descriptive statistical calculation objective is a data transformation objective which concerns any calculation intended to describe a feature of a data set, for example, its center or its variability."@en ;
rdfs:subClassOf obo:OBI_0200166 .
obo:OBI_0000650 a rdfs:Class ;
rdfs:label "differential expression analysis data transformation"@en ;
rdfs:comment "A differential expression analysis data transformation is a data transformation that has an objective of differential expression analysis. Frequently this data transformation involves summarizing or otherwise aggregating signals from various samples categorized into groups, and calculating measures of group differences from these aggregated signals."@en ;
rdfs:subClassOf obo:OBI_0200000 .
obo:STATO_0000446 a rdfs:Class ;
rdfs:label "restricted randomization"@en ;
rdfs:comment """Restricted randomization is a kind of randomization which is used or occured when hard to change factors exist in a study design. In other words, when complete randomization is not possible, a case of restricted randomization exists, for instance in the case of split-plot design.
Restricted randomization allows intuitively poor allocations of treatments to experimental units to be avoided, while retaining the theoretical benefits of randomization.
Restricted randomization can also result from an unplanned event and is then something that should be avoided. RandomizeR R package can be used to detect such events and assess the quality of randomization process."""@en ;
rdfs:subClassOf obo:OBI_0302900 .
obo:STATO_0000583 a rdfs:Class ;
rdfs:label "completely randomized design" ;
rdfs:comment """a completely randomized design is a type of design of experiment where the observation unit receive treatments (independent variable level) entirely at random. In other words, the observations unit are randomly assigned to treatments.
Completely randomized designs differ from randomized complete block design and should not be confused as in the latter, a blocking variable is first use to assign experimental units to blocks. Then only, the members of each block are then randomly assigned to different treatment groups""" ;
rdfs:subClassOf obo:BFO_0000017 , obo:OBI_0500000 .
obo:STATO_0000080 a rdfs:Class ;
rdfs:label "Brown Forsythe test"@en ;
rdfs:comment """the Brown Forsythe test is a statistical test which evaluates if the variance of different groups are equal. It relies on computing the median rather than the mean, as used in the Levene's test for homoschedacity.
This test maybe used to, for instance, ensure that the conditions of applications of ANOVA are met."""@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000137 .
obo:STATO_0000548 a rdfs:Class ;
rdfs:label "sampling distribution estimation by bootstrapping" ;
rdfs:comment "Bootstrapping is the practice of estimating properties of an estimator (such as its variance) by measuring those properties when sampling from an approximating distribution." ;
rdfs:subClassOf obo:STATO_0000535 .
obo:STATO_0000414 a rdfs:Class ;
rdfs:label "mortality"@en ;
rdfs:comment "mortality is a ratio formed by the number of deaths due to a disease divided by the total population size."@en ;
rdfs:subClassOf obo:STATO_0000184 .
obo:OBI_0000319 a rdfs:Class ;
rdfs:label "material to be added role"@en ;
rdfs:comment "material to be added role is a protocol participant role realized by a material which is added into a material bearing the target of material addition role in a material addition process"@en ;
rdfs:subClassOf obo:BFO_0000023 .
obo:STATO_0000076 a rdfs:Class ;
rdfs:label "Mann-Whitney U-test"@en ;
rdfs:comment """The Mann-Whitney U-test is a null hypothesis statistical testing procedure which allows two groups (or conditions or treatments) to be compared without making the assumption that values are normally distributed.
The Mann-Whitney test is the non-parametric equivalent of the t-test for independent samples"""@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000198 .
obo:BFO_0000031 a rdfs:Class ;
rdfs:label "generically dependent continuant"@en ;
rdfs:comment "A continuant that is dependent on one or other independent continuant bearers. For every instance of A requires some instance of (an independent continuant type) B but which instance of B serves can change from time to time."@en ;
rdfs:subClassOf obo:BFO_0000002 .
obo:OBI_0000067 a rdfs:Class ;
rdfs:label "evaluant role"@en ;
rdfs:comment "a role that inheres in a material entity that is realized in an assay in which data is generated about the bearer of the evaluant role"@en ;
rdfs:subClassOf obo:BFO_0000023 .
obo:STATO_0000264 a rdfs:Class ;
rdfs:label "factor level combination"@en ;
rdfs:comment "a factor level combination is one a possible sets of factor levels resulting from the cartesian product of sets of factor and their levels as defined in a factorial design"@en ;
rdfs:subClassOf obo:IAO_0000100 .
obo:STATO_0000210 a rdfs:Class ;
rdfs:label "channel1/channel2 fluorescence intensity ratio"@en ;
rdfs:comment "is a data item formed by dividing the fluorescence intensity obtained in one channel to that obtained in the other channel, typically the case when considering 2-color microarray data when imaging is done for Cy3 and Cy5 dyes."@en ;
rdfs:subClassOf obo:STATO_0000169 .
obo:OBI_0200000 a rdfs:Class ;
rdfs:label "data transformation"@en ;
rdfs:comment "A planned process that produces output data from input data."@en ;
rdfs:subClassOf obo:OBI_0000011 .
obo:STATO_0000709 a rdfs:Class ;
rdfs:label "testing margin" ;
rdfs:comment "a prespecified threshold that distinguishes between a null and alternative hypothesis." ;
rdfs:subClassOf obo:STATO_0000633 .
obo:STATO_0000431 a rdfs:Class ;
rdfs:label "meta analysis by DerSimonian and Leard method"@en ;
rdfs:comment "a meta analysis which relies on the computation of the DerSimonian and Leard estimator as a measure of heterogeneity over a set of studies."@en ;
rdfs:subClassOf obo:STATO_0000155 .
obo:OBI_0002744 a rdfs:Class ;
rdfs:label "molecular label"@en ;
rdfs:comment "A molecular reagent intended to associate with some molecular target to serve as a proxy for the presence, abundance, or location of this target in a detection of molecular label assay"@en ;
rdfs:subClassOf obo:CHEBI_23367 , obo:OBI_0001879 .
obo:STATO_0000721 a rdfs:Class ;
rdfs:label "nominal variable" ;
rdfs:comment "A categorical variable for which the meanings of the categories do not have an ordered relationship." ;
rdfs:subClassOf obo:STATO_0000252 .
obo:STATO_0000535 a rdfs:Class ;
rdfs:label "sampling from a probability distribution" ;
rdfs:comment "sampling from a probability distribution is a data transformation which aims at obtaining a sequence of random samples from a probability distribution for which direct sampling is difficult." ;
rdfs:subClassOf obo:OBI_0200000 .
obo:STATO_0000654 a rdfs:Class ;
rdfs:label "paired observation comparison objective" ;
rdfs:comment "the objective of a data transformation to test a null hypothesis of absence of difference within subject holds." ;
rdfs:subClassOf obo:OBI_0000675 .
obo:STATO_0000478 a rdfs:Class ;
rdfs:label "pedigree data set"@en ;
rdfs:comment "a dataset which is made up of pedigree information, that is presenting ancestry or lineage information in a set of individuals of an organism."@en ;
rdfs:subClassOf obo:IAO_0000100 .
obo:STATO_0000130 a rdfs:Class ;
rdfs:label "Breslow-Day test for homogeneity of odds ratio"@en ;
rdfs:comment "the Breslow-Day test is a statistical test which evaluates if the odds ratios are homogenous across N 2x2 contingency tables, for instance several 2x2 contingency tables associated with different strata of a stratified population when evaluating the relationship between exposure and outcome or associated with the different samples coming from several centres in a multicentric study in clinical trial context."@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000247 , obo:STATO_0000697 .
obo:STATO_0000489 a rdfs:Class ;
rdfs:label "additive dominant genetic and epistatic inheritance model"@en ;
rdfs:comment "an additive genetic model is a data item which refer to the contributions to the final phenotype from more than one gene, or from alleles of a single gene (in heterozygotes), that combine in such a way that the sum of their effects in unison is equal to the sum of their individual effect, their additive dominant (effect (of alleles at a single locus) and their epistasic effect (of alleles at more different loci)."@en ;
rdfs:subClassOf obo:STATO_0000534 .
obo:IAO_0000579 a rdfs:Class ;
rdfs:label "centrally registered identifier registry"@en ;
rdfs:comment "A CRID registry is a dataset of CRID records, each consisting of a CRID symbol and additional information which was recorded in the dataset through a assigning a centrally registered identifier process."@en ;
rdfs:subClassOf obo:IAO_0000100 .
obo:STATO_0000091 a rdfs:Class ;
rdfs:label "genome-wide association study"@en ;
rdfs:comment "Genome wide association study is a kind of study whose objective is to detect association between genetic markers (SNP or otherwise) accross the genome and a trait which may be a disease or another phenotype (e.g. trait of agronomic relevance in animal or plant studies). Genome wide association study compare the allele frequencies in 2 populations, one free of the trait used as control, the other one showing the trait use as 'case'. GWAS studies implement case-control design"@en ;
rdfs:subClassOf obo:STATO_0000235 .
obo:STATO_0000089 a rdfs:Class ;
rdfs:label "case-control study design"@en ;
rdfs:comment "a case-control study design is a observation study design which assess the risk of particular outcome (a trait or a disease) associated with an event (either an exposure or endogenous factor). A case-control study design therefore declares an exposure variable which is dichotomous in nature (exposed/non-exposed) and an outcome variable, which is also dichotomous (case or control), thus giving the name to the design. During the execution of the design, a case control study defines a population and counts the events to determine their frequency."@en ;
rdfs:subClassOf obo:OBI_0500006 .
a rdfs:Class ;
rdfs:comment "An unconstrained type or object" .
obo:STATO_0000383 a rdfs:Class ;
rdfs:label "contrast estimation"@en ;
rdfs:comment "a data transformation that finds a contrast value (the contrast estimate) by computing the weighted sum of model parameter estimates using a set of contrast weights."@en ;
rdfs:subClassOf obo:OBI_0200000 .
obo:IAO_0000005 a rdfs:Class ;
rdfs:label "objective specification"@en ;
rdfs:comment "A directive information entity that describes an intended process endpoint. When part of a plan specification the concretization is realized in a planned process in which the bearer tries to effect the world so that the process endpoint is achieved."@en ;
rdfs:subClassOf obo:IAO_0000033 .
obo:OBI_0000071 a rdfs:Class ;
rdfs:label "quantitative confidence value"@en ;
rdfs:comment "A data item which is used to indicate the degree of uncertainty about a measurement."@en ;
rdfs:subClassOf obo:STATO_0000609 .
obo:STATO_0000569 a rdfs:Class ;
rdfs:label "score"@en ;
rdfs:comment "The score indicates how sensitive a likelihood function L(\\Theta,X) is to its parameter \\Theta. Explicitly, the score for \\Theta is the gradient of the log-likelihood with respect to \\Theta."@en ;
rdfs:subClassOf obo:OBI_0000648 , obo:STATO_0000039 .
obo:STATO_0000648 a rdfs:Class ;
rdfs:label "standard error of the difference between independent means"@en ;
rdfs:comment """A measure of dispersion applied to differences between means of independent groups across hypothetical repeated random samples.
A standard error is used to quantify the uncertainty around a statistical estimate due to random sampling error."""@en ;
rdfs:seeAlso ;
rdfs:subClassOf obo:STATO_0000562 .
obo:OBI_0000811 a rdfs:Class ;
rdfs:label "primary structure of DNA macromolecule" ;
rdfs:comment "a quality of a DNA molecule that inheres in its bearer due to the order of its DNA nucleotide residues." ;
rdfs:subClassOf obo:SO_0000001 .
obo:OBI_0000791 a rdfs:Class ;
rdfs:label "multiple testing correction objective" ;
rdfs:comment "A multiple testing correction objectives is a data transformation objective where the aim is to correct for a set of statistical inferences considered simultaneously" ;
rdfs:subClassOf obo:OBI_0200186 .
obo:STATO_0000340 a rdfs:Class ;
rdfs:label "breeding value estimation using phenotypic data"@en ;
rdfs:comment "breeding value estimation is a data transformation process aiming at computing breeding value estimates of an organism given a set of phenotypic observations." ;
rdfs:subClassOf obo:STATO_0000337 .
obo:STATO_0000394 a rdfs:Class ;
rdfs:label "Pareto type-III probability distribution"@en ;
rdfs:comment """The Pareto(III) distribution is a continous probability distribution which is described with a cumulative distribution function of the following form:
F(x) = 1 − [1 + ((x − mu)/sigma)1/gamma]−1
for x > mu, sigma > 0, gamma > 0 and s =1.
a is the location parameter,
b is the scale parameter,
g is the inequality parameter
s is the shape parameter of value 1
The Pareto III distribution corresponds to a Pareto Type IV distribution where the shape parameter has a value of 1."""@en ;
rdfs:subClassOf obo:STATO_0000067 .
obo:OBI_0000727 a rdfs:Class ;
rdfs:label "k-nearest neighbors"@en ;
rdfs:comment "A k-nearest neighbors is a data transformation which achieves a class discovery or partitioning objective, in which an input data object with vector y is assigned to a class label based upon the k closest training data set points to y; where k is the largest value that class label is assigned."@en ;
rdfs:subClassOf obo:APOLLO_SV_00000796 , obo:OBI_0200171 , obo:OBI_0200175 .
obo:OBI_0200045 a rdfs:Class ;
rdfs:label "single linkage hierarchical clustering"@en ;
rdfs:comment "A single linkage hierarchical clustering is an agglomerative hierarchical clustering which generates successive clusters based on a distance measure, where the distance between two clusters is calculated as the minimum distance between objects from the first cluster and objects from the second cluster."@en ;
rdfs:subClassOf obo:OBI_0200154 .
obo:STATO_0000302 a rdfs:Class ;
rdfs:label "one sample t-test"@en ;
rdfs:comment """one sample t-test is a kind of Student's t-test which evaluates if a given sample can be reasonably assumed to be taken from the population.
The test compares the sample statistic (m) to the population parameter (M).
The one sample t-test is the small sample analog of the z test, which is suitable for large samples."""@en ;
rdfs:subClassOf obo:OBI_0000739 , obo:OBI_0200000 , obo:STATO_0000279 .
obo:STATO_0000354 a rdfs:Class ;
rdfs:label "banded heterogeneous Toeplitz covariance structure"@en ;
rdfs:comment "the banded heterogeneous Toeplitz covariance structure is a type of coviance structure which is often used to analyzed and intepret repeated measure design." ;
rdfs:subClassOf obo:STATO_0000346 .
obo:STATO_0000499 a rdfs:Class ;
rdfs:label "augmented experimental design" ;
rdfs:comment """augmented design is a kind of experimental design where the goal is to compare existing (control) treatments with new treatments that have an experimental constraint of \"limited replication\". To understand limited replication, consider about experiments that may only allow a single representation of the new treatment, this limitation may be many times due to the cost associated with the experiment, limited resources, or limited number of new units that can be used in the experiment. In contrast, the existing treatments are referred as checks and are generally replicated multiple times. With augmented design one can estimate the following:
a) Differences between checks and new treatments,
b) Differences among new treatments,
c) Differences among check treatments, and
d) Differences among new and check treatments combined.""" ;
rdfs:subClassOf obo:OBI_0500000 .
obo:STATO_0000092 a rdfs:Class ;
rdfs:label "Wilcoxon signed rank test"@en ;
rdfs:comment """The Wilcoxon signed rank test is a statistical test which tests the null hypothesis that the median difference between pairs of observations is zero. This is the non-parametric analogue to the paired t-test, and should be used if the distribution of differences between pairs may be non-normally distributed.
The procedure involves a ranking, hence the name. The absolute value of the differences between observations are ranked from smallest to largest, with the smallest difference getting a rank of 1, then next larger difference getting a rank of 2, etc. Ties are given average ranks. The ranks of all differences in one direction are summed, and the ranks of all differences in the other direction are summed. The smaller of these two sums is the test statistic, W (sometimes symbolized Ts). Unlike most test statistics, smaller values of W are less likely under the null hypothesis."""@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000202 .
obo:STATO_0000484 a rdfs:Class ;
rdfs:label "Bayes B"@en ;
rdfs:comment "Bayes B is a data transformation used in the context of estimating breeding value, which relies on a Bayesian model, treats the prior probability π that a SNP has zero effect to a set value (i.e π >0) and uses a mixture distribution." ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000119 , obo:STATO_0000337 .
obo:STATO_0000643 a rdfs:Class ;
rdfs:label "variance for sample" ;
rdfs:comment "the sample variance is a variance computed over the actual observations made, which correspond to a sample drawn from a population in an experiment. the sample variance can be used to estimate the true variance of the underlying population/distribution." ;
rdfs:subClassOf obo:STATO_0000113 .
obo:OBI_0000964 a rdfs:Class ;
rdfs:label "in live cell assay" ;
rdfs:comment "An assay in which a measurement is made by observing entities located in a live cell." ;
rdfs:subClassOf obo:OBI_0000070 .
obo:OBI_0000659 a rdfs:Class ;
rdfs:label "specimen collection process" ;
rdfs:comment "A planned process with the objective of collecting a specimen." ;
rdfs:subClassOf obo:OBI_0000011 .
obo:STATO_0000078 a rdfs:Class ;
rdfs:label "Levene's test"@en ;
rdfs:comment "Levene's test is a null hypothesis statistical test which evaluates the null hypothesis of equality of variance in several populations."@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000137 , obo:STATO_0000191 .
obo:STATO_0000195 a rdfs:Class ;
rdfs:label "number of factor level combinations"@en ;
rdfs:comment "A non-negative integer defining how many combination of factor levels (or treatments in the statistical sense) are to be used in a study." ;
rdfs:subClassOf obo:STATO_0000047 .
obo:STATO_0000410 a rdfs:Class ;
rdfs:label "negative likelihood ratio"@en ;
rdfs:comment "the likelihood ratio of negative results is a ratio which is formed by dividing the difference between 1 and sensitivity of the test by the specificity value of a test. This can be expressed also as dividing the probability of a person who has the disease testing negative by the probability of a person who does not have the disease testing negative."@en ;
rdfs:subClassOf obo:STATO_0000409 .
obo:STATO_0000202 a rdfs:Class ;
rdfs:label "within subject comparison statistical test"@en ;
rdfs:comment "within subject comparison statistical test is a kind of statistical test which evaluates if a change occurs within one experimental unit over time following a treatment or an event"@en ;
rdfs:subClassOf obo:OBI_0000673 .
obo:OBI_0200119 a rdfs:Class ;
rdfs:label "median calculation"@en ;
rdfs:comment "A median calculation is a descriptive statistics calculation in which the midpoint of the data set (the 0.5 quantile) is calculated. First, the observations are sorted in increasing order. For an odd number of observations, the median is the middle value of the sorted data. For an even number of observations, the median is the average of the two middle values."@en ;
rdfs:subClassOf obo:APOLLO_SV_00000796 , obo:OBI_0200181 , obo:OBI_0200184 .
obo:STATO_0000313 a rdfs:Class ;
rdfs:label "Plackett-Burman design"@en ;
rdfs:comment """Plackett-Burman design is a type of study design optimizing multifactorial experiments characterized by their parsimony and economy with the run number a multiple of 4 (rather than a power of 2).
Plackett-Burman design is often used for screening experiments where the main effect is often heavily confounded with two-factor interactions.
This type of design is very useful for economically detecting large main effects, assuming all interactions are negligible when compared with the few important main effects."""@en ;
rdfs:subClassOf obo:OBI_0500000 .
obo:OBI_0500002 a rdfs:Class ;
rdfs:label "repeated measure design"@en ;
rdfs:comment "a study design which use the same individuals and exposure them to a set of conditions. The effect of order and practice can be confounding factor in such designs"@en ;
rdfs:subClassOf obo:OBI_0000115 , obo:OBI_0500000 .
obo:STATO_0000401 a rdfs:Class ;
rdfs:label "sample mean"@en ;
rdfs:comment """the sample mean of sample of size n with n observations is an arithmetic mean computed over n number of observations on a statistical sample.
The sample mean, denoted x¯ and read “x-bar,” is simply the average of the n data points x1, x2, ..., xn:
x¯=x1+x2+⋯+xnn=1n∑i=1nxi
The sample mean summarizes the \"location\" or \"center\" of the data.
the sample mean is a measure of dispersion of the observations made on the sample and provides an unbias estimate of the population mean"""@en ;
rdfs:subClassOf obo:STATO_0000471 , obo:STATO_0000573 .
obo:OBI_0000164 a rdfs:Class ;
rdfs:label "clonal cDNA library"@en ;
rdfs:comment """Mixed population of cDNAs (complementaryDNA) made from mRNA from a defined source, usually a specific cell type. This term should be associated only to nucleic acid interactors not to their proteins product. For instance in 2h screening use living cells (MI:0349) as sample process.
ALT DEF (PRS):: a cDNA library is a collection of host cells, typically E.Coli cells but not exclusively. modified by transfer of plasmid DNA molecule used as vector containing a fragment or totality of cDNA molecule (the insert) . cDNA library may have an array of role and applications."""@en ;
rdfs:subClassOf obo:OBI_0000731 .
obo:STATO_0000630 a rdfs:Class ;
rdfs:label "Cohen's kappa" ;
rdfs:comment "A Kappa statistic in which the expected agreement by chance is based on an assumption that the likelihood of each category for assignment is based on the proportion observed, and the number of raters is 2." ;
rdfs:subClassOf obo:STATO_0000682 .
obo:NCBITaxon_32524 a rdfs:Class ;
rdfs:label "Amniota" ;
rdfs:subClassOf obo:NCBITaxon_32523 .
obo:OBI_0000097 a rdfs:Class ;
rdfs:label "participant under investigation role"@en ;
rdfs:comment "A role that is realized through the execution of a study design in which the bearer of the role participates and in which data about that bearer is collected." ;
rdfs:subClassOf obo:BFO_0000023 .
obo:IAO_0000310 a rdfs:Class ;
rdfs:label "document"@en ;
rdfs:comment "A collection of information content entities intended to be understood together as a whole"@en ;
rdfs:subClassOf obo:IAO_0000030 .
obo:STATO_0000641 a rdfs:Class ;
rdfs:label "Friedman test" ;
rdfs:comment "The Friedman test is a non-parametric statistical test used to determine whether there are statistically significant differences among multiple related groups. It is an extension of the Wilcoxon signed-rank test for more than two related samples." ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000279 .
obo:OBI_0001225 a rdfs:Class ;
rdfs:label "genetic population background information"@en ;
rdfs:comment "a genetic characteristics information which is a part of genotype information that identifies the population of organisms"@en ;
rdfs:subClassOf obo:OBI_0001404 .
obo:STATO_0000665 a rdfs:Class ;
rdfs:label "difference in differences"@en ;
rdfs:comment "A statistic that is a subtraction of one difference from another."@en ;
rdfs:subClassOf obo:STATO_0000614 .
obo:OBI_0001143 a rdfs:Class ;
rdfs:label "labeled nucleic acid extract" ;
rdfs:comment "a labeled specimen that is the output of a labeling process and has grain labeled nucleic acid for detection of the nucleic acid in future experiments." ;
rdfs:subClassOf obo:OBI_0000924 .
obo:NCBITaxon_40674 a rdfs:Class ;
rdfs:label "Mammalia" ;
rdfs:subClassOf obo:NCBITaxon_32524 .
obo:STATO_0000609 a rdfs:Class ;
rdfs:label "measure of hypothesis testing"@en ;
rdfs:comment ""@en ;
rdfs:subClassOf obo:STATO_0000039 .
obo:OBI_0000668 a rdfs:Class ;
rdfs:label "error correction data transformation"@en ;
rdfs:comment "An error correction data transformation is a data transformation that has the objective of error correction, where the aim is to remove (correct for) erroneous contributions from the input to the data transformation."@en ;
rdfs:subClassOf obo:APOLLO_SV_00000796 , obo:OBI_0200000 .
obo:OBI_0001865 a rdfs:Class ;
rdfs:label "assay array"@en ;
rdfs:comment "A device made to be used in an analyte assay for immobilization of substances that bind the analyte at regular spatial positions on a surface." ;
rdfs:subClassOf obo:OBI_0000968 .
obo:STATO_0000141 a rdfs:Class ;
rdfs:label "acute toxicity study"@en ;
rdfs:comment "acute toxicity study is an investigation which use interventions organized according to a factorial design and a parallel group design to observe the effect of use of high dose xenobiotics in animal models or cellular models"@en ;
rdfs:subClassOf obo:OBI_0000066 .
obo:IAO_0000400 a rdfs:Class ;
rdfs:label "cartesian spatial coordinate datum"@en ;
rdfs:comment "A cartesian spatial coordinate datum is a representation of a point in a spatial region, in which equal changes in the magnitude of a coordinate value denote length qualities with the same magnitude"@en ;
rdfs:subClassOf obo:IAO_0000027 .
obo:STATO_0000442 a rdfs:Class ;
rdfs:label "Tietjen-Moore test for outliers"@en ;
rdfs:comment """Tietjen-Moore test for outlier is a statistical test used to detect outliers and corresponds to a generalization of the Grubb's test, thus allowing detection of more than one outlier in a univariate data set assumed to come from a normally distributed population.
If testing for a single outlier, the Tietjen-Moore test is equivalent to the Grubbs' test."""@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000443 .
obo:STATO_0000473 a rdfs:Class ;
rdfs:label "Kenward-Roger degree of freedom approximation"@en ;
rdfs:comment "The Kenward-Roger method's fundamental idea is to calculate the approximate mean and variance of their statistic and then match moments with an F distribution to obtain the denominator degrees of freedom."@en ;
rdfs:subClassOf obo:STATO_0000472 .
obo:NCBITaxon_10239 a rdfs:Class ;
rdfs:label "Viruses" ;
rdfs:subClassOf obo:OBI_0100026 .
obo:IAO_0000027 a rdfs:Class ;
rdfs:label "data item"@en ;
rdfs:comment "a data item is an information content entity that is intended to be a truthful statement about something (modulo, e.g., measurement precision or other systematic errors) and is constructed/acquired by a method which reliably tends to produce (approximately) truthful statements."@en ;
rdfs:subClassOf obo:IAO_0000030 .
obo:STATO_0000558 a rdfs:Class ;
rdfs:label "statistical model term testing"@en ;
rdfs:comment "A statistical model term testing is a data transformation that accounts for the evaluation of a component of a statistical model or model term."@en ;
rdfs:subClassOf obo:OBI_0200000 .
obo:STATO_0000421 a rdfs:Class ;
rdfs:label "Tau squared"@en ;
rdfs:comment "Tau-squared is an estimate of the between-study variance in a random-effects meta-analysis. The square root of this number (i.e. tau) is the estimated standard deviation of underlying effects across studies."@en ;
rdfs:subClassOf obo:STATO_0000418 .
obo:OBI_0500007 a rdfs:Class ;
rdfs:label "randomized complete block design"@en ;
rdfs:comment "A randomized complete block design is_a study design which assigns randomly treatments to block. The number of units per block equals the number of treatment so each block receives each treatment exactly once (hence the qualifier 'complete'). The design was originally devised from field trials used in agronomy and agriculture. The analysis assumes that there is no interaction between block and treatment. The method was then used in other settings So The randomised complete block design is a design in which the subjects are matched according to a variable which the experimenter wishes to control. The subjects are put into groups (blocks) of the same size as the number of treatments. The members of each block are then randomly assigned to different treatment groups."@en ;
rdfs:subClassOf obo:BFO_0000017 , obo:OBI_0000115 , obo:OBI_0500000 , obo:STATO_0000046 .
obo:STATO_0000637 a rdfs:Class ;
rdfs:label "number needed to screen to detect" ;
rdfs:comment """A statistic that represents the number of units that needs to be tested to identify one additional case. The Number Needed to Screen to Detect is calculated as the reciprocal of a difference in rate of detected cases with and without screening.
The Number Needed to Screen (NNS) value is often rounded up to the next highest whole integer. The Number Needed to Screen to Detect is distinct from the Number Needed to Screen to Prevent as the formulas to calculate are different, even though both may be abbreviated as NNS.""" ;
rdfs:subClassOf obo:STATO_0000634 .
obo:STATO_0000537 a rdfs:Class ;
rdfs:label "Metropolis–Hastings sampling" ;
rdfs:comment "the Metropolis–Hastings algorithm is a Markov chain Monte Carlo (MCMC) method for obtaining a sequence of random samples from a probability distribution for which direct sampling is difficult." ;
rdfs:subClassOf obo:STATO_0000535 .
obo:STATO_0000006 a rdfs:Class ;
rdfs:label "x-axis"@en ;
rdfs:comment "x-axis is a cartesian coordinate axis which is orthogonal to the y-axis and the z-axis"@en ;
rdfs:subClassOf obo:STATO_0000011 .
obo:NCBITaxon_2 a rdfs:Class ;
rdfs:label "Bacteria" ;
rdfs:subClassOf obo:OBI_0100026 .
obo:STATO_0000063 a rdfs:Class ;
rdfs:label "genomic coordinate datum"@en ;
rdfs:comment "genomic coordinate datum is a data item which denotes a genomic position expressed using a genomic coordinate system"@en ;
rdfs:subClassOf obo:IAO_0000027 .
obo:STATO_0000365 a rdfs:Class ;
rdfs:label "first order autoregressive covariance structure"@en ;
rdfs:comment "first order autoregressive covariance structure is a covariance structure where correlations among errors decline exponentially with distance"@en ;
rdfs:subClassOf obo:STATO_0000346 .
obo:STATO_0000328 a rdfs:Class ;
rdfs:label "statistical model selection"@en ;
rdfs:comment "A statistical model selection is a data transformation which is based on computing a relative quality value in order to evaluate and select which model best explains data."@en ;
rdfs:subClassOf obo:OBI_0200000 .
obo:STATO_0000372 a rdfs:Class ;
rdfs:label "generalized least squares estimation"@en ;
rdfs:comment "the generalized least squares estimation is a model parameter estimation for a linear regression model with errors that are dependent and (possibly) have heterogeneous variance. Difficult to use use in practice, as covariance matrix of the errors must known to \"whiten\" data and model. If true covariance is known, it is the Best Linear Unbiased Estimation (BLUE) method under these assumptions, Uniformly Minimum-Variance Unbiased Estimator (UMVUE) with addition of a Gaussian assumption."@en ;
rdfs:subClassOf obo:STATO_0000119 .
obo:OBI_0000086 a rdfs:Class ;
rdfs:label "reagent role"@en ;
rdfs:comment "A role inhering in a biological or chemical entity that is intended to be applied in a scientific technique to participate (or have molecular components that participate) in a chemical reaction that facilitates the generation of data about some entity distinct from the bearer, or the generation of some specified material output distinct from the bearer."@en ;
rdfs:subClassOf obo:BFO_0000023 .
obo:STATO_0000546 a rdfs:Class ;
rdfs:label "Bayes R"@en ;
rdfs:comment "Bayes R is a data transformation used in the context of estimating breeding value, which relies on a Bayesian model to compute 'genomic estimated breeding values'. In contrast to Bayes B methods, the new method assumes that the true SNP effects are derived from a series of normal distributions, the first with zero variance, up to one with a variance of approximately 1% of the genetic variance."@en ;
rdfs:subClassOf obo:OBI_0200000 , obo:STATO_0000119 , obo:STATO_0000337 .
obo:STATO_0000253 a rdfs:Class ;
rdfs:label "within subject comparison objective"@en ;
rdfs:comment "the objective of a data transformation to test a null hypothesis of absence of difference within subject holds."@en ;
rdfs:subClassOf obo:OBI_0000675 .
obo:OBI_0000403 a rdfs:Class ;
rdfs:label "sort function"@en ;
rdfs:comment "A sort function is a function to distinguish material components based on some associated physical quality or entity and to partition the separate components into distinct fractions according to a defined order."@en ;
rdfs:subClassOf obo:OBI_0000372 .
obo:BFO_0000179 a rdf:Property ;
rdfs:label "BFO OWL specification label"@en ;
rdfs:comment "Relates an entity in the ontology to the name of the variable that is used to represent it in the code that generates the BFO OWL file from the lispy specification."@en ;
rdfs:range xsd:string .
obo:BFO_0000180 a rdf:Property ;
rdfs:label "BFO CLIF specification label"@en ;
rdfs:comment "Relates an entity in the ontology to the term that is used to represent it in the the CLIF specification of BFO2"@en ;
rdfs:range xsd:string .
obo:IAO_0000111 a rdf:Property ;
rdfs:label "editor preferred term"@en ;
rdfs:comment "The concise, meaningful, and human-friendly name for a class or property preferred by the ontology developers. (US-English)"@en ;
rdfs:range xsd:string .
obo:IAO_0000112 a rdf:Property ;
rdfs:label "example of usage"@en ;
rdfs:comment "A phrase describing how a term should be used and/or a citation to a work which uses it. May also include other kinds of examples that facilitate immediate understanding, such as widely know prototypes or instances of a class, or cases where a relation is said to hold."@en ;
rdfs:range xsd:string .
obo:IAO_0000114 a rdf:Property ;
rdfs:label "has curation status"@en ;
rdfs:range xsd:string .
obo:IAO_0000115 a rdf:Property ;
rdfs:label "definition"@en ;
rdfs:comment "The official definition, explaining the meaning of a class or property. Shall be Aristotelian, formalized and normalized. Can be augmented with colloquial definitions."@en ;
rdfs:range xsd:string .
obo:IAO_0000116 a rdf:Property ;
rdfs:label "editor note"@en ;
rdfs:comment "An administrative note intended for its editor. It may not be included in the publication version of the ontology, so it should contain nothing necessary for end users to understand the ontology."@en ;
rdfs:range xsd:string .
obo:IAO_0000117 a rdf:Property ;
rdfs:label "term editor"@en ;
rdfs:comment "Name of editor entering the term in the file. The term editor is a point of contact for information regarding the term. The term editor may be, but is not always, the author of the definition, which may have been worked upon by several people"@en ;
rdfs:range xsd:string .
obo:IAO_0000118 a rdf:Property ;
rdfs:label "alternative term"@en ;
rdfs:comment "An alternative name for a class or property which means the same thing as the preferred name (semantically equivalent)"@en ;
rdfs:range xsd:string .
obo:IAO_0000119 a rdf:Property ;
rdfs:label "definition source"@en ;
rdfs:comment "Formal citation, e.g. identifier in external database to indicate / attribute source(s) for the definition. Free text indicate / attribute source(s) for the definition. EXAMPLE: Author Name, URI, MeSH Term C04, PUBMED ID, Wiki uri on 31.01.2007"@en ;
rdfs:range xsd:string .
obo:IAO_0000232 a rdf:Property ;
rdfs:label "curator note"@en ;
rdfs:comment "An administrative note of use for a curator but of no use for a user"@en ;
rdfs:range xsd:string .
obo:IAO_0000233 a rdf:Property ;
rdfs:label "term tracker item"@en ;
rdfs:comment "An IRI or similar locator for a request or discussion of an ontology term."@en ;
rdfs:range xsd:string .
obo:IAO_0000412 a rdf:Property ;
rdfs:label "imported from"@en ;
rdfs:comment "For external terms/classes, the ontology from which the term was imported"@en ;
rdfs:range xsd:string .
obo:IAO_0000417 a rdf:Property ;
rdfs:label "is quality measured as"@en ;
rdfs:comment "inverse of the relation of is quality measurement of"@en ;
rdfs:range .
obo:IAO_0000589 a rdf:Property ;
rdfs:label "OBO foundry unique label"@en ;
rdfs:comment "An alternative name for a class or property which is unique across the OBO Foundry."@en ;
rdfs:range xsd:string .
obo:IAO_0000600 a rdf:Property ;
rdfs:label "elucidation"@en ;
rdfs:range xsd:string .
obo:IAO_0000601 a rdf:Property ;
rdfs:label "has associated axiom(nl)"@en ;
rdfs:range xsd:string .
obo:IAO_0000602 a rdf:Property ;
rdfs:label "has associated axiom(fol)"@en ;
rdfs:range xsd:string .
obo:OBI_0001847 a rdf:Property ;
rdfs:label "ISA alternative term"@en ;
rdfs:comment "An alternative term used by the ISA tools project (http://isa-tools.org)." ;
rdfs:range xsd:string .
obo:OBI_9991118 a rdf:Property ;
rdfs:label "IEDB alternative term" ;
rdfs:comment "An alternative term used by the IEDB." ;
rdfs:range xsd:string .
obo:RO_0000053 a rdf:Property ;
rdfs:label "bearer of"@en ;
rdfs:comment "a relation between an independent continuant (the bearer) and a specifically dependent continuant (the dependent), in which the dependent specifically depends on the bearer for its existence"@en ;
rdfs:range obo:BFO_0000020 .
obo:RO_0000080 a rdf:Property ;
rdfs:label "quality of"@en ;
rdfs:comment "a relation between a quality and an independent continuant (the bearer), in which the quality specifically depends on the bearer for its existence"@en ;
rdfs:range xsd:string ;
rdfs:subPropertyOf obo:RO_0000052 .
obo:RO_0000086 a rdf:Property ;
rdfs:label "has quality"@en ;
rdfs:comment "a relation between an independent continuant (the bearer) and a quality, in which the quality specifically depends on the bearer for its existence"@en ;
rdfs:range obo:BFO_0000019 ;
rdfs:subPropertyOf obo:RO_0000053 .
obo:RO_0001015 a rdf:Property ;
rdfs:label "location of"@en ;
rdfs:comment "a relation between two independent continuants, the location and the target, in which the target is entirely within the location"@en ;
rdfs:range .
obo:RO_0001900 a rdf:Property ;
rdfs:label "temporal interpretation"@en ;
rdfs:comment "An assertion that holds between an OWL Object Property and a temporal interpretation that elucidates how OWL Class Axioms that use this property are to be interpreted in a temporal context." ;
rdfs:range xsd:string .
obo:RO_0002222 a rdf:Property ;
rdfs:label "temporal relation"@en ;
rdfs:comment "A relation that holds between two occurrents. This is a grouping relation that collects together all the Allen relations." ;
rdfs:range obo:BFO_0000003 .
obo:STATO_0000032 a rdf:Property ;
rdfs:label "STATO alternative term"@en ;
rdfs:comment "an alternative term used for STATO statistical ontology and ISA team"@en ;
rdfs:range xsd:string .
obo:STATO_0000041 a rdf:Property ;
rdfs:label "R command"@en ;
rdfs:comment "a R command syntax or link to a R documentation in support of Statistical Ontology Classes or Data Transformations"@en ;
rdfs:range xsd:string .
obo:STATO_0000110 a rdf:Property ;
rdfs:label "assumes values specified by"@en ;
rdfs:comment "A relation between an entity and a value specification, where the value specification is about the entity."@en ;
rdfs:range .
obo:STATO_0000114 a rdf:Property ;
rdfs:label "is member of"@en ;
rdfs:comment "relationship between an element and a set it belongs to"@en ;
rdfs:seeAlso obo:RO_0002350 ;
rdfs:range .
obo:STATO_0000345 a rdf:Property ;
rdfs:label "has fixed effect on"@en ;
rdfs:comment "'has fixed effect on' is a special case of the 'is about' relationship to be used with fixed effect models"@en ;
rdfs:range xsd:string ;
rdfs:subPropertyOf obo:STATO_0000344 .
obo:STATO_0000380 a rdf:Property ;
rdfs:label "has interaction effect on"@en ;
rdfs:comment "'has interaction effect on' is a special case of the 'is about' relationship to be used for mixed effect models"@en ;
rdfs:range xsd:string ;
rdfs:subPropertyOf obo:STATO_0000344 .
obo:STATO_0000381 a rdf:Property ;
rdfs:label "has random effect on"@en ;
rdfs:comment "'has random effect on' is a special case of the 'is about' relationship to be used for random effect models"@en ;
rdfs:range xsd:string ;
rdfs:subPropertyOf obo:STATO_0000344 .
obo:STATO_0000391 a rdf:Property ;
rdfs:label "Python command"@en ;
rdfs:comment "an annotation property to provide a canonical command to invoke a method implementation using Python programming language"@en ;
rdfs:range xsd:string .
obo:STATO_0000404 a rdf:Property ;
rdfs:label "preferred mathematical notation"@en ;
rdfs:comment "the most common series or system of written mathematical symbols used to represent the entity"@en ;
rdfs:range xsd:string .
a rdfs:Datatype .
obo:IAO_0000078 a rdfs:Class ;
rdfs:label "curation status specification"@en ;
rdfs:comment "The curation status of the term. The allowed values come from an enumerated list of predefined terms. See the specification of these instances for more detailed definitions of each enumerated value."@en ;
rdfs:subClassOf obo:IAO_0000102 .
obo:IAO_0000002 a obo:IAO_0000078 ;
rdfs:label "example to be eventually removed"@en .
obo:IAO_0000120 a obo:IAO_0000078 ;
rdfs:label "metadata complete"@en ;
rdfs:comment "Class has all its metadata, but is either not guaranteed to be in its final location in the asserted IS_A hierarchy or refers to another class that is not complete."@en .
obo:IAO_0000121 a obo:IAO_0000078 ;
rdfs:label "organizational term"@en ;
rdfs:comment "Term created to ease viewing/sort terms for development purpose, and will not be included in a release"@en .
obo:IAO_0000122 a obo:IAO_0000078 ;
rdfs:label "ready for release"@en ;
rdfs:comment "Class has undergone final review, is ready for use, and will be included in the next release. Any class lacking \"ready_for_release\" should be considered likely to change place in hierarchy, have its definition refined, or be obsoleted in the next release. Those classes deemed \"ready_for_release\" will also derived from a chain of ancestor classes that are also \"ready_for_release.\""@en .
obo:IAO_0000123 a obo:IAO_0000078 ;
rdfs:label "metadata incomplete"@en ;
rdfs:comment "Class is being worked on; however, the metadata (including definition) are not complete or sufficiently clear to the branch editors."@en .
obo:IAO_0000124 a obo:IAO_0000078 ;
rdfs:label "uncurated"@en ;
rdfs:comment "Nothing done yet beyond assigning a unique class ID and proposing a preferred term."@en .
obo:IAO_0000125 a obo:IAO_0000078 ;
rdfs:label "pending final vetting"@en ;
rdfs:comment "All definitions, placement in the asserted IS_A hierarchy and required minimal metadata are complete. The class is awaiting a final review by someone other than the term editor."@en .
obo:IAO_0000423 a obo:IAO_0000078 ;
rdfs:label "to be replaced with external ontology term"@en ;
rdfs:comment "Terms with this status should eventually replaced with a term from another ontology."@en .
obo:IAO_0000428 a obo:IAO_0000078 ;
rdfs:label "requires discussion"@en ;
rdfs:comment "A term that is metadata complete, has been reviewed, and problems have been identified that require discussion before release. Such a term requires editor note(s) to identify the outstanding issues."@en .
obo:OBI_0000639 a rdfs:Class ;
rdfs:label "material separation objective" ;
rdfs:comment "is an objective to transform a material entity into spatially separated components." ;
rdfs:subClassOf obo:OBI_0000456 .
obo:OBI_0000678 a obo:OBI_0000639 ;
rdfs:label "portioning objective" ;
rdfs:comment "A material separation objective aiming to separate material into multiple portions, each of which contains a similar composition of the input material." .
obo:OBI_0000681 a obo:OBI_0000639 ;
rdfs:label "separation into different composition objective" ;
rdfs:comment "A material separation objective aiming to separate a material entity that has parts of different types, and end with at least one output that is a material with parts of fewer types (modulo impurities)." .