Glossary
Term  Definition/Explanation 
A numerical identifier for a Gene, marker, or gene product in a public database. 

Any variant form of a Nucleic Acid sequence or marker at a particular Locus. 

Significance level. Although alpha can be any value between 0 and 1, it is typically set at either 0.01, 0.05 or 0.10. 

A position that a researcher evaluates in an experiment. The alternative hypothesis, H1 (or Ha), is the hypothesis that sample observations are influenced by a specific nonrandom cause. It is rival to the Null Hypothesis, H0. 

The building block of Proteins. An enormous variety of proteins can be constructed by linking together Amino Acids (there are more than twenty types) in a linear chain, which in turn become folded in more complex configurations. 

A computational task that uses input data and parameters in a statistical method or other algorithm to produce output in the form of files, data sets, tables, graphics, logs, and so on. Also known as an Analytical Process. Abbreviated as AP. 

Analysis of covariance; a general linear model with a continuous outcome Variable and multiple predictor variables, with at least one nominal and one continuous predictor variable. Considered a hybrid of regression for continuous variables and ANOVA, ANCOVA can determine whether specific factors have an impact on the outcome variable after removing variance resulting from Covariates (the qualitative predictors). 

Data set containing a variety of information about the identity, biological function, pathway association, and so on, for the Genes, gene fragments, gene products, Probe Set (Probeset)s, genetic markers, and so on, under investigation. 

Statistical models and procedures that partition observed Variance in a Variable into components attributable to different variation sources. By analyzing comparisons of variance estimates, ANOVA can determine whether the Means of several groups are statistically equal. 

The statistically significant cooccurrence of two or more phenomena. In the context of a GenomeWide Association Study (GWAS), mapping of a Gene for a particular Trait or disease is performed by detecting significant associations between the trait and marker Genotype. 

Area under the Receiver Operator Characteristics (ROC) Curves Statistic that is used to assess the ability of a model to predict future responses. For most models, the greater the AUC, the better the model is for making accurate predictions. 

Any Chromosome that is not a Sex Chromosome. 

A graphical representation of discrete or noncontinuous data. It consists of rectangular bars whose lengths are proportional to the magnitude of the values that they represent. See Bar Chart. 

Also known as a nitrogenous base or nucleobase, it is one component of a Nucleotide. Every nucleotide has exactly one base. 

Denotes Type II Error rate, and is related to the Power of a test power = 1beta). 

A group of related of functionally similar Observations that are considered as a unit for statistical analysis. 

Binary Trait 
A characteristic with a dichotomous expression. Unlike a Quantitative Trait (which can be found in degrees, or among a continuous scale), a binary trait is either found, or not found, in an organism. Synonymous with Dichotomous Trait. 
Binary Trait Locus (BTL) 
A region of DNA that is associated with either the presence or absence of a particular Phenotype. 
A Variable that contains two discrete values (0 and 1, for example). 

A regression method where the Dependent Variable contains binomial values (for example, 0 and 1, often corresponding to ‘no’ and ‘yes’, or ‘failure’ and ‘success’, respectively). 

A scientific field of study involving the integration and application of computer science, information technology, mathematics, and statistics to the fields of biology, genetics, Genomics, and medicine. 

Involving two Variables. 

The practice of using withreplacement empirical distributions of Observations to estimate the statistical properties of the population from which the observations were made. 

Used to display the response distribution at different combinations of factor levels. Box plots can reveal differences in the response Mean at different levels, suggesting Main Effects. Box plots can also reveal whether the response variation is homogenous across factor levels, an assumption made in ANOVA. See Box Plot. 

A twodimensional Scatterplot showing the relationship between two Variables over time. Each circle, or bubble, represents a single instance of an ID variable. See Bubble Plot. 

All of the Observations with the same values for all BY Variables. 

An optional (in most APs) Variable specification whose values define groups of Observations, such as hour, month, or year. Specifying a BY variable enables you to animate an image so that you can see how response values change according to some grouping, like over time. Alternatively, BY variables can enable analyses to be performed separately on different groups as defined by a variable such as gender. 

The fundamental building block of a living Organism. Cells consist of Organelles. A cell is the smallest unit that can be said to be living. 

A Heat Map or color map display, mapping colors to values of Variables and displaying them in a rectangular grid. See Cell Plot. 

These columns specify those Observations for which data have been censored or truncated. For example, investigations of the effects of certain Genes on life span might be terminated before all of the individuals have expired. The ultimate life spans for these individuals are unknown. All that can be said is that they exceed the period of the study. These data are considered censored. 

Also referred to as a map unit. A measure of Genetic Distance between loci; one centimorgan is equivalent to the physical separation between loci needed for a recombination frequency of 1%. Recombination between loci is affected by a variety of molecular and biochemical factors, in addition to Physical Distance, and the centimorgan should not be considered as representing a linear measurement. 

A Variable whose values can consist of alphabetic and special characters as well as numeric characters 

A graphical representation of data. Charts can take many forms. See Chart. 

A statistical test used to test the existence of a relationship between two nominal Variables where the sampling distribution of the Test Statistic is a chisquared distribution when the Null Hypothesis is true (or where it is asymptotically true). 

A mathematical method for taking the square root of a symmetric matrix. The Cholesky root of a matrix A is L, where A = LL`, and L is a lowertriangular matrix. It is useful in Quantitative Trait Locus (QTL) analysis because it allows modeling of a Pedigreeinduced Covariance structure via a Mixed Model. It more efficiently solves a kinship matrix (see K Matrix) compared to classical LU decomposition, thus improves execution time. However, it should not be applied to illconditioned matrices containing sparse or lowquality data. 

Bundled strands of DNA and Protein located in the Cell Nucleus. Chromosomes are inherited from parents. Chromosome count per Organism cell varies by Species. Human cells contain 23 pairs of nuclear chromosomes. 

The Variable whose values define the groups for analysis. Class variables can have continuous values, but they typically have a few discrete values that define the classifications of the variable. Values can either be character or numeric. 

The process of dividing a data set into mutually exclusive groups such that the Observations for each group are as close as possible to one another, and different groups are as far as possible from one another. 

A statistical test used for repeated tests of nominal variable independence. 

A Variable whose values are used to specify how the graphical output of an analysis is to be colored. 

Method for mapping of a target Quantitative Trait Locus (QTL) for a Trait. It uses markers, located elsewhere in the Genome, that have previously been shown to be associated with additional QTLs for that trait. Multiple analysis points across each interLocus interval for the target QTL are assessed. 

The probability of an event (for example, X) given that another specific event (for example, Y) occurs. Conditional probability is often expressed as P(XY) or PY(X). 

A table used to record and analyze the relationship between two or more categorical variables. See Contingency Table. 

Continuous Trait 
A trait based on a characteristic measured on an ordered scale, lacking discrete divisions or gaps. For example, height and skin color are continuous traits. Continuous traits are in contrast to Dichotomous Traits, where categorizations are discrete. 
Any Deletion, Insertion, duplication, or other variant in the DNA sequence of a Genome that results in that sequence being present in greater or lesser numbers relative to those seen in a normal, reference genome. A CNV can result from relatively simple duplications, either tandem or inverted, or deletion of small or large blocks of sequence. They might also be more complex, involving gains or losses of homologous sequences at multiple sites in the genome. Disruption of contiguous Gene sequences and altered gene dosages by CNVs have been shown to influence gene Expression, increase phenotypic variation and cause disease. 

A relationship between Variables in terms of dependence. 

Also known as the Pearson productmoment correlation coefficient, it is equal to the Covariance of two Variables divided by the product of their Standard Deviations. 

A measure of the relationship between two Variables. It equals the Correlation Coefficient between the two variables times the square roots of their Variances. 

An Independent Variable, not manipulated by the experimenter, that can influence the outcome of the experiment. 

A classical semiparametric (sometimes considered nonparametric) method that relates the time of an event (for example, failure or death) to explanatory variables (Covariates). This model assumes that hazard rate, rather than survival time, is a function of the explanatory variables. There are no assumptions made on the shape or nature of the hazard function. 

A statistical method for evaluating how well a model predicts the outcome of additional experiments. 

Commaseparated value format. This text format stores tabular data, with line breaks and commas used to delimit table rows and columns, respectively. 

A mutation that results in a missing DNA sequence or chromosomal region. 

One or more characters that separate the designations for the different Alleles in a Genotype. JMP frequently uses a forwardslash (/) as a delimiter. 

A treelike diagram used to summarize a Clustering process. A dendrogram shows where each cluster divides in a hierarchical fashion. See Dendrogram. 

A Variable whose value is determined by the value of another variable or by the values of a set of variables. This variable lists the responses you measure. In a twodimensional plot, the dependent variable is usually plotted on the y (horizontal) axis. 

A Residual that measures the disagreement between the maxima of the fitted and observed log likelihood functions. 

An interactive window that enables you to set parameters for and run an analytical process. 

Dichotomous Trait 
A trait that completely and discretely separates a population of organisms belonging to the same species. For example, blood type is a dichotomous trait. Dichotomous traits are in contrast to Continuous Traits (such as weight), where categorizations are not discrete. 
Graphics showing the number or proportion of events falling within a particular interval. JMP Genomics software presents these distributions as histograms or Parallel Plots. See Distribution. 

Deoxyribonucleic acid, a Nucleic Acid containing genetic instructions for the development and functioning of living Organisms (except for RNA viruses). DNA segments encoding genetic information are known as Genes. Noncoding DNA can have structural or regulatory purposes. 

An algebraic operation that takes two equallength number sequences (usually coordinate vectors) and returns a single number obtained by multiplying corresponding entries and summing those products. 

Double False Discovery Rate (FDR) Adjustment 
The Double FDR method of Mehrotra and Heyse (2004)2 is used to compare the incidence ofadverse events among treatments, leveraging the grouping of related adverse events. The method considers whether related terms within a group show differences between the treatments and upweights or downweights the significance of an individual term within the group accordingly. In the 2004 paper, the FDR adjustment is performed twice, and simulations are used to control the false discovery rate. Mehrotra and Adewale (2011) refine the Double FDR method to avoid the need for simulations by applying FDR adjustment thrice. 
The sum of all Organisms living in a given area along with the relevant Environmental components of that area. 

A scalar value that determines by how much a corresponding eigenvector is scaled by the square matrix for which it is defined. In Principal Components analysis, the eigenvalues of the Covariance or Correlation matrix represent the Variance of the components. 

For a given square matrix, a nonzero vector that changes length, but not direction, when multiplied by the matrix. The computation of Principal Components for a set of Variables uses the eigenvectors of the variables' Covariance or Correlation matrix. 

The sum of all living and nonliving things (including physical conditions and factors) in a given physical space. This term is often used in contrast with Genotype to explain effects not attributable to genetic makeup alone. 

A programming statement for certain SAS procedures (for example, PROC MIXED) used to specify parameters used in both ANOVA and Mixed Model analyses to test an arbitrary set of linear hypotheses regarding the relative importance of different combinations of Fixed Effects parameters. 

The distance between two points that would be measured with a ruler. It is derived from the Pythagorean equation: a2 + b2 = c2. 

Any portion of the transcribed region of a Gene that make up the mature mRNA. Exons are separated in the genomic DNA by intervening sequences (Introns) that are transcribed with the exons. Introns are excised and the exons are spliced together during posttranscriptional processing and mRNA maturation. 

An EDDS is a SAS data set that provides information about the columns of a tall data set. It describes relevant experimental Variables such as treatment conditions and Covariates as well as a variable named ColumnName. Entries in the ColumnName column must exactly match the column names in the input tall data set. EDDSs have certain constraints that must be followed for the processes to run successfully. An EDDS is required by most processes using a tall input data set. Many of the input engines that generate a tall data set from raw data files also automatically generate the needed EDDS. 

A file that provides JMP Genomics with important information about how an experiment was carried out. It defines experimental Variables such as treatment conditions and Covariates and provides the basis for organizing and analyzing your data. An EDF is required by many of the input engines for the construction of a SAS data set from the raw data files. An EDF also serves as a precursor to the Experimental Design Data Set (EDDS). 

The process by which the information contained in a Gene is used to make a functional RNA or Protein. 

Also referred to as an Independent Variable or Predictor variable, a factor is a Variable included in a model to account for variation in a response. Factors are the variables whose values (levels) you set to study their relationship to a response. You often experiment with many potentially influential factors at the same time. 

The expected percentage of a set of predictions that are assumed to be false. For example, if an analysis, which predicts the association of 10 genes with a particular Trait has a false discovery rate of 0.1, you can expect 9 of the predictions to be correct. 

The probability of making one or more false discoveries (Type I Errors) among all hypotheses while performing multiple pairwise tests. 

A textbased format for representing DNA, RNA, or Protein sequences. Singleletter codes corresponding to Nucleotides (composing DNA and RNA) or Amino Acids (composing proteins) are used for sequence representation. No standard file extension exists for FASTA files, but often the extensions “.fasta”, “.fas”, “.fa”, or “.txt” are used. 

A textbased format for representing DNA or RNA sequences with associated quality scores. Nucleotides (composing DNA and RNA) and quality scores are represented with a single character. No standard file extension exists for FASTQ files, but often the extensions “.fastq”, “.fq”, or “.txt” are used. 

A window area in which you can view, enter, or modify a value. 

A statistical significance test used in the analysis of contingency tables where sample sizes are small. It is useful when you want to conduct a Chisquare Test, but one of your cells has an expected frequency of five or less. Its name is derived from its inventor, R.A. Fisher, and reflects that the significance of the deviation from a Null Hypothesis can be calculated exactly (as opposed to relying on an approximation whose exactness is realized only as sample size approaches infinity). 

A graphical display designed to illustrate the relative strength of treatment effects (or relative degree of gene enrichment), in multiple quantitative scientific studies (or databases) addressing the same question. Forest plots generally display results for each study (or other data source) as horizontal lines representing the 95% confidence interval of the effect observed in that trial. See Forest Plot. 

Multivariate probability distributions encoding a dependency network among variables. 

Molecular unit of heredity in a living Organism, comprising a contiguous sequence of DNA or RNA, coding for a Protein or RNA chain, which in turn has a function in the organism. 

Genetic divergence between Species (with or without using a genetic map) or between populations within a species. Smaller genetic distances indicate closer genetic relationships. A variety of genetic distance measures exist, including the CentiMorgan (cM), Trait frequency differences, the fixation index, Nei’s standard genetic distance, and so on. 

A set of interactions occurring between a group of Genes. Many of the genes in the interaction network rely on the functions of other individual genes within the network in order to yield a net worthwhile product or function to the Cell. 

The entire set of hereditary information in an Organism, encoded by DNA or RNA, comprising Genes and noncoding sequences. 

An examination of the entire Genome of multiple individuals for an association between a genetic variant and a Trait. 

The scientific field of study concerned with Genomes. 

The genetic complement an individual has at a particular Locus. 

A Variable that is used for grouping results. 

The combination of Alleles that is transmitted from one generation to the next as a single unit on a Chromosome. 

The state of a population in which Gene frequencies and genotypic ratios remain constant from generation to generation. 

See Cell Plot. 

The state of a Cell containing only one copy of an Allele for a particular Gene. 

The state of a Cell containing two different Alleles for a particular Gene on homologous Chromosomes. 

A method of cluster analysis that constructs a hierarchy of clustering. Strategies include the agglomerative approach, where each cluster initially contains only one observation, and the divisive approach, where all observations are initially contained in one cluster. Hierarchical clustering results are commonly presented in Dendrogram form. 

A portion of the data that is set aside during model development. Holdout data can be used as test data to benchmark the fit and accuracy of the emerging predictive model. 

A nonparametric measure of association that detects general departures from independence. This Statistic approximates a weighted sum over observations of chisquare statistics for twobytwo classification tables. 

The state of a Cell containing two identical Alleles for a particular Gene on homologous Chromosomes. 

A test of the Null Hypothesis that “the Population Mean vector is equal to the given mean vector”. It is the multidimensional equivalent of the onesample ttest. 

Haplotype tag Single Nucleotide Polymorphism (SNP). htSNPs are a subset of genetic markers that can be used to explain much of the haplotype diversity. See Tag SNP. 

A decisionmaking rule based on data from an experiment or observational study. A hypothesis test is used to conclude significance of a result based on the sufficiently low likelihood (set by the predefined significance level) that it occurred because of random chance alone. 

Two or more Alleles are identical by descent (IBD) if they are identical copies of the same ancestral allele. 

Two ore more Alleles are identical by state (IBS) either because they are derived from a common ancestor (Identical by Descent (IBD)) or because of chance. 

Two or more Alleles are identical by type (IBT) if they have the same phenotypic effect, or if applied to a variation in the composition of DNA such as a Single Nucleotide Polymorphism (SNP) when they have the same DNA sequence. 

The computation of replacement values for missing input values. 

The probability that an individual's two Alleles at any locus are Identical by Descent (IBD). 

This Variable does not depend on the value of another variable; it represents the condition or parameter that is manipulated by the investigator. In a twodimensional plot, the independent variable is usually plotted on the x (horizontal) axis. 

One or more columns specifying how the Observations are to be classified. 

A mutation that results in an extra DNA sequence or chromosomal region. 

Method for mapping of a target Quantitative Trait Locus (QTL) for a Trait between two flanking markers. 

A Nucleotide sequence within a Gene that is removed through RNA splicing to yield the mature RNA product of a gene. Intron can refer to both DNA gene sequence and the RNA Transcript sequence corresponding to that sequence. 

In JMP, a journal is a file (.jrn) and associated window that contains results of userspecified Processes. 

The relative kinship matrix containing pairwise kinship (or coancestry) coefficients. 

The information for the Linkage Disequilibrium (LD) measure Rho. 

A curve based on the survival function estimator from lifetime or clinical outcome data. For example, it can be used to measure the proportion of patients living for a given amount of time after treatment, or to measure the time until a tumor disappears. 

The probability that two Alleles from a single Locus in a randomly selected pair of individuals are Identical by Descent (IBD). 

A statistical method that creates optimally separated groups of Observations in data using one of several methods. A set of points called cluster seeds is selected as a first guess of the means of the clusters. One cluster seed is selected for each of k clusters. Each observation is assigned to the nearest seed to form temporary clusters. The seeds are then replaced by the Means of the temporary clusters, and the process is repeated until no further changes occur in the clusters. 

A column containing descriptive labels that can be printed in the output by certain procedures instead of, or in addition to, the Variable name (which is also known as the SAS Variable Name). Synonymous with SAS Variable Label. 

In a Tree Map, a leaf is any segment that is not further segmented. The final leaves in a tree are called terminal nodes. 

A successive hierarchical partition of data in a Tree Map. The first level represents the entire unpartitioned data set. The second level represents the first partition of the data into segments, and so on. 

The property by which Alleles located on the same Chromosome tend to be inherited together. The closer two loci are on the chromosome, the more tightly they tend to be linked. 

A measure of the association between two Alleles at separate loci. Note: A high LD does not imply that loci are physically linked. An association (either positive or negative) between allels can occur even if the loci are not located on the same chromosome, provided other factors affecting the Population (directional selection, for example) are in effect. 

The location of a specific genetic sequence on a Chromosome. 

A logarithmic statistical estimate of the probability that two loci are located proximal to each other on a Chromosome. A Lod score of 3, which indicates that two loci are 1000 times more likely than not to lie close to each other, is generally considered minimal for significance. 

Method for eliminating nonbiological bias and variation from Microarray data by fitting a local regression curve to Expression data. Assumes that the majority of the Genes in the study are not differentially affected by the experimental conditions. 

A nonparametric Hypothesis Test to compare the survival distributions of two samples. It is appropriate when data are rightskewed and noninformatively censored. Also known as a MantelCox test. This test can be considered a timestratified CochranMantelHaenszel Test. 

A common sigmoid curve that can model the Sshaped curve of Population growth. Initial growth approximates an exponential curve, followed by slowing growth as saturation begins, followed by no growth at maturity. 

A generalized linear model used for prediction of the probability of event occurrence (Binomial Regression) by fitting data to a Logit Function logistic curve. 

The inverse of the sigmoidal Logistic Function. It is synonymous with Logodds. 

See Logit Function. 

Results from a Deletion (or other Mutation) of the normal Allele, at a Locus Heterozygous for the normal alleles and a deleterious mutant allele. Produces a locus that is either Homozygous or Hemizygous for the deleterious allele. 

Least squares Means, which are estimates of means of classification effects that would be observed, assuming that the experimental design is balanced. 

A plot of the distribution of redtogreen intensity ratio (M; yaxis) by the average intensity (A; xaxis). It can be used to visualize the intensitydependent ratio of raw Microarray data in order to determine whether Normalization is needed. See MA Plot for more information. 

A distance measure based on Correlations between Variables. In contrast to Euclidean Distance, it is better adapted to nonspherically symmetric distributions, and is scaleinvariant. See Mahalanobis Distances. 

An effect measures the extent to which the response depends on the factors involved in the effect. A main effect is the change in the response due to a single factor. For twolevel factors, the main effect is the difference between the mean response at the high level of a factor and the Mean response at its low level. 

From a set of Alleles for a given gene or locus, the allele that occurs most often in a Population. 

Multivariate analysis of covariance; an extension of the analysis of covariance (ANCOVA) for multiple Dependent Variables or where it is not feasible to combine dependent variables. MANCOVA is similar to MANOVA, but enables control for additional continuous Independent Variables (Covariates). 

A type of scatter plot commonly used to display dense data, or data of highly diverse orders of magnitude. One typical use is in genomics applications, such as GenomeWide Association Study (GWAS). See Manhattan Plot. 

Multivariate analysis of variance, a generalized form of univariate analysis of variance (ANOVA), used when there are two or more Dependent Variables. This analysis is useful in determining whether changes in the Independent Variables have significant effects on the dependent variables, as well as the associated interactions among dependent and independent variables. 

The column listing each individual's Allele or Genotype for the genetic markers used in an analysis. If marker variables are listed as alleles, there is a pair of marker variables for each marker. 

Mathematical average for a collection of n Observations. It is calculated by dividing the sum of the observations by n. 

In any set of n Observations arranged in order of magnitude, the median is represented by the observation positioned at n/2. 

The primary list of items at the top of a window, which represent the actions or classes of actions that can be executed. Selecting an item executes an action, opens a Pulldown Menu, or opens a Dialog box that requests additional information. 

A compact twodimensional array of biological material on a solid substrate (chip). Microarrays can be used for measuring Gene Expression, detecting SNPs, and evaluating proteinprotein interactions, among many other things. 

From a set of Alleles for a given gene or locus, the allele that occurs least often in a Population. 

A value in the SAS System indicating that no data is stored for the Variable in the current Observation. It is indicated by a single dot (.) for a numeric variable or a blank for a character variable. 

A statistical model containing both Fixed Effects and Random Effects. 

The value that occurs most often in a probability Distribution or data set. 

A formula or algorithm that computes output values from input values. 

An argument of proof by contradiction; often known as denying the consequent. It has the general argument form of: 1. If P, then Q. 2. Not Q. 3. Therefore, not P. 

A graphical representation of a twoway frequency table or Contingency Table. A mosaic plot is divided into colored rectangles, so that the area of each rectangle is proportional to the proportions of the Y Variable in each level of the X Variable. See Mosaic Plot. 

A change (Insertion, Deletion, substitution, duplication, or inversion) in a genomic sequence. 

A Variable that contains discrete values that do not have a logical order. Includes names and other verbal descriptions. 

Multiple meanings are possible: 1. The division of more than one data set by a shared Variable to remove the effects of that variable from the data. By bringing the data to a common scale, data originating from different scales can be properly compared. 2. The isolation of statistical error in repeated measures data. 3. The adjustment of experimental data to remove variation from background noise and account for differences from technical artifacts (for example, assay or Microarray chipspecific differences) 

A DNA or RNA molecule. Nucleic acids store genetic information in all living Organisms. 

Building block of DNA and RNA. DNA nucleotides include Adenine (A), Cytosine (C), Guanine (G), and Thymine (T). RNA nucleotides are the same as those in DNA, with the exception of Uracil (U) replacing Thymine (T). 

The membranecovered Organelle containing most of the genetic material in a eukaryotic Cell. 

A general or default position that a researcher tests (and attempts to reject) in an experiment. The null hypothesis, H0, is an essential part of a research design, and usually proposes that sample Observations result purely from chance. The null hypothesis can never be proven; data can reject it or fail to reject it only. If a null hypothesis is rejected, an Alternative Hypothesis, H1 (or Ha) is accepted. 

A Variable that contains only numeric values and related symbols, such as decimal points, plus signs, and minus signs. 

A row (horizontal component) in a SAS data set. Each observation contains one data value for each Variable in the data set. 

Analysis of variance with one betweengroups factor. This is useful when you have a nominal Independent Variable and a normally distributed interval Dependent Variable, and you want to compare differences in the means of the dependent variable according to levels of the independent variable. 

A plot showing the response points along the yaxis for each X factor value. Using the plot, you can compare the distribution of the response across the levels of the X factor. The distinct values of X are sometimes called levels. See Oneway Plot. 

Analysis of variance used on one nominal Independent Variable and a normally distributed interval Dependent Variable that is repeated at least twice for each subject. This method is equivalent to the paired samples ttest, but allows for two or more nominal variable levels. 

The established systematic tendency for humans to be overly optimistic about the outcome of planned actions. The likelihood of positive and negative events are over and underestimated, respectively. This tendency varies based on person and type of action. 

A Variable that contains discrete values that have a logical order. For example, a variable called Rank could have values such as 1, 2, 3, 4, and 5. 

A collection of Tissues combined in one structure to serve a particular function. 

A plot showing several lines or markers on the yaxis overlaid to a common variable on the xaxis. See Overlay Plot. 

A plot consisting of connected line segments across all responses for each row in a data table. See Parallel Plot. 

A statistical technique that simultaneously partitions variability of both X and Y Variables (or matrices), somewhat similar to Principal Components. A PLS model attempts to identify the multidimensional direction in the X space that explains maximum multidimensional Variance direction in the Y space. 

See Percentile. 

A parametric measure of association for two variables. It measures both the strength and the direction of a linear relationship. If one variable X is an exact linear function of another variable Y, a positive relationship exists if the correlation is 1 and a negative relationship exists if the correlation is 1. If there is no linear predictability between the two variables, the correlation is 0. If the two variables are normal with a correlation 0, the two variables are independent. However, correlation does not imply causality because, in some cases, an underlying causal relationship might not exist. 

The ancestral lineage of an individual or group of closely related individuals. 

A discriminative classifier known for simultaneous Variable selection and classification. Its performance declines as the number of variables increases, and is often compared with that of Support Vector Machine (SVM). 

The value of a Variable below which a certain percent of Observations fall. For example, the 60th percentile is the value below which 60% of the observations can be found. Note the following percentile landmarks.  25th percentile = first quartile = Q1  50th percentile = second quartile = median = Q2  75th percentile = third quartile = Q3 

The physical manifestation of a Genotype. 

Distance between Genes or sequences measured in Bases, kilobases, megabases, or centiRays. 

The phenomenon where a single Gene influences multiple phenotypic Traits. Mutations in one pleiotropic gene can affect some or all associated traits simultaneously. 

The collection of all Organisms from the same Species living in a given geographical area. 

The phenomenon in which differences in Allele frequencies between cases and controls in studies of genetic diseases that might have been ascribed to association of specific Genes with disease are instead found to result from systematic differences in ancestry of the experimental groups. 

The Conditional Probability of a random event that is assigned after relevant evidence is considered. Contrast with Prior Probability. 

The probability of a statistical significance test allowing you to reject the Null Hypothesis when the Alternative Hypothesis is true. Power equals one minus Beta (the rate of Type II Error). 

An Independent Variable used to predict a Dependent Variable. Its distinct levels correspond to different predictions, and are often modeled by constructing a set of 01 Binary Variables corresponding to each distinct level. 

A numeric Independent Variable that predicts a Dependent Variable. Its predictions are computed directly as a function of the numeric variable, as in a linear regression. 

A statistical tool, made up of informative Variables, that is used to forecast future behaviors or responses. 

Linear combinations of all of the original Variables that maximally explain variability. Useful when the analysis considers effects of many variables at once. By combining the variables into groups, you can reduce the total number in any one analysis. 

A graphical display of a Principal Components analysis. The results of a principal components analysis (PCA) are plotted either on a Scatterplot Matrix or a ThreeDimensional Scatterplot. See Principal Components Analysis Plot. 

The probability of an event computed before collection of new data (often based on an experienced expert opinion or rulesofthumb). An experimenter begins with a prior probability of an event and then revises it in light of new data. Contrast with posterior probability. 

An individual spot or sample (a DNA or Protein sequence, for example) attached to a Microarray chip that hybridizes to a specific Target. Typical microarrays contain thousands of probes. 

Strength of the signal generated by hybridization of the Target sequence to the specific Probe Set (Probeset) on the Microarray. 

All of the different Probes specific for a Transcript. As an internal control, Microarrays typically include multiple Target sequences taken from different regions of a transcript. Comparisons of intensities resulting from the hybridization of transcripts to each of these sequences allows for more effective evaluation of transcript levels. The collection of targets specific for a transcript are referred to as a probeset. 

A computational task or procedure. In JMP Genomics, process typically refers to an Analytical Procedure (AP). 

A biochemical compound consisting of polypeptides, ordered as folded chains, sheets, or more complex threedimensional structures. Proteins can have structural or functional roles in Organisms. 

The list of menu items or choices that appears when you choose an item from a Menu Bar or from another menu. 

The statistical probability that a Statistic is as or more extreme than the observed value, assuming that the Null Hypothesis is true. A smaller pvalue enables you to more rigorously reject the null hypothesis. 

The n x p Population structure incidence matrix where n is the number of individuals assayed and p is the number of populations defined. 

Quantitative Trait 
Characteristics that are found in different degrees (along a continuous scale) across Organisms, unlike Binary Traits, which are either present or absent. Examples of quantitative traits are height and hair color. 
Quantitative Trait Locus (QTL) 
A region of DNA that is associated with the strength of a particular Phenotype. By themselves, QTLs do not determine whether a Gene is expressed. Instead, each QTL interacts with other QTLs, located throughout the Genome, to influence the relative level of Expression. 
A predictive modeling method used to interpolate multidimensional space, using a hidden layer (often Gaussian) and an output layer, associating each input data point with a Radial Basis Function (RBF). RBM is resistant to local minima problems, but the input space must be covered well by RBFs. 

A plot of curves summarizing the tradeoff between Sensitivity and Specificity in predictive modeling. See Receiver Operating Characteristics (ROC) Curves. 

Techniques for modeling and analyzing several Variables, with the focus on the relationship between dependent and independent variables. Regression analysis is useful in uncovering how values of a Dependent Variable change when a single Independent Variable is varied. 

A graph where the conditional distribution of the observations, given the forecast probability, is plotted against the forecast probability. The distributions for perfectly reliable forecasts are plotted along the 45degree diagonal. See Reliability Diagram. 

Value equal to the response value minus the predicted value. 

See Spearman Correlation. Also, a measure of Linkage Disequilibrium (LD). 

A proprietary document file format created by Microsoft, used in many word processing programs. 

Ribonucleic acid, a nucleic acid transcribed from DNA. RNA is used as a messenger (mRNA) to conduct Protein synthesis. Some viruses use RNA to encode Genes. 

A measure of the differences between the values predicted by a model or an estimator and the values actually observed. It is calculated by taking the square root of the Mean square error value. 

The number of Observations that constitute a statistical sample. For example, the sample size in a study might consist of the number of subjects. Greater sample sizes lead to greater precision and Power for a study design to detect an effect at a given size. 

Variables (columns) in a SAS data set can have a SAS Variable Label. This label has much less restrictive creation rules than the corresponding SAS Variable Name. Blank spaces, special characters, and longer lengths are permitted. See SAS Variable Names and Labels. 

Every Variable (column) in a SAS data set must have a unique SAS Variable Name. This name must conform to a number of conventions, with notable restrictions on the first character, blank spaces, special characters, and length. See SAS Variable Names and Labels. 

A graph showing the relationship between two Variables. Multiple scatterplot formats exist, including scatterplot matrices, threedimensional scatterplots, and Bubble Plots. See Reliability Diagram. 

A graphical method for determining the number of factors. The Eigenvalues are plotted in the sequence of the principal factors. The number of factors is chosen where the plot levels off to a linear decreasing pattern. See Scree Plot. 

A plot of sample versus physical position by Chromosome. See Segmentation Summary Plot. 

A SAS file that contains saved process settings, including paths to input and output data sets, and specific options. Settings files are generated by use of the button after completing a process input dialog. Rather than manually respecifying parameters for every run of a process, a settings file can quickly autopopulate this information via the button. See Saving and Loading Settings. 

A Chromosome that influences the sex of an Organism. For any given sexually reproducing Species, there are usually two types of sex chromosomes. All other chromosomes are called Autosomes. 

A graphical display enabling you to compare how an experimental Population responds to an experimental treatment. See Shift Plot. 

A specific type of Linkage analysis where markers are tested for linkage to a phenotypic Trait or disease by measuring the degree to which affected sib pairs share marker Haplotypes. 

DNA variant in which a sequence differs from the wildtype or other reference sequence by a single Nucleotide. 

The factorization of a real or complex matrix, allowing the matrix to be expressed as a product. Every m x n matrix has a singular value decomposition. 

A number determining the degree of smoothing for certain algorithms. 

Nonparametric method for examining whether two quantitative Variables covary. Each pair of variables is converted to ranks and is linked with an “unseen nominal variable. 

Multiple definitions exist, which convey essentially the same meaning:  A group of Organisms capable of interbreeding, resulting in fertile offspring.  A group of Organisms belonging to the same taxonomic rank by means of an arbitrarily sufficient similarity in morphology, ecological niche, or genomic content. 

A SAS data set that contains a square matrix. Identical entities are found in rows and columns. This data set often contains similarity, dissimilarity, identity, or distance values, and diagonal cells containing the values of 1 or 0. Note that although square data sets contain square matrices, they sometimes contain slightly more columns than rows (so that rows can be labeled to match column labels and to associate additional information with these labels). 

A SAS data set that has all Observations of interest stacked into a single Variable, or column. Rows are organized into groups of similar observations in which each row in the group differs in only one experimental parameter. Each group differs from other groups in additional parameters. Whereas a Tall Data Set typically has more rows than columns, a Stacked Data Set typically has many, many more rows than columns. 

A statistical measure of how “spread out” the data are. It is calculated by taking the positive square root of the sum of the squared deviations of each Observation from the sample Mean divided by (n1). 

The standard deviation of the sample mean. It is calculated by dividing the Standard Deviation by the square root of the Sample Size. 

Multiple meanings are possible:  Transformation of a data set to have zero Mean and unit Variance.  Making all regression coefficients have the same scale. 

Residual plots, widely used in regression analyses. are useful in determining whether there are additional Variables that should be included in the regression model. Residual plots also assist in outlier detection. More commonly, residual plots are used as diagnostic tools in deciding whether a distribution or model fit the data well. In linear regression, residuals are assumed to be normally distributed. Therefore, for convenience, they are transformed to the standardized form in standardized residual plots. See Standardized Residual Plots. 

A Variable that partitions the data into blocks with similar characteristics. 

Plots of survival functions estimated for each subject. See Survival Curves. 

A Single Nucleotide Polymorphism (SNP) in a high linkage disequilibrium region of a genome, representative of other specific SNPs. The use of Tag SNPs in a GenomeWide Association Study (GWAS) can greatly reduce the computational burden of the underlying analyses. Also known as a haplotypetag SNP (htSNP). 

A SAS data set that has samples as columns and molecular entity (for example, marker, gene, clone, protein, or metabolite) as rows. Tall data sets are the transpose of Wide Data Sets. See Tall and Wide Data Sets for more information. 

In Microarrays, a target is a specific experimental or clinical sample of cDNA, cRNA, or Protein that is washed over a microarray chip (containing Probes). Sequence presence or abundance is quantified by probetarget hybridization on the chip. 

A nonparametric measure of association based on the number of concordances and discordances in paired Observations. Concordance occurs when paired observations vary together, and discordance occurs when paired observations vary differently. Also, used for the truncated product pValue adjustment method to indicate that there is at least one false Null Hypothesis among those with pvalues less than tau when the null hypothesis is rejected. 

See Holdout Data. 

Test Statistic 
A function of the data sample that reduces and summarizes the data to either one or a few values that can be used to conduct a Hypothesis Test. 
A collection of Cells from the same origin that achieves a specific function. The cells need not be identical in morphology or genomic content, but must have identical function. Examples of animal and plant tissues include muscle and meristematic tissues, respectively. 

The sequence generated through transcription by using a DNA sequence as a template to create a complimentary RNA sequence. 

A familybased association test used to map Binary Traits. 

The portion of the initial data set that contains input values and target values that are used to develop a predictive model. 

A characteristic possessed by an Organism. Traits can be determined by Genotype, Environment, or both. 

A consensus sequence of Nucleotide Bases made up of the cluster of Exons transcribed from a particular strand of a defined region of the Genome. 

The process of applying a function to a Variable in order to adjust the variable's range, variability, or both. 

A graphic of hierarchical data represented by nested, tiled, colored rectangles. Every branch of the hierarchical tree is assigned a rectangle, which in turn is tiled with successively smaller rectangles corresponding to subbranches. See Tree Map. 

A method that smooths pValues over windows of markers for n Hypothesis Tests by taking the product of those pvalues less than a specified cutoff value and evaluating the probability of this product under the overall hypothesis that all n hypotheses are true. 

A measure of how extreme a statistical estimate is. It is calculated by subtracting a reference of hypothetical value from your estimate and then dividing the remainder by the Standard Error value for the experiment. 

A test that assesses the statistical difference between the Means of two different experimental groups. The Test Statistic follows a Student’s t distribution if the Null Hypothesis is supported. If only one Variable is chosen (onesample ttest), the null hypothesis is that “the population mean is equal to the given mean”. 

An incorrect decision made when a test rejects a true Null Hypothesis (H0). This is comparable to a false positive error. Type I error rate is denoted by Alpha, and is referred to as the size of the test. 

An incorrect decision made when a test fails to reject a false Null Hypothesis (H0). This is comparable to a false negative error. Type II error rate is denoted by Beta, and is related to the Power of a test (power = 1beta). 

A column (vertical component) in a SAS data set. The data values for each variable describe a single characteristic for all Observations. 

A measure of deviation of a group of samples from the mean. It is calculated by squaring the Standard Deviation. 

A Scatterplot of the negative log10transformed pValues derived from Genespecific ttest against the log2fold change in Expression. Genes whose expression is decreased lie to the left of the Mean; genes whose expression is increased lie to the right of the mean. Genes with statistically significant differential expression lie above a horizontal threshold. This plot provides an effective means for visualizing the direction, magnitude, and significance of changes in gene expression. See Volcano Plot. 

A SAS statement that enables you to filter a set of Observations so that only the subset of data meeting the specific filtering criteria are considered in the analysis. 

A SAS data set that has samples as rows and molecular entity (for example, marker, gene, clone, protein, or metabolite) as columns. Wide data sets are the transpose of Tall Data Sets. See Tall and Wide Data Sets for more information. 

A nonparametric statistical hypothesis test used when comparing two related samples or repeated measurements on a single sample to assess whether their population Mean ranks differ. It is appropriate as an alternative to the paired Student’s ttest when the population is not normally distributed or the data is ordinal. 

A series of Processes run in a specified order, whose output is collected in a Journal. Given a constant basic experimental design and analysis objectives, a workflow can be used repeatedly with different data sets. 
