Glossary

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

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 non-random cause. It is rival to the Null Hypothesis, H0.

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.

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.

See Analytical Procedure (AP).

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.

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

Bayesian Confidence Propagation Neural Network1Bate, A, et al. (1998) A Bayesian neural network method for adverse drug reaction signal generation. Eur J Clin Pharmacol 54:315-321; Gould, AL. (2003) Practical pharmacovigilance analysis strategies. Pharmacoepidemiology and Drug Safety 12: 559–574.

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

A region of DNA that is associated with either the presence or absence of a particular Phenotype.

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).

Involving two Variables.

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.

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

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.

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.

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

An item in a dialog or window that you can select without affecting any other items. You can deactivate a check box by selecting it again.

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 lower-triangular matrix. It is useful in Quantitative Trait Locus (QTL) analysis because it allows modeling of a Pedigree-induced 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 ill-conditioned matrices containing sparse or low-quality data.

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.

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

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 inter-Locus interval for the target QTL are assessed.

See Mosaic Plot.

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.

A relationship between Variables in terms of dependence.

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

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.

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

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

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 two-dimensional plot, the dependent variable is usually plotted on the y (horizontal) axis.

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

A matrix of distances.

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. Non-coding DNA can have structural or regulatory purposes.

The Double FDR method of Mehrotra and Heyse (2004)2Mehrotra DV, Heyse JH. (2004) Use of the false discovery rate for evaluating clinical safety data. Statistical Methods in Medical Research 13:227-238. 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.

See Experimental Design File (EDF).

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 non-living 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.

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

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.

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

A text-based 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 statistical significance test used in the analysis of contingency tables where sample sizes are small. It is useful when you want to conduct a Chi-square 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.

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.

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.

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

The genetic complement an individual has at a particular Locus.

A Variable that is used for grouping results.

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

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

Chemical-driven damage (toxicity) to the liver.

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.

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

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 decision-making 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 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.

The computation of replacement values for missing input values.

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 two-dimensional plot, the independent variable is usually plotted on the x (horizontal) axis.

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

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.

A scripting language used in JMP applications.

See JMP Scripting Language (JSL).

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

A metric used to measure the degree of correspondence between two sets of rankings where the metrics used to assess each set of rankings are not equivalent.

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.

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.

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.

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.

A nonparametric Hypothesis Test to compare the survival distributions of two samples. It is appropriate when data are right-skewed and non-informatively censored. Also known as a Mantel-Cox test. This test can be considered a time-stratified Cochran-Mantel-Haenszel Test.

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

See Logit Function.

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

A single statement, instruction, or catalog entry that automatically expands into a set of statements, instructions, or text.

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 two-level 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.

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).

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.

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

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 Pull-down Menu, or opens a Dialog box that requests additional information.

Multi-Item Gamma Poisson Shrinker3DuMouchel W. (1999) Bayesian data mining in large frequency tables with an application to the FDA spontaneous reporting system. The American Statistician 53: 177-90.

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

A statistical model containing both Fixed Effects and Random Effects.

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

Describes any group descended from a common ancestor that includes the ancestor and all of its descendents.

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

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 chip-specific differences)

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).

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

A plot showing the response points along the y-axis 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 One-way Plot.

An object in an expression to be operated on. An operand can be a variable, a function, or a constant.

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 under-estimated, respectively. This tendency varies based on person and type of action.

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

A living system or body capable of development, growth, homeostasis, and reproduction. Advanced multicellular organisms comprise multiple body systems.

A plot showing several lines or markers on the y-axis overlaid to a common variable on the x-axis. See Overlay 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.

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.

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 physical manifestation of a Genotype.

The format of a text (.txt) file that is readable with little-to-no-processing. Files in this format cannot be embellished with multiple font styles, underlining, italicization, emboldening, and so on.

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

An open standard for document exchange, created by Adobe Systems, that is used for representation of documents in a software, hardware, and operating system-independent manner.

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).

A function or variable used to estimate a response.

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.

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.

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

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

A SAS procedure; a group of SAS statements that call and execute a procedure, usually with a SAS data set as input

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

Proportional Reporting Ratio4Evans SJW, Waller PC, Davis S. (2001) Use of proportional reporting ratios (PRRs) for signal generation from spontaneous adverse drug reaction reports. Pharmacoepidemiology and Drug Safety 10:483-486.

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

Portions taken at regular intervals along a distribution that divide a data set into discrete subsets.

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.

The starting point for a random number generator. Unless a number is specified, an arbitrary value, such as the date or time of an event, is used.

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.

Value equal to the response value minus the predicted value.

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

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.

A file that contains all the SAS statements that you have submitted, messages about the execution of your analytical process and the SAS program running in the background, and in some cases, output from certain procedures. This file is generated and placed in the designated output folder.

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.

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

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 Save 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 Load button. See Saving and Loading Settings.

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

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

A number determining the degree of smoothing for certain algorithms.

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

The proportion of true negatives that are correctly identified. Specifically, specificity equals the number of true negatives divided by the sum of the number of true negatives and the number of false positives.

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.

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

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 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.

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 p-Value adjustment method to indicate that there is at least one false Null Hypothesis among those with p-values less than tau when the null hypothesis is rejected.

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.

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

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

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 complete set of rules that are used to split data into a hierarchy of successive segments. A tree consists of branches and leaves, in which each set of leaves represents an optimal segmentation of the branches above them according to a statistical measure.

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

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 (one-sample t-test), the null hypothesis is that “the population mean is equal to the given mean”.

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 = 1-beta).

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

Measures of physiological statistics used to assess basic body functions. The most common vital signs include body temperature, heart rate (or pulse), blood pressure, and respiratory rate.

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 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 t-test 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.