Enrichment or depletion of a GO category within a class of genes: which test?

• Published in: Bioinformatics Vol. 23; no. 4; pp. 401 - 407
• Main Authors: Rivals, Isabelle, Personnaz, Léon, Taing, Lieng, Potier, Marie-Claude
• Format: Journal Article
• Language: English
• Published: Oxford Oxford University Press 15.02.2007; Oxford Publishing Limited (England); Oxford University Press (OUP)
• Subjects: Bioinformatics; Biological and medical sciences; Computer Science; Data Interpretation, Statistical; Database Management Systems; Databases, Protein; Fundamental and applied biological sciences. Psychology; Gene Expression Profiling - methods; General aspects; Information Storage and Retrieval - methods; Life Sciences; Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects); Methodology; Multigene Family - physiology; Oligonucleotide Array Sequence Analysis - methods; Proteins - classification; Proteins - metabolism; Quantitative Methods; Statistics; Gene; Ontology; Computer program; Test; Distribution; DNA chip; Database; Hypergeometric function; Probability; Review; Gene expression; Bioinformatics; hypergeometric test; p-value; Fisher's exact test; GO category
• ISSN: 1367-4803; 1367-4811; 1460-2059; 1367-4811
• DOI: 10.1093/bioinformatics/btl633

Motivation: A number of available program packages determine the significant enrichments and/or depletions of GO categories among a class of genes of interest. Whereas a correct formulation of the problem leads to a single exact null distribution, these GO tools use a large variety of statistical tests whose denominations often do not clarify the underlying P-value computations. Summary: We review the different formulations of the problem and the tests they lead to: the binomial, χ2, equality of two probabilities, Fisher's exact and hypergeometric tests. We clarify the relationships existing between these tests, in particular the equivalence between the hypergeometric test and Fisher's exact test. We recall that the other tests are valid only for large samples, the test of equality of two probabilities and the χ2-test being equivalent. We discuss the appropriateness of one- and two-sided P-values, as well as some discreteness and conservatism issues. Contact:isabelle.rivals@espci.fr Supplementary information: Supplementary data are available at Bioinformatics online.