title: Overlapping probabilities of top ranking gene lists, hypergeometric distribution, and stringency of gene selection criterion.
abstract: When the same set of genes appear in two top ranking gene lists in two different studies, it is often of interest to estimate the probability for this being a chance event. This overlapping probability is well known to follow the hypergeometric distribution. Usually, the lengths of top-ranking gene lists are assumed to be fixed, by using a pre-set criterion on, e.g., p-value for the t-test. We investigate how overlapping probability changes with the gene selection criterion, or simply, with the length of the top-ranking gene lists. It is concluded that overlapping probability is indeed a function of the gene list length, and its statistical significance should be quoted in the context of gene selection criterion.
authors.affiliation: Regeneron Pharmaceutical Inc., Tarrytown, NY 10591, USA. wen.fury@regeneron.com
authors.forename: Wen
authors.initials: W
authors.lastname: Fury
authors.forename: Franak
authors.initials: F
authors.lastname: Batliwalla
authors.forename: Peter K
authors.initials: PK
authors.lastname: Gregersen
authors.forename: Wentian
authors.initials: W
authors.lastname: Li
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D003627:Data Interpretation, Statistical; D030562:Databases, Protein; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D006801:Humans; D008957:Models, Genetic; D015233:Models, Statistical; D008962:Models, Theoretical; D020411:Oligonucleotide Array Sequence Analysis / Q000295:instrumentation / Q000379:methods*; D010363:Pattern Recognition, Automated; D011336:Probability; D012984:Software