title: Using GOstats to test gene lists for GO term association.
abstract: BACKGROUND
  Functional analyses based on the association of Gene Ontology (GO) terms to genes in a selected gene list are useful bioinformatic tools and the GOstats package has been widely used to perform such computations. In this paper we report significant improvements and extensions such as support for conditional testing.
  
  
  RESULTS
  We discuss the capabilities of GOstats, a Bioconductor package written in R, that allows users to test GO terms for over or under-representation using either a classical hypergeometric test or a conditional hypergeometric that uses the relationships among GO terms to decorrelate the results.
  
  
  BACKGROUND
  GOstats is available as an R package from the Bioconductor project: http://bioconductor.org
authors.affiliation: Fred Hutchison Cancer Research Center, Program Computational Biology,1100 Fairview Avenue North P. O. Box 19024, Seattle, WA 98109, USA. sfalcon@fhcrc.org
authors.forename: S
authors.initials: S
authors.lastname: Falcon
authors.forename: R
authors.initials: R
authors.lastname: Gentleman
mesh_terms: D000465:Algorithms; D003627:Data Interpretation, Statistical; D003628:Database Management Systems; D030562:Databases, Protein; D020869:Gene Expression Profiling / Q000379:methods; D016247:Information Storage and Retrieval / Q000379:methods*; D009323:Natural Language Processing; D011506:Proteins / Q000737:chemistry / Q000145:classification* / Q000378:metabolism; D012984:Software; D009626:Terminology as Topic
chemical_list: D011506:Proteins