Using GOstats to test gene lists for GO term association
S Falcon, R Gentleman - Bioinformatics, 2007 - academic.oup.com
S Falcon, R Gentleman
Bioinformatics, 2007•academic.oup.comMotivation: 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 …
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 …
Abstract
Motivation: 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.
Availability: GOstats is available as an R package from the Bioconductor project:
Contact: sfalcon@fhcrc.org
Oxford University Press