GOstats

GOstats performs Gene Ontology enrichment analysis to identify over- and under-represented GO terms in gene lists.

Key Features:

• Gene Ontology association: Associates genes from selected gene lists with Gene Ontology (GO) terms to characterize biological processes, cellular components, and molecular functions.
• Statistical testing for over/under-representation: Performs classical hypergeometric test and conditional hypergeometric test to evaluate enrichment and depletion of GO terms.
• Support for conditional testing: Implements conditional testing that accounts for dependencies among GO terms to decorrelate results and reduce redundancy.
• Implementation: Implemented in R and distributed via the Bioconductor project.

Scientific Applications:

• Microarray data analysis: Identifies functional categories associated with differentially expressed genes from microarray datasets.
• Genomic studies: Aids interpretation of large-scale genomic data by linking observed gene sets or genetic variations to biological functions and processes via GO terms.

Methodology:

Associates genes with GO terms and applies classical and conditional hypergeometric tests, where the conditional test accounts for the GO hierarchical structure and decorrelates term results.