FUNC: A package for detecting significant associations between gene sets and ontological annotations

Kay Prüfer, Bjoern Muetzel, Hong Hai Do, Gunter Weiss, Philipp Khaitovich, Erhard Rahm, Svante Pääbo, Michael Lachmann, Wolfgang Enard

Research output: Contribution to journalArticlepeer-review

135 Citations (Scopus)


Background: Genome-wide expression, sequence and association studies typically yield large sets of gene candidates, which must then be further analysed and interpreted. Information about these genes is increasingly being captured and organized in ontologies, such as the Gene Ontology. Relationships between the gene sets identified by experimental methods and biological knowledge can be made explicit and used in the interpretation of results. However, it is often difficult to assess the statistical significance of such analyses since many inter-dependent categories are tested simultaneously. Results: We developed the program package FUNC that includes and expands on currently available methods to identify significant associations between gene sets and ontological annotations. Implemented are several tests in particular well suited for genome wide sequence comparisons, estimates of the family-wise error rate, the false discovery rate, a sensitive estimator of the global significance of the results and an algorithm to reduce the complexity of the results. Conclusion: FUNC is a versatile and useful tool for the analysis of genome-wide data. It is freely available under the GPL license and also accessible via a web service.

Original languageEnglish
Article number41
JournalBMC Bioinformatics
Publication statusPublished - 2007
Externally publishedYes


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