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

Kay Prüfer1*, Bjoern Muetzel1, Hong-Hai Do2, Gunter Weiss1, Philipp Khaitovich13, Erhard Rahm2, Svante Pääbo1, Michael Lachmann1 and Wolfgang Enard1

Author Affiliations

1 Max-Planck-Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany

2 Interdisciplinary Center for Bioinformatics, University of Leipzig, Härtelstr. 16-18, D-04107, Germany

3 Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China

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BMC Bioinformatics 2007, 8:41  doi:10.1186/1471-2105-8-41

Published: 6 February 2007

Abstract

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.