Methodology article

Grouping Gene Ontology terms to improve the assessment of gene set enrichment in microarray data

Alex Lewin¹ and Ian C Grieve²

• Corresponding authors: Alex Lewin a.m.lewin@imperial.ac.uk - Ian C Grieve ian.grieve@imperial.ac.uk

Author Affiliations

¹ Department of Epidemiology and Public Health, Imperial College, Norfolk Place, London W2 1PG, UK

² MRC Clinical Sciences Centre, Imperial College, Hammersmith Hospital, London W12 ONN, UK

BMC Bioinformatics 2006, 7:426 doi:10.1186/1471-2105-7-426

Published: 3 October 2006

Abstract

Background

Gene Ontology (GO) terms are often used to assess the results of microarray experiments. The most common way to do this is to perform Fisher's exact tests to find GO terms which are over-represented amongst the genes declared to be differentially expressed in the analysis of the microarray experiment. However, due to the high degree of dependence between GO terms, statistical testing is conservative, and interpretation is difficult.

Results

We propose testing groups of GO terms rather than individual terms, to increase statistical power, reduce dependence between tests and improve the interpretation of results. We use the publicly available package POSOC to group the terms. Our method finds groups of GO terms significantly over-represented amongst differentially expressed genes which are not found by Fisher's tests on individual GO terms.

Conclusion

Grouping Gene Ontology terms improves the interpretation of gene set enrichment for microarray data.