Handling multiple testing while interpreting microarrays with the gene oncology database

Abstract

Background: The development of software tools that analyze microarray data in the context of genetic knowledgebases is being pursued by multiple research groups using different methods. A common problem for many of these tools is how to correct for multiple statistical testing since simple corrections are overly conservative and more sophisticated corrections are currently impractical. A careful study of the nature of the distribution one would expect by chance, such as by a simulation study, may be able to guide the development of an appropriate correction that is not overly time consuming computationally. Results: We present the results from a preliminary study of the distribution one would expect for analyzing sets of genes extracted from Drosophila, S. cerevisiae, Wormbase, and Gramene databases using the Gene Ontology Database. Conclusions: We found that the estimated distribution is not regular and is not predictable outside of a particular set of genes. Permutation-based simulations may be necessary to determine the confidence in results of such analyses. © 2004 Osier et al; licensee BioMed Central Ltd.