On testing the significance of sets of genes

Details On testing the significance of sets of genes On testing the significance of sets of genes

2006-10-22

arxiv.org/abs/math/0610667v2

Annals of Applied Statistics 2007, Vol. 1, No. 1, 107-129

Mathematics

Statistics Theory

Published at http://dx.doi.org/10.1214/07-AOAS101 in the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Ins

Scientific paper

10.1214/07-AOAS101

This paper discusses the problem of identifying differentially expressed groups of genes from a microarray experiment. The groups of genes are externally defined, for example, sets of gene pathways derived from biological databases. Our starting point is the interesting Gene Set Enrichment Analysis (GSEA) procedure of Subramanian et al. [Proc. Natl. Acad. Sci. USA 102 (2005) 15545--15550]. We study the problem in some generality and propose two potential improvements to GSEA: the maxmean statistic for summarizing gene-sets, and restandardization for more accurate inferences. We discuss a variety of examples and extensions, including the use of gene-set scores for class predictions. We also describe a new R language package GSA that implements our ideas.

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