The Annals of Applied Statistics

On testing the significance of sets of genes

Bradley Efron and Robert Tibshirani
Source: Ann. Appl. Stat. Volume 1, Number 1 (2007), 107-129.

Abstract

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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Links and Identifiers

Permanent link to this document: http://projecteuclid.org/euclid.aoas/1183143731
Digital Object Identifier: doi:10.1214/07-AOAS101
Mathematical Reviews number (MathSciNet): MR2393843
Zentralblatt MATH identifier: 1129.62102


2013 © Institute of Mathematical Statistics

The Annals of Applied Statistics

The Annals of Applied Statistics

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