Annals of Applied Statistics

On testing the significance of sets of genes

Bradley Efron and Robert Tibshirani

Full-text: Open access


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.

Article information

Ann. Appl. Stat., Volume 1, Number 1 (2007), 107-129.

First available in Project Euclid: 29 June 2007

Permanent link to this document

Digital Object Identifier

Mathematical Reviews number (MathSciNet)

Zentralblatt MATH identifier

Multiple testing gene set enrichment hypothesis testing


Efron, Bradley; Tibshirani, Robert. On testing the significance of sets of genes. Ann. Appl. Stat. 1 (2007), no. 1, 107--129. doi:10.1214/07-AOAS101.

Export citation