Extensions to gene set enrichment

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Saeed AI, Bhagabati NK, Braisted JC, Liang W, Sharov V, Howe EA, et al. TM4 microarray software suite. Methods in Enzymology. 2006;411:134-93. Abstract

Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, et al. TM4: a free, open-source system for microarray data management and analysis. Vol 34.; 2003.

Publication Type:

Journal Article

Authors:

Jiang,Zhen; Gentleman,Robert

Source:

Bioinformatics (Oxford, England), Volume 23, Issue 3, p.306 - 313 (2007)

ISBN:

1460-2059

URL:

http://www.ncbi.nlm.nih.gov/pubmed/17127676

Keywords:

Gene Set Enrichment Analysis

Abstract:

MOTIVATION: Gene Set Enrichment Analysis (GSEA) has been developed recently to capture changes in the expression of pre-defined sets of genes. We propose number of extensions to GSEA, including the use of different statistics to describe the association between genes and phenotypes of interest. We make use of dimension reduction procedures, such as principle component analysis, to identify gene sets with correlated expression. We also address issues that arise when gene sets overlap. RESULTS: Our proposals extend the range of applicability of GSEA and allow for adjustments based on other covariates. We have provided a well-defined procedure to address interpretation issues that can raise when gene sets have substantial overlap. We have shown how standard dimension reduction methods, such as PCA, can be used to help further interpret GSEA. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.