Gene set enrichment analysis made simple

Rafael A. Irizarry, Chi Wang, Yun Zhou, Terence P. Speed

Research output: Contribution to journalArticle

Abstract

Among the many applications of microarray technology, one of the most popular is the identification of genes that are differentially expressed in two conditions. A common statistical approach is to quantify the interest of each gene with a p-value, adjust these p-values for multiple comparisons, choose an appropriate cut-off, and create a list of candidate genes. This approach has been criticised for ignoring biological knowledge regarding how genes work together. Recently a series of methods, that do incorporate biological knowledge, have been proposed. However, the most popular method, gene set enrichment analysis (GSEA), seems overly complicated. Furthermore, GSEA is based on a statistical test known for its lack of sensitivity. In this article we compare the performance of a simple alternative to GSEA. We find that this simple solution clearly outperforms GSEA. We demonstrate this with eight different microarray datasets.

Original languageEnglish (US)
Pages (from-to)565-575
Number of pages11
JournalStatistical Methods in Medical Research
Volume18
Issue number6
DOIs
StatePublished - Dec 2009

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Gene
Genes
p-Value
Microarray
Multiple Comparisons
Statistical test
Quantify
Choose
Technology
Series
Alternatives
Demonstrate
Knowledge

ASJC Scopus subject areas

  • Epidemiology
  • Health Information Management
  • Statistics and Probability

Cite this

Irizarry, R. A., Wang, C., Zhou, Y., & Speed, T. P. (2009). Gene set enrichment analysis made simple. Statistical Methods in Medical Research, 18(6), 565-575. https://doi.org/10.1177/0962280209351908

Gene set enrichment analysis made simple. / Irizarry, Rafael A.; Wang, Chi; Zhou, Yun; Speed, Terence P.

In: Statistical Methods in Medical Research, Vol. 18, No. 6, 12.2009, p. 565-575.

Research output: Contribution to journalArticle

Irizarry, RA, Wang, C, Zhou, Y & Speed, TP 2009, 'Gene set enrichment analysis made simple', Statistical Methods in Medical Research, vol. 18, no. 6, pp. 565-575. https://doi.org/10.1177/0962280209351908
Irizarry, Rafael A. ; Wang, Chi ; Zhou, Yun ; Speed, Terence P. / Gene set enrichment analysis made simple. In: Statistical Methods in Medical Research. 2009 ; Vol. 18, No. 6. pp. 565-575.
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