Gene Set Enrichment Analysis Made Right

Details Gene Set Enrichment Analysis Made Right Gene Set Enrichment Analysis Made Right

2011-10-18

arxiv.org/abs/1110.4128v1

Statistics

Methodology

Submitted to Statistical Methods in Medical Research

Scientific paper

10.1016/j.jbi.2011.12.002

Since its first publication in 2003, the Gene Set Enrichment Analysis (GSEA) method, based on the Kolmogorov-Smirnov statistic, has been both heavily used, modified, and also questioned. Recently a simplified approach using a one-sample t-test score to assess enrichment and ignoring gene-gene correlations was proposed as a serious contender. The argument criticizes GSEA's nonparametric nature and use of an empirical null distribution as unnecessary and hard to compute. We carefully consider this proposed simplified method and GSEA by systematically comparing them on a large benchmark set of 50 datasets. Our results provide strong empirical evidence that gene-gene correlations cannot be ignored and should be taken into account when estimating enrichment significance. In addition, we discuss the challenges that the complex correlation structure and multi-modality of gene sets pose more generally for gene set enrichment methods

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