Quantitative set analysis for gene expression: a method to quantify gene set differential expression including gene-gene correlations.

ABSTRACT: Enrichment analysis of gene sets is a popular approach that provides a functional interpretation of genome-wide expression data. Existing tests are affected by inter-gene correlations, resulting in a high Type I error. The most widely used test, Gene Set Enrichment Analysis, relies on computationally intensive permutations of sample labels to generate a null distribution that preserves gene-gene correlations. A more recent approach, CAMERA, attempts to correct for these correlations by estimating a variance inflation factor directly from the data. Although these methods generate P-values for detecting gene set activity, they are unable to produce confidence intervals or allow for post hoc comparisons. We have developed a new computational framework for Quantitative Set Analysis of Gene Exp

SUBMITTER: Yaari G 

PROVIDER: S-EPMC3794608 | biostudies-literature | 2013 Oct

REPOSITORIES: biostudies-literature