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Nucleic Acids Research, Vol. 40, No. 17. (01 September 2012), pp. e133-e133, doi:10.1093/nar/gks461 Key: citeulike:11329923
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Competitive gene set tests are commonly used in molecular pathway analysis to test for enrichment of a particular gene annotation category amongst the differential expression results from a microarray experiment. Existing gene set tests that rely on gene permutation are shown here to be extremely sensitive to inter-gene correlation. Several data sets are analyzed to show that inter-gene correlation is non-ignorable even for experiments on homogeneous cell populations using genetically identical model organisms. A new gene set test procedure (CAMERA) is proposed based on the idea of estimating the inter-gene correlation from the data, and using it to adjust the gene set test statistic. An efficient procedure is developed for estimating the inter-gene correlation and characterizing its precision. CAMERA is shown to control the type I error rate correctly regardless of inter-gene correlations, yet retains excellent power for detecting genuine differential expression. Analysis of breast cancer data shows that CAMERA recovers known relationships between tumor subtypes in very convincing terms. CAMERA can be used to analyze specified sets or as a pathway analysis tool using a database of molecular signatures.
New competitive gene set enrichment test from Smyth. Exploits the same idea of linear model and moderated T-statistics (now besides limma for gene-wise test, they also introduce special gene set statistic, which corrects for inter-gene correlations). May be useful to have this method at hand (it is not computationally expensive, as all is computed numerically, without permutations
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