Improved False Positive Control of Gene-Permuting GSEA with Absolute Filtering
Released Sep 21, 2017 by Sora Yoon
Gene-set enrichment analysis (GSEA) is popularly used to assess the enrichment of differential signal in a pre-defined gene-set without using a cutoff threshold for differential expression. The significance of enrichment is evaluated through sample- or gene-permutation method. Although the sample-permutation approach is highly recommended due to its good false positive control, we must use gene-permuting method if the number of samples is small. However, such gene-permuting GSEA (or preranked GSEA) generates a lot of false positive gene-sets as the inter-gene correlation in each gene set increases. These false positives can be successfully reduced by filtering with the one-tailed absolute GSEA results. This package provides a function that performs gene-permuting GSEA calculation with or without the absolute filtering. Without filtering, users can perform (original) two-tailed or one-tailed absolute GSEA.