CRAN

AbsFilterGSEA 1.5.1

Improved False Positive Control of Gene-Permuting GSEA with Absolute Filtering

Released Sep 21, 2017 by Sora Yoon

This package cannot yet be used with Renjin it depends on other packages which are not available: Biobase 2.32.0, DESeq 1.24.0, and RcppArmadillo 0.7.960.1.2

Dependencies

Biobase 2.32.0 DESeq 1.24.0 RcppArmadillo 0.7.960.1.2 Rcpp limma 3.28.21

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.

Source

R
C++

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