Table 4

A sensitivity analysis using simulated data in the absence and presence of overlap between gene sets
Scenario GSA GSEA PADOG Setup I PADOG Setup II PADOG Setup III
1 5e-04 0.0015 0.0121 0.0378 0.0067
2 0.0276 0.225 0.0113 0.0374 0.0059
3 0.0654 0.2539 0.0133 0.0397 0.0111
4 0.0103 0.1535 0.0018 0.0271 3e-04
5 0.0161 0.2352 0.0011 0.016 1e-04

The table shows the mean p-values for GS1 (designed to be relevant to the phenotype) over 50 different trials in each of the 5 different scenarios. GSA and GSEA p-values do not change if genes in GS1 are found in other gene sets as well. Results for PADOG are given in the absence of overlap (Setup I), presence of overlap between the genes designed to be DE in GS1 and other gene sets (Setup II), and presence of overlap between the non-DE genes of GS1 and other gene sets (Setup III). All methods used 1000 permutations to compute the two sided p-values for GS1. Best values are shown in bold and second best are italicized.

Tarca et al.

Tarca et al. BMC Bioinformatics 2012 13:136   doi:10.1186/1471-2105-13-136

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