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Table 2 Benchmarking results for SetRank compared to other methods

From: Avoiding the pitfalls of gene set enrichment analysis with SetRank

Method Sensitivity Prioritization Specificity
PLAGE [28] 0.0022 25.00% 1.10%
GLOBALTEST [29] 0.0001 27.90% 2.00%
PADOG [7] 0.096 9.70% 2.50%
ORA 0.0732 18.30% 2.50%
SAFE [30] 0.1065 18.80% 1.30%
SIGPATHWAY Q2 [31] 0.0565 38.00% 0.90%
GSA [32] 0.142 21.00% 1.30%
SSGSEA [33] 0.0808 40.30% 1.00%
ZSCORE [34] 0.095 39.80% 1.00%
GSEA [35] 0.1801 33.10% 2.30%
GSVA [36] 0.1986 51.50% 1.10%
CAMERA [37] 0.3126 43.00% 0.50%
MRGSE [38] 0.01 18.80% 4.90%
GSEAP 0.0644 36.20% 15.80%
GAGE [39] 0.0024 35.90% 37.90%
SIGPATHWAY. Q1 0.1165 49.70% 17.20%
SetRank filtered 1.0 0.75% (10) 0.09%
no filter 1.0 2.05% (10)
  1. Scores for other methods are taken from Tarca et al. [7]. The best score in each category is highlighted in italic. Note that the prioritisation score for SetRank is based only on the datasets where the target set could be ranked. The numbers in brackets indicates the number of datasets where this was the case