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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