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Table 2 Number of PSMs output by PeptideProphet, Percolator, and OLCS-Ranker

From: A cost-sensitive online learning method for peptide identification

Dataset

Method

FDR = 0.02

FDR = 0.04

  

Targets

Decoys

Ratio

Targets

Decoys

Ratio

Yeast

PepProphet

1379

13

0.206

1436

29

0.214

 

Percolator

1225

12

0.183

1366

27

0.204

 

OLCS-Ranker

1374

13

0.205

1467

29

0.219

Ups1

PepProphet

506

5

0.056

545

11

0.061

 

Percolator

471

4

0.052

554

11

0.062

 

OLCS-Ranker

473

4

0.053

528

10

0.059

Tal08

PepProphet

911

9

0.092

948

20

0.096

 

Percolator

1036

10

0.105

1059

21

0.107

 

OLCS-Ranker

1140

10

0.115

1156

22

0.117

Tal08-large

PepProphet

14966

152

0.354

15516

317

0.367

 

Percolator

15793

159

0.374

16164

329

0.383

 

OLCS-Ranker

15706

157

0.372

16078

327

0.381

Velos-mips

PepProphet

116533

1177

0.558

120080

2450

0.575

 

Percolator

116046

1172

0.556

120952

2468

0.579

 

OLCS-Ranker

117084

1182

0.561

120033

2448

0.575

Velos-nomips

PepProphet

166790

1684

0.542

173935

3549

0.566

 

Percolator

165174

1668

0.537

174361

3558

0.567

 

OLCS-Ranker

170722

1723

0.555

177007

3611

0.576

  1. “Targets”: number of selected target PSMs; “Decoys”: number of selected decoy PSMs; “ratio”: the ratio of the number of selected target PSMs under FDR = 0.04 to the total number of target PSMs in the dataset; “PepProphet”: PeptideProphet