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Table 6 The extended LOO benchmark

From: NetMHCIIpan-2.0 - Improved pan-specific HLA-DR predictions using a novel concurrent alignment and weight optimization training procedure

   

OLD

NEW

TEPITOPE

Allele

#

#bind

PCC

AUC

NN

dist

PCC

AUC

NN

dist

AUC

DRB1*0101

7685

4382

0.567

0.767

DRB1*0401

0.352

0.583

0.786

DRB1*1402

0.322

0.727

DRB1*0301

2505

649

0.433

0.727

DRB3*0101

0.277

0.499

0.765

DRB1*0302

0.156

0.718

DRB1*0401

3116

1039

0.563

0.787

DRB1*0405

0.066

0.594

0.804

DRB1*0405

0.066

0.762

DRB1*0404

577

336

0.592

0.806

DRB1*0401

0.091

0.595

0.804

DRB1*0401

0.091

0.747

DRB1*0405

1582

627

0.638

0.826

DRB1*0401

0.066

0.633

0.833

DRB1*0401

0.066

 

DRB1*0701

1745

849

0.659

0.831

DRB1*0901

0.504

0.648

0.826

DRB1*0901

0.504

0.780

DRB1*0802

1520

431

0.380

0.710

DRB1*1101

0.111

0.369

0.692

DRB1*0813

0.041

0.777

DRB1*0901

1520

622

0.539

0.757

DRB5*0101

0.431

0.517

0.762

DRB5*0101

0.431

0.645

DRB1*1101

1794

778

0.602

0.799

DRB1*1302

0.084

0.460

0.741

DRB1*1302

0.084

 

DRB1*1302

1580

493

0.338

0.691

DRB1*1101

0.084

0.323

0.671

DRB1*1101

0.084

0.793

DRB1*1501

1769

709

0.568

0.775

DRB1*0404

0.295

0.525

0.756

DRB1*0404

0.295

0.596

DRB3*0101

1501

281

0.339

0.672

DRB1*0301

0.277

0.374

0.702

DRB3*0301

0.223

0.731

DRB4*0101

1521

485

0.506

0.753

DRB1*0404

0.397

0.518

0.766

DRB1*0404

0.397

 

DRB5*0101

3106

1280

0.547

0.781

DRB1*1101

0.295

0.608

0.813

DRB1*1101

0.295

 

DRB1*0302

148

44

0.396

0.729

DRB1*0301

0.156

0.542

0.759

DRB1*1402

0.119

0.760

DRB1*0806

118

91

0.670

0.886

DRB1*0802

0.107

0.703

0.902

DRB1*0802

0.107

 

DRB1*0813

1370

455

0.505

0.735

DRB1*0802

0.041

0.340

0.666

DRB1*0802

0.041

0.884

DRB1*0819

116

54

0.567

0.789

DRB1*0802

0.107

0.566

0.813

DRB1*0813

0.083

0.750

DRB1*1201

117

81

0.626

0.786

DRB1*1101

0.445

0.609

0.798

DRB1*1202

0.045

 

DRB1*1202

117

79

0.623

0.814

DRB1*1101

0.399

0.713

0.879

DRB1*1201

0.045

 

DRB1*1402

118

78

0.570

0.793

DRB1*1101

0.148

0.659

0.846

DRB1*0302

0.119

 

DRB1*1404

30

16

0.393

0.594

DRB1*0404

0.311

0.646

0.679

DRB1*0806

0.240

 

DRB1*1412

116

63

0.640

0.845

DRB1*0802

0.180

0.738

0.897

DRB1*0813

0.139

 

DRB3*0301

160

70

0.395

0.738

DRB3*0101

0.223

0.545

0.765

DRB3*0101

0.223

 

Ave

  

0.527

0.766

  

0.554

0.780

   

Ave*

  

0.543

0.779

  

0.529

0.774

  

0.744

Ave**

  

0.539

0.771

  

0.606

0.800

   
  1. The predictive performance of the pan-specific NN-align method when trained in a leave-one-out experiment and evaluated on the 24 alleles included in the new peptide binding data set.
  2. # is the number of peptide binding data for each allele, #bind is the number of peptides with a binding affinity stronger than 500 nM. OLD is the method described here trained on the old peptide data set, NEW is the method described here trained on the new data set, and TEPITOPE is the method by Sturniolo et al. [1]. NN is the nearest neighbor as defined by the pseudo sequence distance, and dist is the nearest neighbor distance calculated as described in Materials and methods. Ave is the per allele average, Ave* is the per allele average of the 13 alleles characterized by the TEPITOPE method, and Ave** is the per-allele average performance of the 10 alleles included in the new peptide binding data set. In bold is highlighted the best performing method for each of the 24 alleles. AUC values were calculated using a binding threshold of 500 nM. Only AUC values are included for the TEPITOPE method since prediction values for this method are not linearly related to the binding affinity. The double line separates the 10 novel alleles from the original 14 alleles included in the development of the NetMHCIIpan-1.0 method.