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Table 1 Prediction accuracies for the full dataset

From: Predicting MHC class I epitopes in large datasets

  Allele Name Binders Non-Binders Total DynaPredPOS NetMHC SVMHC YKW
   (n) (n) (n) AUC AUC AUC AUC
1 A*0101 163 1316 1479 0.93 0.98 0.95 0.94
2 A*0201 1544 1929 3473 0.93 0.96 0.92 0.91
3 A*0202 723 697 1420 0.88 0.93 0.85 0.85
4 A*0203 732 685 1417 0.88 0.95 0.86 0.84
5 A*0206 633 782 1415 0.88 0.95 0.87 0.86
6 A*0301 637 1618 2255 0.89 0.96 0.88 0.80
7 A*1101 816 1279 2095 0.92 0.96 0.90 0.91
8 A*2402 202 464 666 0.80 0.85 0.78 0.81
9 A*2601 69 885 954 0.84 0.93 0.83 0.84
10 A*3101 510 1480 1990 0.89 0.95 0.89 0.88
11 A*3301 203 994 1197 0.88 0.96 0.89 0.88
12 A*6801 578 620 1198 0.85 0.92 0.82 0.81
13 A*6802 439 980 1419 0.84 0.93 0.85 0.83
14 B*0702 238 1110 1348 0.94 0.98 0.94 0.93
15 B*0801 23 687 710 0.82 0.99 0.78 0.79
16 B*1501 182 836 1018 0.86 0.97 0.89 0.90
17 B*2705 81 917 998 0.93 0.97 0.90 0.94
18 B*3501 273 578 851 0.83 0.93 0.84 0.85
19 B*4001 94 1112 1206 0.90 0.97 0.93 0.91
20 B*4402 76 136 212 0.77 0.84 0.75 0.76
21 B*4403 71 142 213 0.68 0.81 0.65 0.70
22 B*5101 108 249 357 0.82 0.93 0.80 0.81
23 B*5301 127 228 355 0.86 0.95 0.85 0.87
24 B*5801 78 893 971 0.90 0.99 0.93 0.93
  Average AUC     0.86 0.94 0.86 0.86
  1. Alleles included in the study with the number of binders and non-binders available; all available binders and non-binders were included in the analysis irrespective of whether quantitative laboratory test data was available or not (Dataset F). Only unique peptide sequences were included in the counts; all peptides with more than one entry for a particular allele in IEDB were counted once only. The overall performance of the four prediction models on different alleles is shown; AUC = area under the curve (ROC analysis). The average AUC for each method is included at the bottom of each column.