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Table 1 Number of somatic mutations contributed by 12 cancer genome-sequencing projects to conform some of the proxy datasets

From: Improving the prediction of the functional impact of cancer mutations by baseline tolerance transformation

Tumor datasets Samples analyzed Genes with non-synonymous mutations Non-synonymous mutations Center Source
breast(JHU) 39 483 649 Johns Hopkins University ICGC DCC
breast(WTSI) 100 3644 5,189 Sanger Center (ICGC) ICGC DCC
ovary(TCGA) 316 7082 12,819 TCGA MEMo
CLL(MICINN) 109 944 1,160 MICINN (ICGC) ICGC DCC
colorectal(JHU) 34 415 600 Johns Hopkins University ICGC DCC
pediatricbrain(DKFZ) 109 604 730 DKFZ (ICGC) ICGC DCC
glioblastoma(TCGA) 139 400 740 TCGA MEMo
glioblastoma(JHU) 77 1,269 1,536 Johns Hopkins University ICGC DCC
lung(TSP) 153 320 755 Washington University School of Medicine ICGC DCC
pancreatic(JHU) 112 737 962 Johns Hopkins University ICGC DCC
pancreatic(OICR) 34 1,361 1,792 OICR (ICGC) ICGC DCC
pancreatic(QCMG) 67 847 1,033 QCMG (ICGC) ICGC DCC
  1. Only mutations successfully scored by at least one method were included. Original sources: breast(JHU) [40, 41], breast(WTSI) [42], ovary(The Cancer Gene Atlas) [43], CLL(MICINN) [44, 45], colorectal(JHU) [40, 46], pediatricbrain(DKFZ) [47, 48], glioblastoma(TCGA) [49], glioblastoma(JHU) [50], lung(TSP) [51], pancreatic(JHU) [52];, pancreatic(OICR) and pancreatic(QCMG) are unpublished lists of mutations downloaded through the ICGC data coordination centre [29]. DKFZ, German Cancer Res Center; ICGC, Data Coordination Center [29]; MEMo, datasets of mutations packed with the software implementing the MEMo algorithm [30]; MICINN, Spanish Ministry of Science and Innovation; OICR, Ontario Institute for Cancer Research; QCMG, Queensland Centre for Medical Genomics.