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

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

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

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[49], glioblastoma(JHU) [50], lung(TSP) [51], pancreatic(JHU) [52];, pancreatic(OICR) and pancreatic(QCMG) are unpublished lists of mutations downloaded through the ICGC data coordination centre [29].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.

ISSN: 1756-994X