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Extensive bioinformatics analysis of these datasets of tumor somatic mutations data have revealed the presence of some 500-600 cancer driver genes. The identification of all potential driver mutations affecting cancer genes is essential to implement precision cancer medicine and to understand the interplay of mutation probability and selection in tumor development. Here, we present an in silico saturation mutagenesis approach to identify all drivermutations in 568 cancer genes across 66 tumordoi:10.1101/2020.06.03.130211 fatcat:y3wnbdks3vbhlahkdsrvtpizjy