@article{3101,
  keywords = {Humans, DNA Mutational Analysis, Mutation, Genomics, Female, Male, Exome, Genetic Predisposition to Disease, Polymorphism, Genetic, Neoplasms, Software, Germ-Line Mutation, Genes, Neoplasm},
  author = {Pawel Przytycki and Mona Singh},
  title = {Differential analysis between somatic mutation and germline variation profiles reveals cancer-related genes.},
  abstract = { <p>A major aim of cancer genomics is to pinpoint which somatically mutated genes are involved in tumor initiation and progression. We introduce a new framework for uncovering cancer genes, differential mutation analysis, which compares the mutational profiles of genes across cancer genomes with their natural germline variation across healthy individuals. We present DiffMut, a fast and simple approach for differential mutational analysis, and demonstrate that it is more effective in discovering cancer genes than considerably more sophisticated approaches. We conclude that germline variation across healthy human genomes provides a powerful means for characterizing somatic mutation frequency and identifying cancer driver genes. DiffMut is available at https://github.com/Singh-Lab/Differential-Mutation-Analysis .</p> },
  year = {2017},
  journal = {Genome Med},
  volume = {9},
  pages = {79},
  month = {2017 Aug 25},
  issn = {1756-994X},
  doi = {10.1186/s13073-017-0465-6},
  language = {eng},
}