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Cancer cells accumulate DNA mutations as result of DNA damage and DNA repair processes. This computational framework is aimed at deciphering DNA mutational signatures operating in cancer. The input is a numeric matrix of DNA mutation counts detected in a panel of cancer samples. The framework performs Non-negative Matrix Factorization to extract the most likely signatures explaining the observed set of DNA mutations. The framework relies on parallelization and is optimized for use on multi-core systems. This framework is an R-based implementation of the original MATLAB WTSI framework by Alexandrov LB et al (2013) <DOI:10.1016/j.celrep.2012.12.008>.

Damiano Fantini

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