Analysis of Mutational Signatures Using the mutSignatures R Library

Abstract

Accumulation of somatic mutations is a hallmark of cancer. Defects in DNA metabolism and DNA repair and exposure to mutagens may result in characteristic nonrandom profiles of DNA mutations, also known as mutational signatures. Resolving mutational signatures can help identifying genetic instability processes active in human cancer samples, and there is an expectation that this information might be exploited in the future for drug discovery and personalized treatment.Here we show how to analyze bladder cancer mutation data using mutSignatures, an open-source R-based computational framework aimed at investigating DNA mutational signatures. We illustrate the typical steps of a mutational signature analysis. We start by importing and pre-processing mutation data from a list of Variant Call Format (VCF) files. Next, we show how to perform de novo mutational signature extraction and how to determine activity of previously resolved mutational signatures, including Catalogue of Somatic Mutations In Cancer (COSMIC) signatures. Finally, we provide insights into parameter selection, algorithm tuning, and data visualization.Overall, the chapter guides the reader through all steps of a mutational signature analysis using R and mutSignatures, a software that may help gathering insights into genetic instability and cancer biology.

Keywords: Cancer genomics; Deconvolution; Genetic instability; Mutational signatures; Nonnegative matrix factorization; Software; Somatic mutations.