title: EMu: probabilistic inference of mutational processes and their localization in the cancer genome.
abstract: The spectrum of mutations discovered in cancer genomes can be explained by the activity of a few elementary mutational processes. We present a novel probabilistic method, EMu, to infer the mutational signatures of these processes from a collection of sequenced tumors. EMu naturally incorporates the tumor-specific opportunity for different mutation types according to sequence composition. Applying EMu to breast cancer data, we derive detailed maps of the activity of each process, both genome-wide and within specific local regions of the genome. Our work provides new opportunities to study the mutational processes underlying cancer development. EMu is available at http://www.sanger.ac.uk/resources/software/emu/.
authors.forename: Andrej
authors.initials: A
authors.lastname: Fischer
authors.forename: Christopher J R
authors.initials: CJ
authors.lastname: Illingworth
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Campbell
authors.forename: Ville
authors.initials: V
authors.lastname: Mustonen
mesh_terms: D001943:Breast Neoplasms / Q000235:genetics*; D004273:DNA, Neoplasm / Q000235:genetics*; D005260:Female; D015894:Genome, Human; D006801:Humans; D016296:Mutagenesis; D011336:Probability; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software
chemical_list: D004273:DNA, Neoplasm