A Simple Model-Based Approach to Inferring and Visualizing Cancer Mutation Signatures

Recent advances in sequencing technologies have enabled the production of massive amounts of data on somatic mutations from cancer genomes. These data have led to the detection of characteristic patterns of somatic mutations or "mutation signatures" at an unprecedented resolution, with the...

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Bibliographic Details
Published in:	PLoS genetics Vol. 11; no. 12; p. e1005657
Main Authors:	Shiraishi, Yuichi, Tremmel, Georg, Miyano, Satoru, Stephens, Matthew
Format:	Journal Article
Language:	English
Published:	United States Public Library of Science 01.12.2015 Public Library of Science (PLoS)
Subjects:	Algorithms Amino Acid Substitution - genetics Binding sites Cancer Carcinoma - genetics Carcinoma - pathology Cell growth Cluster Analysis Deoxyribonucleic acid DNA DNA Mutational Analysis Epigenomics Experiments Gene mutations Genetic aspects Genome Genomes Humans Laboratories Melanoma Metastasis Methods Models, Statistical Models, Theoretical Mutation Mutation - genetics Neoplasms - genetics Neoplasms - pathology Observations Tobacco smoke Transcription, Genetic Visualization
ISSN:	1553-7404, 1553-7390, 1553-7404
Online Access:	Get full text
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