TY - JOUR T1 - A Comprehensive Assessment of Somatic Mutation Calling in Cancer Genomes JF - bioRxiv DO - 10.1101/012997 SP - 012997 AU - Tyler S. Alioto AU - Sophia Derdak AU - Timothy A. Beck AU - Paul C. Boutros AU - Lawrence Bower AU - Ivo Buchhalter AU - Matthew D. Eldridge AU - Nicholas J Harding AU - Lawrence E. Heisler AU - Eivind Hovig AU - David T. W. Jones AU - Andrew G. Lynch AU - Sigve Nakken AU - Paolo Ribeca AU - Anne-Sophie Sertier AU - Jared T. Simpson AU - Paul Spellman AU - Patrick Tarpey AU - Laurie Tonon AU - Daniel Vodák AU - Takafumi N. Yamaguchi AU - Sergi Beltran Agullo AU - Marc Dabad AU - Robert E. Denroche AU - Philip Ginsbach AU - Simon C. Heath AU - Emanuele Raineri AU - Charlotte L. Anderson AU - Benedikt Brors AU - Ruben Drews AU - Roland Eils AU - Akihiro Fujimoto AU - Francesc Castro Giner AU - Minghui He AU - Pablo Hennings-Yeomans AU - Barbara Hutter AU - Natalie Jäger AU - Rolf Kabbe AU - Cyriac Kandoth AU - Semin Lee AU - Louis Létourneau AU - Singer Ma AU - Hidewaki Nakagawa AU - Nagarajan Paramasivam AU - Anne-Marie Patch AU - Myron Peto AU - Matthias Schlesner AU - Sahil Seth AU - David Torrents AU - David A. Wheeler AU - Liu Xi AU - John Zhang AU - Daniela S. Gerhard AU - Víctor Quesada AU - Rafael Valdés-Mas AU - Marta Gut AU - Thomas J. Hudson AU - John D. McPherson AU - Xose S. Puente AU - Ivo G. Gut Y1 - 2014/01/01 UR - http://biorxiv.org/content/early/2014/12/24/012997.abstract N2 - The emergence of next generation DNA sequencing technology is enabling high-resolution cancer genome analysis. Large-scale projects like the International Cancer Genome Consortium (ICGC) are systematically scanning cancer genomes to identify recurrent somatic mutations. Second generation DNA sequencing, however, is still an evolving technology and procedures, both experimental and analytical, are constantly changing. Thus the research community is still defining a set of best practices for cancer genome data analysis, with no single protocol emerging to fulfil this role. Here we describe an extensive benchmark exercise to identify and resolve issues of somatic mutation calling. Whole genome sequence datasets comprising tumor-normal pairs from two different types of cancer, chronic lymphocytic leukaemia and medulloblastoma, were shared within the ICGC and submissions of somatic mutation calls were compared to verified mutations and to each other. Varying strategies to call mutations, incomplete awareness of sources of artefacts, and even lack of agreement on what constitutes an artefact or real mutation manifested in widely varying mutation call rates and somewhat low concordance among submissions. We conclude that somatic mutation calling remains an unsolved problem. However, we have identified many issues that are easy to remedy that are presented here. Our study highlights critical issues that need to be addressed before this valuable technology can be routinely used to inform clinical decision-making.SSMSomatic Single-base Mutations or Simple Somatic Mutations, refers to a somatic single base changeSIMSomatic Insertion/deletion MutationCNVCopy Number VariantSVStructural VariantSNPSingle Nucleotide Polymorphisms, refers to a single base variable position in the germline with a frequency of > 1% in the general populationCLLChronic Lymphocytic LeukaemiaMBMedulloblastomaICGCInternational Cancer Genome ConsortiumBMBenchmarkAbbreviations and Definitionsaligner = mapper, these terms are used interchangeably ER -