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A comprehensive assessment of somatic mutation detection in cancer using whole-genome sequencing.


ABSTRACT: As whole-genome sequencing for cancer genome analysis becomes a clinical tool, a full understanding of the variables affecting sequencing analysis output is required. Here using tumour-normal sample pairs from two different types of cancer, chronic lymphocytic leukaemia and medulloblastoma, we conduct a benchmarking exercise within the context of the International Cancer Genome Consortium. We compare sequencing methods, analysis pipelines and validation methods. We show that using PCR-free methods and increasing sequencing depth to ? 100 × shows benefits, as long as the tumour:control coverage ratio remains balanced. We observe widely varying mutation call rates and low concordance among analysis pipelines, reflecting the artefact-prone nature of the raw data and lack of standards for dealing with the artefacts. However, we show that, using the benchmark mutation set we have created, many issues are in fact easy to remedy and have an immediate positive impact on mutation detection accuracy.

SUBMITTER: Alioto TS 

PROVIDER: S-EPMC4682041 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

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A comprehensive assessment of somatic mutation detection in cancer using whole-genome sequencing.

Alioto Tyler S TS   Buchhalter Ivo I   Derdak Sophia S   Hutter Barbara B   Eldridge Matthew D MD   Hovig Eivind E   Heisler Lawrence E LE   Beck Timothy A TA   Simpson Jared T JT   Tonon Laurie L   Sertier Anne-Sophie AS   Patch Ann-Marie AM   Jäger Natalie N   Ginsbach Philip P   Drews Ruben R   Paramasivam Nagarajan N   Kabbe Rolf R   Chotewutmontri Sasithorn S   Diessl Nicolle N   Previti Christopher C   Schmidt Sabine S   Brors Benedikt B   Feuerbach Lars L   Heinold Michael M   Gröbner Susanne S   Korshunov Andrey A   Tarpey Patrick S PS   Butler Adam P AP   Hinton Jonathan J   Jones David D   Menzies Andrew A   Raine Keiran K   Shepherd Rebecca R   Stebbings Lucy L   Teague Jon W JW   Ribeca Paolo P   Giner Francesc Castro FC   Beltran Sergi S   Raineri Emanuele E   Dabad Marc M   Heath Simon C SC   Gut Marta M   Denroche Robert E RE   Harding Nicholas J NJ   Yamaguchi Takafumi N TN   Fujimoto Akihiro A   Nakagawa Hidewaki H   Quesada Víctor V   Valdés-Mas Rafael R   Nakken Sigve S   Vodák Daniel D   Bower Lawrence L   Lynch Andrew G AG   Anderson Charlotte L CL   Waddell Nicola N   Pearson John V JV   Grimmond Sean M SM   Peto Myron M   Spellman Paul P   He Minghui M   Kandoth Cyriac C   Lee Semin S   Zhang John J   Létourneau Louis L   Ma Singer S   Seth Sahil S   Torrents David D   Xi Liu L   Wheeler David A DA   López-Otín Carlos C   Campo Elías E   Campbell Peter J PJ   Boutros Paul C PC   Puente Xose S XS   Gerhard Daniela S DS   Pfister Stefan M SM   McPherson John D JD   Hudson Thomas J TJ   Schlesner Matthias M   Lichter Peter P   Eils Roland R   Jones David T W DT   Gut Ivo G IG  

Nature communications 20151209


As whole-genome sequencing for cancer genome analysis becomes a clinical tool, a full understanding of the variables affecting sequencing analysis output is required. Here using tumour-normal sample pairs from two different types of cancer, chronic lymphocytic leukaemia and medulloblastoma, we conduct a benchmarking exercise within the context of the International Cancer Genome Consortium. We compare sequencing methods, analysis pipelines and validation methods. We show that using PCR-free metho  ...[more]

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