A comprehensive assessment of somatic mutation detection in cancer using whole-genome sequencing
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Author
Alioto, Tyler S.
Buchhalter, Ivo
Derdak, Sophia
Hutter, Barbara
Eldridge, Matthew D.
Hovig, Eivind
Heisler, Lawrence E.
Beck, Timothy A.
Simpson, Jared T.
Tonon, Laurie
Sertier, Anne-Sophie
Patch, Ann-Marie
Jäger, Natalie
Ginsbach, Philip
Drews, Ruben
Paramasivam, Nagarajan
Kabbe, Rolf
Chotewutmontri, Sasithorn
Diessl, Nicolle
Previti, Christopher
Schmidt, Sabine
Brors, Benedikt
Feuerbach, Lars
Heinold, Michael
Gröbner, Susanne
Korshunov, Andrey
Tarpey, Patrick S.
Butler, Adam P.
Hinton, Jonathan
Jones, David
Menzies, Andrew
Raine, Keiran
Shepherd, Rebecca
Stebbings, Lucy
Teague, Jon W.
Ribeca, Paolo
Giner, Francesc Castro
Beltran, Sergi
Raineri, Emanuele
Dabad, Marc
Heath, Simon C.
Gut, Marta
Denroche, Robert E.
Harding, Nicholas J.
Yamaguchi, Takafumi N.
Fujimoto, Akihiro
Nakagawa, Hidewaki
Quesada, Víctor
Valdés-Mas, Rafael
Nakken, Sigve
Vodák, Daniel
Bower, Lawrence
Lynch, Andrew G.
Anderson, Charlotte L.
Waddell, Nicola
Pearson, John V.
Grimmond, Sean M.
Peto, Myron
Spellman, Paul
He, Minghui
Kandoth, Cyriac
Zhang, John
Létourneau, Louis
Ma, Singer
Seth, Sahil
Torrents, David
Xi, Liu
Wheeler, David A.
López-Otín, Carlos
Campo, Elías
Campbell, Peter J.
Boutros, Paul C.
Puente, Xose S.
Gerhard, Daniela S.
Pfister, Stefan M.
McPherson, John D.
Hudson, Thomas J.
Schlesner, Matthias
Lichter, Peter
Eils, Roland
Jones, David T. W.
Gut, Ivo G.
Note: Order does not necessarily reflect citation order of authors.
Published Version
https://doi.org/10.1038/ncomms10001Metadata
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Alioto, T. S., I. Buchhalter, S. Derdak, B. Hutter, M. D. Eldridge, E. Hovig, L. E. Heisler, et al. 2015. “A comprehensive assessment of somatic mutation detection in cancer using whole-genome sequencing.” Nature Communications 6 (1): 10001. doi:10.1038/ncomms10001. http://dx.doi.org/10.1038/ncomms10001.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.Other Sources
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4682041/pdf/Terms of Use
This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAACitable link to this page
http://nrs.harvard.edu/urn-3:HUL.InstRepos:23993535
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