A comprehensive multicenter comparison of whole genome sequencing pipelines using a uniform tumor-normal sample pair
By
Ivo Buchhalter,
Barbara Hutter,
Tyler S. Alioto,
Timothy A Beck,
Paul C Boutros,
Benedikt Brors,
Adam P Butler,
Sasithorn Chotewutmontri,
Robert E. Denroche,
Sophia Derdak,
Nicolle Diessl,
Lars Feuerbach,
Akihiro Fujimoto,
Susanne Gröbner,
Ivo Glynne Gut,
Nicholas J. Harding,
Michael Heinold,
Lawrence E Heisler,
Jonathan Hinton,
Natalie Jäger,
David Jones,
Rolf Kabbe,
Andrey Korshunov,
John D. McPherson,
Andrew Menzies,
Hidewaki Nakagawa,
Christopher Previti,
Keiran Raine,
Paolo Ribeca,
Sabine Schmidt,
Rebecca Shepherd,
Lucy Stebbings,
Patrick S Tarpey,
Jon W Teague,
Laurie Tonon,
David A. Wheeler,
Liu Xi,
Takafumi N. Yamaguchi,
Anne-Sophie Sertier,
Stefan M. Pfister,
Peter J. Campbell,
Matthias Schlesner,
Peter Lichter,
Roland Eils,
Ivo G. Gut,
David T. W. Jones,
on behalf of the ICGC Verification and Validation Working Group
Posted 24 Dec 2014
bioRxiv DOI: 10.1101/013177
As next-generation sequencing becomes a clinical tool, a full understanding of the variables affecting sequencing analysis output is required. Through the International Cancer Genome Consortium (ICGC), we compared sequencing pipelines at five independent centers (CNAG, DKFZ, OICR, RIKEN and WTSI) using a single tumor-blood DNA pair. Analyses by each center and with one standardized algorithm revealed significant discrepancies. Although most pipelines performed well for coding mutations, library preparation methods and sequencing coverage metrics clearly influenced downstream results. PCR-free methods showed reduced GC-bias and more even coverage. Increasing sequencing depth to ~100x (two- to three-fold higher than current standards) showed a benefit, as long as the tumor:control coverage ratio remained balanced. To become part of routine clinical care, high-throughput sequencing must be globally compatible and comparable. This benchmarking exercise has highlighted several fundamental parameters to consider in this regard, which will allow for better optimization and planning of both basic and translational studies.
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