Rapid and efficient analysis of 20,000 RNA-seq samples with Toil

John Vivian; Arjun Rao; Frank Austin Nothaft; Christopher Ketchum; Joel Armstrong; Adam Novak; Jacob Pfeil; Jake Narkizian; Alden D. Deran; Audrey Musselman-Brown; Hannes Schmidt; Peter Amstutz; Brian Craft; Mary Goldman; Kate Rosenbloom; Melissa Cline; Brian O'Connor; Megan Hanna; Chet Birger; W. James Kent; David A. Patterson; Anthony D. Joseph; Jingchun Zhu; Sasha Zaranek; Gad Getz; David Haussler; Benedict Paten

doi:10.1101/062497

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bioRxiv · 10.1101/062497

Rapid and efficient analysis of 20,000 RNA-seq samples with Toil

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Abstract

Toil is portable, open-source workflow software that supports contemporary workflow definition languages and can be used to securely and reproducibly run scientific workflows efficiently at large-scale. To demonstrate Toil, we processed over 20,000 RNA-seq samples to create a consistent meta-analysis of five datasets free of computational batch effects that we make freely available. Nearly all the samples were analysed in under four days using a commercial cloud cluster of 32,000 preemptable cores.

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John Vivian, Arjun Rao, Frank Austin Nothaft, Christopher Ketchum, Joel Armstrong, Adam Novak, Jacob Pfeil, Jake Narkizian, Alden D. Deran, Audrey Musselman-Brown, Hannes Schmidt, Peter Amstutz, Brian Craft, Mary Goldman, Kate Rosenbloom, Melissa Cline, Brian O'Connor, Megan Hanna, Chet Birger, W. James Kent, David A. Patterson, Anthony D. Joseph, Jingchun Zhu, Sasha Zaranek, Gad Getz, David Haussler, Benedict Paten. 2016-07-07. Rapid and efficient analysis of 20,000 RNA-seq samples with Toil. https://doi.org/10.1101/062497

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