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Computational performance and accuracy of Sentieon DNASeq variant calling workflow

Katherine I. Kendig, Saurabh Baheti, Matthew A. Bockol, Travis M. Drucker, Steven N. Hart, Jacob R. Heldenbrand, Mikel Hernaez, Matthew E. Hudson, Michael T. Kalmbach, Eric W. Klee, Nathan R. Mattson, Christian A. Ross, Morgan Taschuk, Eric D. Wieben, Mathieu Wiepert, Derek E. Wildman, Liudmila S. Mainzer
doi: https://doi.org/10.1101/396325
Katherine I. Kendig
1National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, USA
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Saurabh Baheti
2Mayo Clinic, Department of Research Services, Rochester, MN, USA
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Matthew A. Bockol
3Mayo Clinic, Department of IT Executive Administration, Rochester, MN, USA
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Travis M. Drucker
3Mayo Clinic, Department of IT Executive Administration, Rochester, MN, USA
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Steven N. Hart
4Mayo Clinic, Department of Health Sciences Research, Rochester, MN, USA
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Jacob R. Heldenbrand
1National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, USA
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Mikel Hernaez
5Institute for Genomic Biology, University of Illinois at Urbana-Champaign, USA
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Matthew E. Hudson
5Institute for Genomic Biology, University of Illinois at Urbana-Champaign, USA
6Department of Crop Sciences, University of Illinois at Urbana-Champaign, USA
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Michael T. Kalmbach
3Mayo Clinic, Department of IT Executive Administration, Rochester, MN, USA
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Eric W. Klee
4Mayo Clinic, Department of Health Sciences Research, Rochester, MN, USA
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Nathan R. Mattson
3Mayo Clinic, Department of IT Executive Administration, Rochester, MN, USA
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Christian A. Ross
3Mayo Clinic, Department of IT Executive Administration, Rochester, MN, USA
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Morgan Taschuk
9Genome Sequence Informatics, Ontario Institute for Cancer Research, Toronto, Ontario, Canada
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Eric D. Wieben
7Mayo Clinic, Department of Biochemistry and Molecular Biology, Rochester, MN, USA
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Mathieu Wiepert
3Mayo Clinic, Department of IT Executive Administration, Rochester, MN, USA
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Derek E. Wildman
5Institute for Genomic Biology, University of Illinois at Urbana-Champaign, USA
8Department of Molecular and Integrative Physiology, University of Illinois at Urbana-Champaign, USA
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Liudmila S. Mainzer
1National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, USA
5Institute for Genomic Biology, University of Illinois at Urbana-Champaign, USA
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  • For correspondence: lmainzer@illinois.edu
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Abstract

As reliable, efficient genome sequencing becomes more ubiquitous, the need for similarly reliable and efficient variant calling becomes increasingly important. The Genome Analysis Toolkit (GATK), maintained by the Broad Institute, is currently the widely accepted standard for variant calling software. However, alternative solutions may provide faster variant calling without sacrificing accuracy. One such alternative is Sentieon DNASeq, a toolkit analogous to GATK but built on a highly optimized backend. We evaluated the DNASeq single-sample variant calling pipeline in comparison to that of GATK. Our results confirm the near-identical accuracy of the two software packages, showcase perfect scalability and great speed from Sentieon, and describe computational performance considerations for the deployment of Sentieon DNASeq.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted August 20, 2018.
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Computational performance and accuracy of Sentieon DNASeq variant calling workflow
Katherine I. Kendig, Saurabh Baheti, Matthew A. Bockol, Travis M. Drucker, Steven N. Hart, Jacob R. Heldenbrand, Mikel Hernaez, Matthew E. Hudson, Michael T. Kalmbach, Eric W. Klee, Nathan R. Mattson, Christian A. Ross, Morgan Taschuk, Eric D. Wieben, Mathieu Wiepert, Derek E. Wildman, Liudmila S. Mainzer
bioRxiv 396325; doi: https://doi.org/10.1101/396325
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Computational performance and accuracy of Sentieon DNASeq variant calling workflow
Katherine I. Kendig, Saurabh Baheti, Matthew A. Bockol, Travis M. Drucker, Steven N. Hart, Jacob R. Heldenbrand, Mikel Hernaez, Matthew E. Hudson, Michael T. Kalmbach, Eric W. Klee, Nathan R. Mattson, Christian A. Ross, Morgan Taschuk, Eric D. Wieben, Mathieu Wiepert, Derek E. Wildman, Liudmila S. Mainzer
bioRxiv 396325; doi: https://doi.org/10.1101/396325

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