PEMapper and PECaller provide a simplified approach to whole-genome sequencing

H. Richard Johnston; Pankaj Chopra; Thomas S. Wingo; Viren Patel; Michael P. Epstein; Jennifer G. Mulle; Stephen T. Warren; Michael E. Zwick; Inter Consortium Brain Behav 22q11; Thérèse van Amelsvoort; David J. Cutler

doi:10.1073/pnas.1618065114

PEMapper and PECaller provide a simplified approach to whole-genome sequencing

H. Richard Johnston, Pankaj Chopra, Thomas S. Wingo, Viren Patel, Michael P. Epstein, Jennifer G. Mulle, Stephen T. Warren^*, Michael E. Zwick^*, Inter Consortium Brain Behav 22q11, Thérèse van Amelsvoort, David J. Cutler^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

The analysis of human whole-genome sequencing data presents significant computational challenges. The sheer size of datasets places an enormous burden on computational, disk array, and network resources. Here, we present an integrated computational package, PEMapper/PECaller, that was designed specifically to minimize the burden on networks and disk arrays, create output files that are minimal in size, and run in a highly computationally efficient way, with the single goal of enabling whole-genome sequencing at scale. In addition to improved computational efficiency, we implement a statistical framework that allows for a base by base error model, allowing this package to perform as well or better than the widely used Genome Analysis Toolkit (GATK) in all key measures of performance on human whole-genome sequences.

Original language	English
Pages (from-to)	E1923-E1932
Number of pages	10
Journal	Proceedings of the National Academy of Sciences of the United States of America
Volume	114
Issue number	10
DOIs	https://doi.org/10.1073/pnas.1618065114
Publication status	Published - 7 Mar 2017

Keywords

genome sequencing
GATK
sequence mapping
SNP calling
software
22Q11.2 DELETION SYNDROME
EXOME VARIANTS
GENERATION
SCHIZOPHRENIA
FRAMEWORK
ALIGNMENT
HUMANS
NUMBER
TOOLS
RISK

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10.1073/pnas.1618065114

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Johnston, H. R., Chopra, P., Wingo, T. S., Patel, V., Epstein, M. P., Mulle, J. G., Warren, S. T., Zwick, M. E., Inter Consortium Brain Behav 22q11, van Amelsvoort, T., & Cutler, D. J. (2017). PEMapper and PECaller provide a simplified approach to whole-genome sequencing. Proceedings of the National Academy of Sciences of the United States of America, 114(10), E1923-E1932. https://doi.org/10.1073/pnas.1618065114

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title = "PEMapper and PECaller provide a simplified approach to whole-genome sequencing",

abstract = "The analysis of human whole-genome sequencing data presents significant computational challenges. The sheer size of datasets places an enormous burden on computational, disk array, and network resources. Here, we present an integrated computational package, PEMapper/PECaller, that was designed specifically to minimize the burden on networks and disk arrays, create output files that are minimal in size, and run in a highly computationally efficient way, with the single goal of enabling whole-genome sequencing at scale. In addition to improved computational efficiency, we implement a statistical framework that allows for a base by base error model, allowing this package to perform as well or better than the widely used Genome Analysis Toolkit (GATK) in all key measures of performance on human whole-genome sequences.",

keywords = "genome sequencing, GATK, sequence mapping, SNP calling, software, 22Q11.2 DELETION SYNDROME, EXOME VARIANTS, GENERATION, SCHIZOPHRENIA, FRAMEWORK, ALIGNMENT, HUMANS, NUMBER, TOOLS, RISK",

author = "Johnston, {H. Richard} and Pankaj Chopra and Wingo, {Thomas S.} and Viren Patel and Epstein, {Michael P.} and Mulle, {Jennifer G.} and Warren, {Stephen T.} and Zwick, {Michael E.} and {Inter Consortium Brain Behav 22q11} and {van Amelsvoort}, Th{\'e}r{\`e}se and Cutler, {David J.}",

year = "2017",

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doi = "10.1073/pnas.1618065114",

language = "English",

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journal = "Proceedings of the National Academy of Sciences of the United States of America",

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Johnston, HR, Chopra, P, Wingo, TS, Patel, V, Epstein, MP, Mulle, JG, Warren, ST, Zwick, ME, Inter Consortium Brain Behav 22q11, van Amelsvoort, T & Cutler, DJ 2017, 'PEMapper and PECaller provide a simplified approach to whole-genome sequencing', Proceedings of the National Academy of Sciences of the United States of America, vol. 114, no. 10, pp. E1923-E1932. https://doi.org/10.1073/pnas.1618065114

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T1 - PEMapper and PECaller provide a simplified approach to whole-genome sequencing

AU - Johnston, H. Richard

AU - Chopra, Pankaj

AU - Wingo, Thomas S.

AU - Patel, Viren

AU - Epstein, Michael P.

AU - Mulle, Jennifer G.

AU - Warren, Stephen T.

AU - Zwick, Michael E.

AU - Inter Consortium Brain Behav 22q11

AU - van Amelsvoort, Thérèse

AU - Cutler, David J.

PY - 2017/3/7

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AB - The analysis of human whole-genome sequencing data presents significant computational challenges. The sheer size of datasets places an enormous burden on computational, disk array, and network resources. Here, we present an integrated computational package, PEMapper/PECaller, that was designed specifically to minimize the burden on networks and disk arrays, create output files that are minimal in size, and run in a highly computationally efficient way, with the single goal of enabling whole-genome sequencing at scale. In addition to improved computational efficiency, we implement a statistical framework that allows for a base by base error model, allowing this package to perform as well or better than the widely used Genome Analysis Toolkit (GATK) in all key measures of performance on human whole-genome sequences.

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KW - sequence mapping

KW - SNP calling

KW - software

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KW - EXOME VARIANTS

KW - GENERATION

KW - SCHIZOPHRENIA

KW - FRAMEWORK

KW - ALIGNMENT

KW - HUMANS

KW - NUMBER

KW - TOOLS

KW - RISK

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DO - 10.1073/pnas.1618065114

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SN - 0027-8424

VL - 114

SP - E1923-E1932

JO - Proceedings of the National Academy of Sciences of the United States of America

JF - Proceedings of the National Academy of Sciences of the United States of America

IS - 10

ER -

PEMapper and PECaller provide a simplified approach to whole-genome sequencing

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Keywords

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