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.

authors

Johnston HR,Chopra P,Wingo TS,Patel V,International Consortium on Brain and Behavior in 22q11.2 Deletion Syndrome.,Epstein MP,Mulle JG,Warren ST,Zwick ME,Cutler DJ

doi

10.1073/pnas.1618065114

subject

Has Abstract

pub_date

2017-03-07 00:00:00

pages

E1923-E1932

issue

10

eissn

0027-8424

issn

1091-6490

pii

1618065114

journal_volume

114

pub_type

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