RT Journal Article
SR Electronic
T1 PEMapper / PECaller: A simplified approach to whole-genome sequencing
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 076968
DO 10.1101/076968
A1 H Richard Johnston
A1 Pankaj Chopra
A1 Thomas S Wingo
A1 Viren Patel
A1 Internation Consortium on Brain and Behavior in 22q11.2 Deletion Syndrome
A1 Michael P Epstein
A1 Jennifer Mulle
A1 Stephen T Warren
A1 Michael E Zwick
A1 David J. Cutler
YR 2016
UL http://biorxiv.org/content/early/2016/09/22/076968.abstract
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 novel 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.