PT  - JOURNAL ARTICLE
AU  - H Richard Johnston
AU  - Pankaj Chopra
AU  - Thomas S Wingo
AU  - Viren Patel
AU  - Internation Consortium on Brain and Behavior in 22q11.2 Deletion Syndrome
AU  - Michael P Epstein
AU  - Jennifer Mulle
AU  - Stephen T Warren
AU  - Michael E Zwick
AU  - David J. Cutler
TI  - PEMapper / PECaller: A simplified approach to whole-genome sequencing
AID  - 10.1101/076968
DP  - 2016 Jan 01
TA  - bioRxiv
PG  - 076968
4099  - http://biorxiv.org/content/early/2016/09/22/076968.short
4100  - http://biorxiv.org/content/early/2016/09/22/076968.full
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.