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. 2012 Mar 1;28(5):719-20.
doi: 10.1093/bioinformatics/bts015. Epub 2012 Jan 11.

A scalable and portable framework for massively parallel variable selection in genetic association studies

Gary K Chen  1
Affiliations

A scalable and portable framework for massively parallel variable selection in genetic association studies

Gary K Chen. Bioinformatics. .

Abstract

The deluge of data emerging from high-throughput sequencing technologies poses large analytical challenges when testing for association to disease. We introduce a scalable framework for variable selection, implemented in C++ and OpenCL, that fits regularized regression across multiple Graphics Processing Units. Open source code and documentation can be found at a Google Code repository under the URL http://bioinformatics.oxfordjournals.org/content/early/2012/01/10/bioinformatics.bts015.abstract.

Supplementary information: Supplementary data are available at Bioinformatics online.

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Figures

Fig. 1.
Fig. 1.
ROC for simulations based on 1KGP exome data.
See this image and copyright information in PMC

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