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  Epistasis detection on quantitative phenotypes by exhaustive enumeration using GPUs

Kam-Thong, T., Pütz, B., Karbalai, N., Müller−Myhsok, B., & Borgwardt, K. (2011). Epistasis detection on quantitative phenotypes by exhaustive enumeration using GPUs. Bioinformatics, 27(13), i214-i221.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-BB00-A Version Permalink: https://hdl.handle.net/21.11116/0000-0006-C595-3
Genre: Conference Paper

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https://academic.oup.com/bioinformatics/article-pdf/27/13/i214/430237/btr218.pdf (Publisher version)
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 Creators:
Kam-Thong, T, Author
Pütz, B, Author
Karbalai, N, Author
Müller−Myhsok, B, Author
Borgwardt, K1, Author           
Affiliations:
1Former Research Group Machine Learning and Computational Biology, Max Planck Institute for Intelligent Systems, Max Planck Society, DE, ou_1497664              

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 Abstract: Motivation: In recent years, numerous genome-wide association studies have been conducted to identify genetic makeup that explains phenotypic differences observed in human population. Analytical tests on single loci are readily available and embedded in common genome analysis software toolset. The search for significant epistasis (gene–gene interactions) still poses as a computational challenge for modern day computing systems, due to the large number of hypotheses that have to be tested.
Results: In this article, we present an approach to epistasis detection by exhaustive testing of all possible SNP pairs. The search strategy based on the Hilbert–Schmidt Independence Criterion can help delineate various forms of statistical dependence between the genetic markers and the phenotype. The actual implementation of this search is done on the highly parallelized architecture available on graphics processing units rendering the completion of the full search feasible within a day.

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 Dates: 2011-07
 Publication Status: Issued
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1093/bioinformatics/btr218
BibTex Citekey: KamThongPKMB2011
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Title: 19th Annual International Conference on Intelligent Systems for Molecular Biology and 10th European Conference on Computational Biology (ISMB/ECCB 2011)
Place of Event: Wien, Austria
Start-/End Date: 2011-07-17 - 2011-07-19

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Title: Bioinformatics
Source Genre: Journal
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Publ. Info: Oxford : Oxford University Press
Pages: - Volume / Issue: 27 (13) Sequence Number: - Start / End Page: i214 - i221 Identifier: ISSN: 1367-4803
CoNE: https://pure.mpg.de/cone/journals/resource/954926969991