Home News About Us Contact Contributors Disclaimer Privacy Policy Help FAQ

Home
Search
Quick Search
Advanced
Fulltext
Browse
Collections
Persons
My eDoc
Session History
Login
Name:
Password:
Documentation
Help
Support Wiki
Direct access to
document ID:


          Institute: MPI für Intelligente Systeme (ehemals Max-Planck-Institut für Metallforschung)     Collection: Abt. Schölkopf (Empirical Inference)     Display Documents



  history
ID: 596807.0, MPI für Intelligente Systeme (ehemals Max-Planck-Institut für Metallforschung) / Abt. Schölkopf (Empirical Inference)
Epistasis detection on quantitative phenotypes by exhaustive enumeration using GPUs
Authors:Kam-Thong, T.; Pütz, B.; Karbalai, N.; Müller−Myhsok, B.; Borgwardt, K.
Date of Publication (YYYY-MM-DD):2011-07-01
Title of Journal:Bioinformatics
Volume:27
Issue / Number:13: ISMB/ECCB 2011
Start Page:i214
End Page:i221
Review Status:not specified
Audience:Not Specified
Intended Educational Use:No
Abstract / Description: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.
External Publication Status:published
Document Type:Article
Communicated by:Heide Klooz
Affiliations:MPI für Intelligente Systeme/Abt. Schölkopf
Identifiers:URL:http://www.kyb.tuebingen.mpg.de/
LOCALID:KamThongPKMB2011
DOI:10.1093/bioinformatics/btr218
The scope and number of records on eDoc is subject to the collection policies defined by each institute - see "info" button in the collection browse view.