Please use this identifier to cite or link to this item: http://hdl.handle.net/1783.1/55525

The complete compositional epistasis detection in genome-wide association studies

Authors Wan, Xiang HKUST affiliated (currently or previously)
Yang, Can HKUST affiliated (currently or previously)
Yang, Qiang View this author's profile
Zhao, Hongyu
Yu, Weichuan View this author's profile
Issue Date 2013
Source BMC Genetics , v. 14, February 2013, article number 7
Summary Background: The detection of epistasis among genetic markers is of great interest in genome-wide association studies (GWAS). In recent years, much research has been devoted to find disease-associated epistasis in GWAS. However, due to the high computational cost involved, most methods focus on specific epistasis models, making the potential loss of power when the underlying epistasis models are not examined in these analyses. Results: In this work, we propose a computational efficient approach based on complete enumeration of two-locus epistasis models. This approach uses a two-stage (screening and testing) search strategy and guarantees the enumeration of all epistasis patterns. The implementation is done on graphic processing units (GPU), which can finish the analysis on a GWAS data (with around 5, 000 subjects and around 350, 000 markers) within two hours. Source code is available at http://bioinformatics.ust.hk/BOOST.html\#GBOOST. Conclusions: This work demonstrates that the complete compositional epistasis detection is computationally feasible in GWAS.
Subjects
SNP
GPU
ISSN 1471-2156
Language English
Format Article
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