The complete compositional epistasis detection in genome-wide association studies

Xiang WAN*, Can YANG, Qiang Yang, Hongyu Zhao, Weichuan Yu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)

Abstract

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.htmlâ̂ -#GBOOST.Conclusions: This work demonstrates that the complete compositional epistasis detection is computationally feasible in GWAS.

Original languageEnglish
Article number7
JournalBMC Genetics
Volume14
DOIs
Publication statusPublished - 19 Feb 2013

Scopus Subject Areas

  • Genetics
  • Genetics(clinical)

User-Defined Keywords

  • Compositional epistasis
  • Genome-wide association study
  • GPU
  • SNP

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