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. 2012 Aug 1;28(15):1957-64.
doi: 10.1093/bioinformatics/bts304. Epub 2012 May 21.

High-throughput analysis of epistasis in genome-wide association studies with BiForce

Attila Gyenesei  1 , Jonathan Moody, Colin A M Semple, Chris S Haley, Wen-Hua Wei
Affiliations

High-throughput analysis of epistasis in genome-wide association studies with BiForce

Attila Gyenesei et al. Bioinformatics. .

Erratum in

  • Bioinformatics. 2013 Oct 15;29(20):2667-8

Abstract

Motivation: Gene-gene interactions (epistasis) are thought to be important in shaping complex traits, but they have been under-explored in genome-wide association studies (GWAS) due to the computational challenge of enumerating billions of single nucleotide polymorphism (SNP) combinations. Fast screening tools are needed to make epistasis analysis routinely available in GWAS.

Results: We present BiForce to support high-throughput analysis of epistasis in GWAS for either quantitative or binary disease (case-control) traits. BiForce achieves great computational efficiency by using memory efficient data structures, Boolean bitwise operations and multithreaded parallelization. It performs a full pair-wise genome scan to detect interactions involving SNPs with or without significant marginal effects using appropriate Bonferroni-corrected significance thresholds. We show that BiForce is more powerful and significantly faster than published tools for both binary and quantitative traits in a series of performance tests on simulated and real datasets. We demonstrate BiForce in analysing eight metabolic traits in a GWAS cohort (323 697 SNPs, >4500 individuals) and two disease traits in another (>340 000 SNPs, >1750 cases and 1500 controls) on a 32-node computing cluster. BiForce completed analyses of the eight metabolic traits within 1 day, identified nine epistatic pairs of SNPs in five metabolic traits and 18 SNP pairs in two disease traits. BiForce can make the analysis of epistasis a routine exercise in GWAS and thus improve our understanding of the role of epistasis in the genetic regulation of complex traits.

Availability and implementation: The software is free and can be downloaded from http://bioinfo.utu.fi/BiForce/.

Contact: wenhua.wei@igmm.ed.ac.uk

Supplementary information: Supplementary data are available at Bioinformatics online.

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Figures

Fig. 1.
Fig. 1.
Comparison of power of detection of epistasis in binary traits between BiForce and BOOST. Model 1: multiplicative model, Models 2 and 3: missing lethal genotype model (aabb does not lead to disease, AaBb does in Model 3 but not in Model 2), Model 4: exclusive OR model
Fig. 2.
Fig. 2.
Comparison of power of detection of epistasis in quantitative traits between BiForce and PLINK. Model 1: multiplicative model, Models 2 and 3: missing lethal genotype model (aabb does not lead to disease, AaBb does in Model 3 but not Model 2), Model 4: exclusive OR model
Fig. 3.
Fig. 3.
FPR profiles of BiForce in detection of epistasis in binary and quantitative traits
See this image and copyright information in PMC

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