title: High-throughput analysis of epistasis in genome-wide association studies with BiForce.
abstract: BACKGROUND
  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.
  
  
  METHODS
  The software is free and can be downloaded from http://bioinfo.utu.fi/BiForce/.
  
  
  BACKGROUND
  wenhua.wei@igmm.ed.ac.uk
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Finnish Microarray and Sequencing Centre, Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, 20520, Turku, Finland.
authors.forename: Attila
authors.initials: A
authors.lastname: Gyenesei
authors.forename: Jonathan
authors.initials: J
authors.lastname: Moody
authors.forename: Colin A M
authors.initials: CA
authors.lastname: Semple
authors.forename: Chris S
authors.initials: CS
authors.lastname: Haley
authors.forename: Wen-Hua
authors.initials: WH
authors.lastname: Wei
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D004843:Epistasis, Genetic; D055106:Genome-Wide Association Study; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D008957:Models, Genetic; D020641:Polymorphism, Single Nucleotide; D012984:Software