title: GCORE-sib: An efficient gene-gene interaction tool for genome-wide association studies based on discordant sib pairs.
abstract: BACKGROUND
  A computationally efficient tool is required for a genome-wide gene-gene interaction analysis that tests an extremely large number of single-nucleotide polymorphism (SNP) interaction pairs in genome-wide association studies (GWAS). Current tools for GWAS interaction analysis are mainly developed for unrelated case-control samples. Relatively fewer tools for interaction analysis are available for complex disease studies with family-based design, and these tools tend to be computationally expensive.
  
  
  RESULTS
  We developed a fast gene-gene interaction test, GCORE-sib, for discordant sib pairs and implemented the test into an efficient tool. We used simulations to demonstrate that the GCORE-sib has correct type I error rates and has comparable power to that of the regression-based interaction test. We also showed that the GCORE-sib can run more than 10 times faster than the regression-based test. Finally, the GCORE-sib was applied to a GWAS dataset with approximately 2,000 discordant sib pairs, and the GCORE-sib finished testing 19,368,078,382 pairs of SNPs within 6 days.
  
  
  CONCLUSIONS
  An efficient gene-gene interaction tool for discordant sib pairs was developed. It will be very useful for genome-wide gene-gene interaction analysis in GWAS using discordant sib pairs. The tool can be downloaded for free at http://gcore-sib.sourceforge.net .
authors.affiliation: Institute of Statistics, National Tsing Hua University, Hsin-Chu, Taiwan.
authors.forename: Pei-Yuan
authors.initials: PY
authors.lastname: Sung
authors.affiliation: Institute of Statistics, National Tsing Hua University, Hsin-Chu, Taiwan.
authors.forename: Yi-Ting
authors.initials: YT
authors.lastname: Wang
authors.affiliation: Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan.
authors.forename: Chao A
authors.initials: CA
authors.lastname: Hsiung
authors.affiliation: Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan. rchung@nhri.org.tw.
authors.forename: Ren-Hua
authors.initials: RH
authors.lastname: Chung
mesh_terms: D004843:Epistasis, Genetic; D055106:Genome-Wide Association Study / Q000379:methods*; D023281:Genomics / Q000379:methods; D006801:Humans; D020641:Polymorphism, Single Nucleotide; D035781:Siblings; D012984:Software; D013223:Statistics as Topic
keywords: Discordant sib pair; Gene-gene interaction; Genome-wide association study