Kwon, MinseokLeem, SangseobYoon, JoonPark, Taesung2018-04-192018Kwon, Minseok, Sangseob Leem, Joon Yoon, and Taesung Park. 2018. “GxGrare: gene-gene interaction analysis method for rare variants from high-throughput sequencing data.” BMC Systems Biology 12 (Suppl 2): 19. doi:10.1186/s12918-018-0543-4. http://dx.doi.org/10.1186/s12918-018-0543-4.http://nrs.harvard.edu/urn-3:HUL.InstRepos:35982056Background: With the rapid advancement of array-based genotyping techniques, genome-wide association studies (GWAS) have successfully identified common genetic variants associated with common complex diseases. However, it has been shown that only a small proportion of the genetic etiology of complex diseases could be explained by the genetic factors identified from GWAS. This missing heritability could possibly be explained by gene-gene interaction (epistasis) and rare variants. There has been an exponential growth of gene-gene interaction analysis for common variants in terms of methodological developments and practical applications. Also, the recent advancement of high-throughput sequencing technologies makes it possible to conduct rare variant analysis. However, little progress has been made in gene-gene interaction analysis for rare variants. Results: Here, we propose GxGrare which is a new gene-gene interaction method for the rare variants in the framework of the multifactor dimensionality reduction (MDR) analysis. The proposed method consists of three steps; 1) collapsing the rare variants, 2) MDR analysis for the collapsed rare variants, and 3) detect top candidate interaction pairs. GxGrare can be used for the detection of not only gene-gene interactions, but also interactions within a single gene. The proposed method is illustrated with 1080 whole exome sequencing data of the Korean population in order to identify causal gene-gene interaction for rare variants for type 2 diabetes. Conclusion: The proposed GxGrare performs well for gene-gene interaction detection with collapsing of rare variants. GxGrare is available at http://bibs.snu.ac.kr/software/gxgrare which contains simulation data and documentation. Supported operating systems include Linux and OS X. Electronic supplementary material The online version of this article (10.1186/s12918-018-0543-4) contains supplementary material, which is available to authorized users.en-USGene-gene interactionRare variantMultifactor dimensionality reductionJournal Article2018-04-1910.1186/s12918-018-0543-4