ArticleBMC systems biology2018
GxGrare: gene-gene interaction analysis method for rare variants from high-throughput sequencing data.
Article in BMC systems biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- iRUNNER: A Baseline Mutation Burden Regression for Identifying Gene Interaction Between Rare Variants for Diseases.Genomics, proteomics & bioinformatics · 2025Article
- Deciphering the digenic architecture of congenital heart disease using trio exome sequencing data.American journal of human genetics · 2025Article
- The Impact of Cardiovascular Disease Gene Polymorphism and Interaction with Homocysteine on Deep Vein Thrombosis.ACS omega · 2024Article
- Excalibur: A new ensemble method based on an optimal combination of aggregation tests for rare-variant association testing for sequencing data.PLoS computational biology · 2023Article
- Network-guided search for genetic heterogeneity between gene pairs.Bioinformatics (Oxford, England) · 2021Article
- Roles of interacting stress-related genes in lifespan regulation: insights for translating experimental findings to humans.Journal of translational genetics and genomics · 2021Article
- A genome-wide case-only test for the detection of digenic inheritance in human exomes.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Investigation of gene-gene interactions in cardiac traits and serum fatty acid levels in the LURIC Health Study.PloS one · 2020Article
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Authors and funding
4 authors.
Funding
Abstract
backgroundWith 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.
resultsHere, 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.
conclusionThe 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.
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