ArticleBioinformatics (Oxford, England)2016
An efficient gene-gene interaction test for genome-wide association studies in trio families.
Article in Bioinformatics (Oxford, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Article
- GADGETS: a genetic algorithm for detecting epistasis using nuclear families.Bioinformatics (Oxford, England) · 2022Article
- SAMA: A Fast Self-Adaptive Memetic Algorithm for Detecting SNP-SNP Interactions Associated with Disease.BioMed research international · 2020Article
- Self-Adjusting Ant Colony Optimization Based on Information Entropy for Detecting Epistatic Interactions.Genes · 2019Article
- Identifying gene-gene interactions using penalized tensor regression.Statistics in medicine · 2018Article
- Article
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4 authors.
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Abstract
motivationSeveral efficient gene-gene interaction tests have been developed for unrelated case-control samples in genome-wide association studies (GWAS), making it possible to test tens of billions of interaction pairs of single-nucleotide polymorphisms (SNPs) in a reasonable timeframe. However, current family-based gene-gene interaction tests are computationally expensive and are not applicable to genome-wide interaction analysis.
resultsWe developed an efficient family-based gene-gene interaction test, GCORE, for trios (i.e. two parents and one affected sib). The GCORE compares interlocus correlations at two SNPs between the transmitted and non-transmitted alleles. We used simulation studies to compare the statistical properties such as type I error rates and power for the GCORE with several other family-based interaction tests under various scenarios. We applied the GCORE to a family-based GWAS for autism consisting of approximately 2000 trios. Testing a total of 22 471 383 013 interaction pairs in the GWAS can be finished in 36 h by the GCORE without large-scale computing resources, demonstrating that the test is practical for genome-wide gene-gene interaction analysis in trios. AVAILABILITY AND IMPLEMENTATION: GCORE is implemented with C ++ and is available at http://gscore.sourceforge.net CONTACT: rchung@nhri.org.tw SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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