Process / pipelineBioinformatics / omics
Genome-Wide Association Study (GWAS)
A genome-wide association study (GWAS) systematically tests hundreds of thousands to millions of single-nucleotide polymorphisms (SNPs) across the human genome for statistical association with a trait or disease. By comparing allele frequencies between cases and controls — or by regressing SNP genotypes on a quantitative phenotype — GWAS identifies genomic loci that harbor common genetic variants contributing to complex traits. Since its large-scale debut in 2007, GWAS has catalogued thousands of robust disease–variant associations across virtually every common human condition.
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Sources
- Wellcome Trust Case Control Consortium. (2007). Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature, 447(7145), 661–678. DOI: 10.1038/nature05911 ↗
- Visscher, P. M., Wray, N. R., Zhang, Q., Sklar, P., McCarthy, M. I., Brown, M. A., & Yang, J. (2017). 10 years of GWAS discovery: Biology, function, and translation. American Journal of Human Genetics, 101(1), 5–22. DOI: 10.1016/j.ajhg.2017.06.005 ↗
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Bayesian Copy Number Variation AnalysisBayesian epigenome-wide association studyBayesian epigenome-wide association study in educational researchBayesian eQTL analysisBayesian GWASCopy Number Variation AnalysisDifferential Copy Number Variation AnalysisDifferential Epigenome-Wide Association StudyDifferential eQTL AnalysisEpigenome-wide association studyEpigenome-wide association study in educational researcheQTL AnalysisMachine learning-assisted copy number variation analysisMachine learning-assisted epigenome-wide association studyMachine learning-assisted expression quantitative trait loci analysisMachine learning-assisted genome-wide association studyMachine learning-assisted phylogenetic analysisMulti-omics epigenome-wide association studyMulti-omics eQTL analysisNetwork-based epigenome-wide association studyNetwork-based eQTL analysisNetwork-based GWASNetwork-based Phylogenetic AnalysisNetwork-based variant callingPhylogenetic AnalysisSequence AlignmentSingle-cell eQTL analysisSingle-cell GWASTime-series copy number variation analysisTime-series eQTL analysisTime-series phylogenetic analysisVariant Calling