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Ģenoma plaša asociācijas pētījums (GWAS)×eQTL analīze×
NozareBioinformātikaBioinformātika
SaimeProcess / pipelineProcess / pipeline
Izcelsmes gads2005–20072001 (term coined); widely adopted after 2005
AutorsKlein et al. (age-related macular degeneration GWAS, 2005); landmark scale: Wellcome Trust Case Control Consortium (2007)Ritsert C. Jansen & Jan-Peter Nap
TipsObservational genomic association studyAssociation mapping method
PirmavotsWellcome 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. link ↗Jansen, R. C., & Nap, J.-P. (2001). Genetical genomics: the added value from segregation. Trends in Genetics, 17(7), 388–391. DOI ↗
Citi nosaukumiGWAS, genome-wide association analysis, whole-genome association study, WGASeQTL mapping, expression QTL analysis, transcriptomic QTL analysis, eQTL study
Saistītās66
KopsavilkumsA 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.eQTL analysis identifies genomic loci (variants, typically SNPs) whose genotype statistically associates with variation in the expression level of one or more genes. By jointly profiling DNA-level variation and RNA-level expression in the same individuals, eQTL studies decode the regulatory grammar of the genome — revealing which variants control how much a gene is transcribed, in which tissues, and under what conditions.
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ScholarGateSalīdzināt metodes: Genome-wide association study · eQTL Analysis. Izgūts 2026-06-18 no https://scholargate.app/lv/compare