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Jednotlivá-buněčná GWAS×Genomová asociační studie (GWAS)×
OborBioinformatikaBioinformatika
RodinaProcess / pipelineProcess / pipeline
Rok vzniku2019–2022 (rapid emergence with large-scale scRNA-seq atlases)2005–2007
TvůrceMultiple groups (Price lab, De Jager lab, others); scDRS framework by Zhang et al. 2022Klein et al. (age-related macular degeneration GWAS, 2005); landmark scale: Wellcome Trust Case Control Consortium (2007)
TypIntegrative genomic analysis pipelineObservational genomic association study
Původní zdrojZhang, M. J., Hou, K., Dey, K. K., Sakaue, S., Jagadeesh, K. A., Weinand, K., ... & Price, A. L. (2022). Polygenic enrichment distinguishes disease associations of individual cells in single-cell RNA-seq data. Nature Genetics, 54(8), 1224-1234. link ↗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. link ↗
Další názvysc-GWAS, single-cell GWAS integration, cell-type-specific GWAS, single-cell genetic association analysisGWAS, genome-wide association analysis, whole-genome association study, WGAS
Příbuzné66
ShrnutíSingle-cell GWAS is an integrative bioinformatics pipeline that maps genome-wide association study (GWAS) signals onto single-cell transcriptomic landscapes to identify which cell types and individual cells carry disproportionate genetic risk for a disease or trait. By leveraging single-cell RNA-seq atlases alongside GWAS summary statistics, it moves beyond tissue-level associations to reveal the precise cellular contexts in which disease-associated genetic variants exert their effects.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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ScholarGatePorovnat metody: Single-cell GWAS · Genome-wide association study. Získáno 2026-06-18 z https://scholargate.app/cs/compare