Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Мультиомиксный анализ eQTL× | Полногеномный поиск ассоциаций (GWAS)× | |
|---|---|---|
| Область | Биоинформатика | Биоинформатика |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 2010s–present (foundational eQTL work: ~2007; multi-omics integration: ~2013–2017) | 2005–2007 |
| Автор метода≠ | GTEx Consortium and multi-omics integration pioneers (Nica & Dermitzakis, 2013; GTEx Consortium, 2015–2020) | Klein et al. (age-related macular degeneration GWAS, 2005); landmark scale: Wellcome Trust Case Control Consortium (2007) |
| Тип≠ | Integrative genomic association analysis | Observational genomic association study |
| Основополагающий источник≠ | GTEx Consortium. (2017). Genetic effects on gene expression across human tissues. Nature, 550(7675), 204–213. 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 ↗ |
| Другие названия | multi-omics molQTL, multi-layer eQTL, integrated eQTL analysis, xQTL multi-omics | GWAS, genome-wide association analysis, whole-genome association study, WGAS |
| Связанные | 6 | 6 |
| Сводка≠ | Multi-omics eQTL analysis maps genetic variants (SNPs or structural variants) to molecular phenotypes simultaneously across multiple omics layers — transcriptome, epigenome, proteome, and metabolome — in the same cohort. By linking genotype to gene expression and then tracing those effects through downstream molecular layers, the approach reveals how genetic variation propagates through the molecular machinery of a cell, yielding mechanistic insight that no single-omics eQTL study can provide. | 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. |
| ScholarGateНабор данных ↗ |
|
|