Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Studiu de asociere la nivel de genom (GWAS)× | Studiu de asociere la nivel de epigenom (EWAS)× | |
|---|---|---|
| Domeniu | Bioinformatică | Bioinformatică |
| Familie | Process / pipeline | Process / pipeline |
| Anul apariției≠ | 2005–2007 | 2008–2011 (term and framework established c. 2011) |
| Autorul original≠ | Klein et al. (age-related macular degeneration GWAS, 2005); landmark scale: Wellcome Trust Case Control Consortium (2007) | Rakyan, Down, Balding & Beck (conceptual framework); Illumina arrays enabled large-scale application |
| Tip≠ | Observational genomic association study | Population-scale epigenomic association study |
| Sursa seminală≠ | 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 ↗ | Rakyan, V. K., Down, T. A., Balding, D. J., & Beck, S. (2011). Epigenome-wide association studies for common human diseases. Nature Reviews Genetics, 12(8), 529–541. DOI ↗ |
| Denumiri alternative | GWAS, genome-wide association analysis, whole-genome association study, WGAS | EWAS, methylome-wide association study, epigenetic association study, DNA methylation association study |
| Înrudite≠ | 6 | 5 |
| Rezumat≠ | 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. | An epigenome-wide association study (EWAS) is a hypothesis-free, genome-scale method that systematically tests whether epigenetic marks — predominantly CpG-site DNA methylation — differ between individuals with and without a trait, disease, or exposure. By scanning hundreds of thousands of genomic positions simultaneously, EWAS identifies loci where the epigenome is reproducibly associated with a phenotype, offering a layer of biological regulation that classical GWAS does not capture. |
| ScholarGateSet de date ↗ |
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