Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Utafiti wa Chama cha Epigenome-kote (EWAS)× | Genome-wide association study× | |
|---|---|---|
| Nyanja | Bioinformatiki | Bioinformatiki |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 2008–2011 (term and framework established c. 2011) | 2005–2007 |
| Mwanzilishi≠ | Rakyan, Down, Balding & Beck (conceptual framework); Illumina arrays enabled large-scale application | Klein et al. (age-related macular degeneration GWAS, 2005); landmark scale: Wellcome Trust Case Control Consortium (2007) |
| Aina≠ | Population-scale epigenomic association study | Observational genomic association study |
| Chanzo asilia≠ | 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 ↗ | 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 ↗ |
| Majina mbadala | EWAS, methylome-wide association study, epigenetic association study, DNA methylation association study | GWAS, genome-wide association analysis, whole-genome association study, WGAS |
| Zinazohusiana≠ | 5 | 6 |
| Muhtasari≠ | 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. | 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. |
| ScholarGateSeti ya data ↗ |
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