Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Estudo Diferencial de Associação em Escala de Epigenoma× | Estudo de Associação Genômica Ampla (GWAS)× | |
|---|---|---|
| Área | Bioinformática | Bioinformática |
| Família | Process / pipeline | Process / pipeline |
| Ano de origem≠ | 2009–2011 | 2005–2007 |
| Autor original≠ | Rakyan, Down, Balding & Beck (2011); Irizarry group for differential methylation methods (~2009–2014) | Klein et al. (age-related macular degeneration GWAS, 2005); landmark scale: Wellcome Trust Case Control Consortium (2007) |
| Tipo≠ | Comparative epigenome-wide analysis | Observational genomic association study |
| Fonte seminal≠ | 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. 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 ↗ |
| Outros nomes | Differential EWAS, comparative EWAS, epigenome-wide differential methylation analysis, EWAS differential design | GWAS, genome-wide association analysis, whole-genome association study, WGAS |
| Relacionados | 6 | 6 |
| Resumo≠ | A Differential Epigenome-Wide Association Study (Differential EWAS) scans hundreds of thousands of CpG methylation sites across the genome to identify those whose methylation levels differ significantly between two or more comparison groups — such as cases vs. controls, exposed vs. unexposed, or distinct developmental stages. It is the standard epigenomic analogue of a differential expression analysis but operates at the level of DNA methylation marks rather than RNA counts. | 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. |
| ScholarGateConjunto de dados ↗ |
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