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| 전장 후성유전체 연관 분석 (EWAS)× | eQTL 분석× | |
|---|---|---|
| 분야 | 생물정보학 | 생물정보학 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 2008–2011 (term and framework established c. 2011) | 2001 (term coined); widely adopted after 2005 |
| 창시자≠ | Rakyan, Down, Balding & Beck (conceptual framework); Illumina arrays enabled large-scale application | Ritsert C. Jansen & Jan-Peter Nap |
| 유형≠ | Population-scale epigenomic association study | Association mapping method |
| 원전≠ | 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 ↗ | Jansen, R. C., & Nap, J.-P. (2001). Genetical genomics: the added value from segregation. Trends in Genetics, 17(7), 388–391. DOI ↗ |
| 별칭 | EWAS, methylome-wide association study, epigenetic association study, DNA methylation association study | eQTL mapping, expression QTL analysis, transcriptomic QTL analysis, eQTL study |
| 관련≠ | 5 | 6 |
| 요약≠ | 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. | eQTL analysis identifies genomic loci (variants, typically SNPs) whose genotype statistically associates with variation in the expression level of one or more genes. By jointly profiling DNA-level variation and RNA-level expression in the same individuals, eQTL studies decode the regulatory grammar of the genome — revealing which variants control how much a gene is transcribed, in which tissues, and under what conditions. |
| ScholarGate데이터셋 ↗ |
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