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| Yhden solun epigenomilaajuinen assosiaatiotutkimus (scEWAS)× | Epigenomilaajuinen Assosiaatiotutkimus (EWAS)× | |
|---|---|---|
| Tieteenala | Bioinformatiikka | Bioinformatiikka |
| Menetelmäperhe | Process / pipeline | Process / pipeline |
| Syntyvuosi≠ | 2015–2020 (methodology consolidation period) | 2008–2011 (term and framework established c. 2011) |
| Kehittäjä≠ | Developed through convergence of EWAS methodology (Rakyan et al., 2011) and single-cell epigenomics (Buenrostro et al., 2015) | Rakyan, Down, Balding & Beck (conceptual framework); Illumina arrays enabled large-scale application |
| Tyyppi≠ | Computational genomics pipeline | Population-scale epigenomic association study |
| Alkuperäislähde≠ | Zhang, Y., et al. (2022). Single-cell epigenome analysis reveals age-associated decay of heterochromatin domains in excitatory neurons in the mouse brain. Cell Research, 32(1), 1-18. 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 ↗ |
| Rinnakkaisnimet | scEWAS, single-cell EWAS, sc-epigenome association study, single-cell chromatin accessibility EWAS | EWAS, methylome-wide association study, epigenetic association study, DNA methylation association study |
| Liittyvät≠ | 1 | 5 |
| Tiivistelmä≠ | A single-cell epigenome-wide association study (scEWAS) interrogates epigenetic marks — primarily DNA methylation or chromatin accessibility — across the entire genome at single-cell resolution, then statistically associates variation in those marks with a phenotype, disease, or exposure. By resolving cell-type heterogeneity that bulk EWAS cannot separate, scEWAS identifies epigenetic signals that are specific to rare or intermixed cell populations rather than averaged across tissues. | 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. |
| ScholarGateAineisto ↗ |
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