Comparer des méthodes

	Étude d'association pangénomique épigénétique unicellulaire (scEWAS)	Étude d'association pangénomique épigénétique (EWAS)
Domaine	Bio-informatique	Bio-informatique
Famille	Process / pipeline	Process / pipeline
Année d'origine	2015–2020 (methodology consolidation period)	2008–2011 (term and framework established c. 2011)
Auteur d'origine	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
Type	Computational genomics pipeline	Population-scale epigenomic association study
Source fondatrice	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.	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.
Alias	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
Apparentées	1	5
Résumé	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.