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Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Appel de pics ChIP-seq en séries temporelles× | Étude d'association pangénomique épigénétique (EWAS)× | |
|---|---|---|
| Domaine | Bio-informatique | Bio-informatique |
| Famille | Process / pipeline | Process / pipeline |
| Année d'origine≠ | 2008–2012 (ChIP-seq); time-series extensions ~2015–2020 | 2008–2011 (term and framework established c. 2011) |
| Auteur d'origine≠ | ENCODE Consortium; extended by Haiminen et al. and broader epigenomics community | Rakyan, Down, Balding & Beck (conceptual framework); Illumina arrays enabled large-scale application |
| Type≠ | Computational epigenomics pipeline | Population-scale epigenomic association study |
| Source fondatrice≠ | Landt, S. G., Marinov, G. K., Kundaje, A., Kheradpour, P., Pauli, F., Batzoglou, S., ... & Snyder, M. (2012). ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia. Genome Research, 22(9), 1813–1831. DOI ↗ | 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 ↗ |
| Alias | longitudinal ChIP-seq analysis, dynamic ChIP-seq peak calling, time-course ChIP-seq, temporal chromatin profiling | EWAS, methylome-wide association study, epigenetic association study, DNA methylation association study |
| Apparentées | 5 | 5 |
| Résumé≠ | Time-series ChIP-seq peak calling extends standard chromatin immunoprecipitation sequencing analysis to samples collected at multiple time points. By identifying and comparing protein-DNA binding peaks across a temporal dimension, the method reveals how transcription factor occupancy, histone modifications, or chromatin remodeler binding evolve during biological processes such as differentiation, circadian cycles, or stimulus response. | 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. |
| ScholarGateJeu de données ↗ |
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