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Anàlisi de pics de ChIP-seq de cèl·lula única×Estudi d'Associació a Escala d'Epigenoma (EWAS)×
CampBioinformàticaBioinformàtica
FamíliaProcess / pipelineProcess / pipeline
Any d'origen20192008–2011 (term and framework established c. 2011)
Autor originalGrosselin et al.; Ku et al. (parallel independent development)Rakyan, Down, Balding & Beck (conceptual framework); Illumina arrays enabled large-scale application
TipusEpigenomic profiling pipelinePopulation-scale epigenomic association study
Font seminalGrosselin, K., Durand, A., Marsolier, J., Poitou, A., Marangoni, E., Nemati, F., ... & Vallot, C. (2019). High-throughput single-cell ChIP-seq identifies heterogeneity of chromatin states in breast cancer. Nature Genetics, 51(6), 1060-1066. 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 ↗
ÀliesscChIP-seq peak calling, single-cell chromatin profiling, scChIC-seq analysis, single-cell epigenomic peak detectionEWAS, methylome-wide association study, epigenetic association study, DNA methylation association study
Relacionats55
ResumSingle-cell ChIP-seq peak calling is a bioinformatics pipeline that identifies genomic regions enriched for histone modifications or transcription factor binding in individual cells. By profiling chromatin states at single-cell resolution, it reveals epigenomic heterogeneity hidden in bulk ChIP-seq experiments, enabling researchers to map regulatory landscapes across distinct cell populations within a complex tissue sample.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.
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ScholarGateCompara mètodes: Single-cell ChIP-seq peak calling · Epigenome-wide association study. Recuperat el 2026-06-18 de https://scholargate.app/ca/compare