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| Pemanggilan Puncak ChIP-seq Sel Tunggal× | Studi Asosiasi Seluruh Epigenom (EWAS)× | |
|---|---|---|
| Bidang | Bioinformatika | Bioinformatika |
| Keluarga | Process / pipeline | Process / pipeline |
| Tahun asal≠ | 2019 | 2008–2011 (term and framework established c. 2011) |
| Pencetus≠ | Grosselin et al.; Ku et al. (parallel independent development) | Rakyan, Down, Balding & Beck (conceptual framework); Illumina arrays enabled large-scale application |
| Tipe≠ | Epigenomic profiling pipeline | Population-scale epigenomic association study |
| Sumber perintis≠ | Grosselin, 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 ↗ |
| Alias | scChIP-seq peak calling, single-cell chromatin profiling, scChIC-seq analysis, single-cell epigenomic peak detection | EWAS, methylome-wide association study, epigenetic association study, DNA methylation association study |
| Terkait | 5 | 5 |
| Ringkasan≠ | Single-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. |
| ScholarGateSet data ↗ |
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