Sammenlign metoder
Gjennomgå de valgte metodene side om side; rader som avviker, er uthevet.
| ChIP-seq Peak Calling× | Epigenom-vid assosiasjonsstudie (EWAS)× | |
|---|---|---|
| Fagfelt | Bioinformatikk | Bioinformatikk |
| Familie | Process / pipeline | Process / pipeline |
| Opprinnelsesår≠ | 2007–2008 | 2008–2011 (term and framework established c. 2011) |
| Opphavsperson≠ | Johnson et al. (ChIP-seq concept, 2007); Zhang et al. (MACS algorithm, 2008) | Rakyan, Down, Balding & Beck (conceptual framework); Illumina arrays enabled large-scale application |
| Type≠ | Computational genomics pipeline | Population-scale epigenomic association study |
| Opprinnelig kilde≠ | Zhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., Nusbaum, C., Myers, R. M., Brown, M., Li, W., & Liu, X. S. (2008). Model-based analysis of ChIP-seq (MACS). Genome Biology, 9(9), R137. 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 | ChIP-seq analysis, peak detection, MACS peak calling, ChIP peak identification | EWAS, methylome-wide association study, epigenetic association study, DNA methylation association study |
| Relaterte≠ | 6 | 5 |
| Sammendrag≠ | ChIP-seq peak calling is a computational pipeline that identifies genomic regions where a protein of interest — a transcription factor or histone modification — is enriched, based on sequencing reads from chromatin immunoprecipitation experiments. It converts raw sequencing data into a set of high-confidence binding or modification sites across the genome, enabling downstream analysis of gene regulation, chromatin state, and epigenetic mechanisms. | 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. |
| ScholarGateDatasett ↗ |
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