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ChIP-seq Peak Calling×Analiza ekspresji różnicowej RNA-seq×
DziedzinaBioinformatykaBioinformatyka
RodzinaProcess / pipelineProcess / pipeline
Rok powstania2007–20082008–2010 (RNA-seq DE methodology established)
TwórcaJohnson et al. (ChIP-seq concept, 2007); Zhang et al. (MACS algorithm, 2008)Multiple groups; foundational methods from Anders & Huber (DESeq, 2010), Robinson, McCarthy & Smyth (edgeR, 2010)
TypComputational genomics pipelineQuantitative genomics pipeline
Źródło pierwotneZhang, 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 ↗Love, M. I., Huber, W., & Anders, S. (2014). Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology, 15(12), 550. DOI ↗
Inne nazwyChIP-seq analysis, peak detection, MACS peak calling, ChIP peak identificationRNA-seq DE analysis, transcriptomic differential expression, bulk RNA-seq DE, DEA
Pokrewne66
PodsumowanieChIP-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.RNA-seq differential expression (DE) analysis identifies genes whose transcript abundance differs significantly between two or more biological conditions — for example, treated versus control, or diseased versus healthy tissue. Starting from raw sequencing reads, the pipeline moves through alignment, count-based normalization, statistical modeling of count dispersion, hypothesis testing, and multiple-testing correction to produce a ranked list of differentially expressed genes accompanied by fold-change estimates and adjusted p-values.
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ScholarGatePorównaj metody: ChIP-seq Peak Calling · RNA-seq Differential Expression. Pobrano 2026-06-17 z https://scholargate.app/pl/compare