Compara mètodes

	Estudi Diferencial d'Associació a Escala de l'Epigenoma	Anomenament de pics ChIP-seq
Camp	Bioinformàtica	Bioinformàtica
Família	Process / pipeline	Process / pipeline
Any d'origen	2009–2011	2007–2008
Autor original	Rakyan, Down, Balding & Beck (2011); Irizarry group for differential methylation methods (~2009–2014)	Johnson et al. (ChIP-seq concept, 2007); Zhang et al. (MACS algorithm, 2008)
Tipus	Comparative epigenome-wide analysis	Computational genomics pipeline
Font seminal	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.	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.
Àlies	Differential EWAS, comparative EWAS, epigenome-wide differential methylation analysis, EWAS differential design	ChIP-seq analysis, peak detection, MACS peak calling, ChIP peak identification
Relacionats	6	6
Resum	A Differential Epigenome-Wide Association Study (Differential EWAS) scans hundreds of thousands of CpG methylation sites across the genome to identify those whose methylation levels differ significantly between two or more comparison groups — such as cases vs. controls, exposed vs. unexposed, or distinct developmental stages. It is the standard epigenomic analogue of a differential expression analysis but operates at the level of DNA methylation marks rather than RNA counts.	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.