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Sieťovo orientovaná epigenómová asociačná štúdia (Network EWAS)×Analýza diferenciálnej expresie RNA-seq×
OdborBioinformatikaBioinformatika
RodinaProcess / pipelineProcess / pipeline
Rok vzniku2010s, consolidating 2012–20182008–2010 (RNA-seq DE methodology established)
TvorcaAdapted from EWAS (Rakyan et al., 2011) and network-based genomic methods (e.g., Ideker & Sharan, 2008)Multiple groups; foundational methods from Anders & Huber (DESeq, 2010), Robinson, McCarthy & Smyth (edgeR, 2010)
TypIntegrative epigenomic analysisQuantitative genomics pipeline
Pôvodný zdrojRakyan, 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. link ↗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 ↗
Ďalšie názvynetwork EWAS, network-integrated EWAS, graph-based EWAS, network-based DNA methylation analysisRNA-seq DE analysis, transcriptomic differential expression, bulk RNA-seq DE, DEA
Príbuzné66
ZhrnutieNetwork-based EWAS extends conventional epigenome-wide association studies by overlaying differentially methylated positions or regions onto biological interaction networks — such as protein-protein interaction, co-expression, or gene regulatory networks — to identify functionally coherent epigenetic modules rather than isolated CpG hits. This integration increases statistical power for detecting weak signals and reveals coordinated epigenetic dysregulation across pathways.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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ScholarGatePorovnať metódy: Network-based epigenome-wide association study · RNA-seq Differential Expression. Získané 2026-06-18 z https://scholargate.app/sk/compare