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Мрежово епигенетомно-широко асоциативно изследване (Network EWAS)×Геномно-широко асоциативно изследване (GWAS)×
ОбластБиоинформатикаБиоинформатика
СемействоProcess / pipelineProcess / pipeline
Година на възникване2010s, consolidating 2012–20182005–2007
СъздателAdapted from EWAS (Rakyan et al., 2011) and network-based genomic methods (e.g., Ideker & Sharan, 2008)Klein et al. (age-related macular degeneration GWAS, 2005); landmark scale: Wellcome Trust Case Control Consortium (2007)
ТипIntegrative epigenomic analysisObservational genomic association study
Основополагащ източникRakyan, 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 ↗Wellcome Trust Case Control Consortium. (2007). Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature, 447(7145), 661–678. link ↗
Други названияnetwork EWAS, network-integrated EWAS, graph-based EWAS, network-based DNA methylation analysisGWAS, genome-wide association analysis, whole-genome association study, WGAS
Свързани66
РезюмеNetwork-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.A genome-wide association study (GWAS) systematically tests hundreds of thousands to millions of single-nucleotide polymorphisms (SNPs) across the human genome for statistical association with a trait or disease. By comparing allele frequencies between cases and controls — or by regressing SNP genotypes on a quantitative phenotype — GWAS identifies genomic loci that harbor common genetic variants contributing to complex traits. Since its large-scale debut in 2007, GWAS has catalogued thousands of robust disease–variant associations across virtually every common human condition.
ScholarGateНабор от данни
  1. v1
  2. 2 Източници
  3. PUBLISHED
  1. v1
  2. 2 Източници
  3. PUBLISHED

Към търсенето Изтегляне на слайдове

ScholarGateСравнение на методи: Network-based epigenome-wide association study · Genome-wide association study. Извлечено на 2026-06-19 от https://scholargate.app/bg/compare