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Análisis de Variación del Número de Copias×Estudio de Asociación a Nivel de Epigenoma (EWAS)×
CampoBioinformáticaBioinformática
FamiliaProcess / pipelineProcess / pipeline
Año de origen1998–20062008–2011 (term and framework established c. 2011)
Autor originalPinkel et al. (array CGH); Redon et al. (genome-wide CNV map)Rakyan, Down, Balding & Beck (conceptual framework); Illumina arrays enabled large-scale application
TipoGenomic structural variant detection pipelinePopulation-scale epigenomic association study
Fuente seminalRedon, R., Ishikawa, S., Fitch, K. R., et al. (2006). Global variation in copy number in the human genome. Nature, 444(7118), 444–454. 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 ↗
AliasCNV analysis, copy number variant detection, CNV calling, somatic copy number alteration analysisEWAS, methylome-wide association study, epigenetic association study, DNA methylation association study
Relacionados65
ResumenCopy number variation (CNV) analysis is a genomic pipeline for detecting regions where individuals carry fewer or more copies of a DNA segment than the reference genome. CNVs span kilobases to megabases and are a major class of structural variation implicated in cancer, neurodevelopmental disorders, and population diversity. The pipeline typically processes SNP array intensities or read-depth signals from whole-genome sequencing, applies segmentation algorithms, calls gain and loss events, and annotates them against gene and clinical databases.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.
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ScholarGateComparar métodos: Copy Number Variation Analysis · Epigenome-wide association study. Recuperado el 2026-06-19 de https://scholargate.app/es/compare