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Анализ на диференциални вариации в броя на копията×Геномно-широко асоциативно изследване (GWAS)×
ОбластБиоинформатикаБиоинформатика
СемействоProcess / pipelineProcess / pipeline
Година на възникване2004–20112005–2007
СъздателAdam Olshen, E. S. Venkatraman and colleagues (CBS); Rameen Beroukhim, Gad Getz and colleagues (GISTIC)Klein et al. (age-related macular degeneration GWAS, 2005); landmark scale: Wellcome Trust Case Control Consortium (2007)
ТипComparative genomic analysis pipelineObservational genomic association study
Основополагащ източникOlshen, A. B., Venkatraman, E. S., Lucito, R., & Wigler, M. (2004). Circular binary segmentation for the analysis of array-based DNA copy number data. Biostatistics, 5(4), 557–572. DOI ↗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 названияdCNV analysis, comparative CNV analysis, somatic copy number alteration analysis, SCNA analysisGWAS, genome-wide association analysis, whole-genome association study, WGAS
Свързани16
РезюмеDifferential copy number variation (dCNV) analysis identifies genomic regions where DNA copy numbers differ systematically between two conditions — such as tumor versus normal tissue, case versus control cohorts, or treated versus untreated cells. By combining probe-level read-depth or array-intensity data with statistical segmentation and group-level testing, it pinpoints somatic amplifications and deletions that may drive disease, and distinguishes recurrent driver events from passenger noise across a cohort.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

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ScholarGateСравнение на методи: Differential Copy Number Variation Analysis · Genome-wide association study. Извлечено на 2026-06-19 от https://scholargate.app/bg/compare