Krahasoni metodat

	Analiza diferenciale e variacionit të numrit të kopjeve	Studimi i Asociacionit të Gjenomit të Gjerë (GWAS)
Fusha	Bioinformatikë	Bioinformatikë
Familja	Process / pipeline	Process / pipeline
Viti i origjinës	2004–2011	2005–2007
Krijuesi	Adam 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)
Lloji	Comparative genomic analysis pipeline	Observational genomic association study
Burimi themelues	Olshen, 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.	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.
Emërtime të tjera	dCNV analysis, comparative CNV analysis, somatic copy number alteration analysis, SCNA analysis	GWAS, genome-wide association analysis, whole-genome association study, WGAS
Të lidhura	1	6
Përmbledhja	Differential 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.