Process / pipelineBioinformatics / omics

Differential Copy Number Variation Analysis — Comparative CNV / SCNA Analysis

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.

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Sources

  1. 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. DOI: 10.1093/biostatistics/kxh008
  2. Mermel, C. H., Schumacher, S. E., Hill, B., Meyerson, M. L., Beroukhim, R., & Getz, G. (2011). GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers. Genome Biology, 12(4), R41. DOI: 10.1186/gb-2011-12-4-r41

Related methods

ScholarGateDifferential Copy Number Variation Analysis (Differential Copy Number Variation Analysis). Retrieved 2026-06-04 from https://scholargate.app/en/bioinformatics/differential-copy-number-variation-analysis