Differential Copy Number Variation 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.
Rekod sumber
Petikan disalin secara verbatim daripada rekod sumber kaedah. Tiada pengesahan peringkat tuntutan disimpulkan daripadanya.
- 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
- 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
Tuntutan yang dikurasi
Tuntutan disimpan dalam lejar bukti, setiap satu dengan penilaiannya sendiri.
Pandangan ini tidak mencipta penilaian tuntutan apabila lejar tiada.
Kaedah berkaitan
Dijana daripada graf kaedah dan ditunjukkan sebagai perhubungan yang dicadangkan mesin — tiada tuntutan bukti disimpulkan.