Svpluscnv

Svpluscnv performs integrative analysis of somatic copy number variations (CNVs) and sequencing-based structural variant (SV) calls to characterize complex genomic rearrangements and chromosomal instability in cancer genomes.

Key Features:

• Integration of Datasets: Integrates orthogonal datasets including copy number variant segmentation profiles and sequencing-based SV calls to consolidate CNV and SV evidence.
• Analysis and Visualization Tools: Provides analytical and visualization methods to quantify chromosomal instability and infer ploidy levels.
• Detection of Complex Rearrangements: Detects genes with recurrent structural variants and identifies complex events such as chromothripsis and chromoplexy.
• Identification of Hot-Spot Regions: Systematically identifies hot-spot shattered genomic regions and reports reproducibility across detection methods and datasets.

Scientific Applications:

• Tumor somatic landscape characterization: Characterizes somatic CNVs and SVs across tumor types to investigate tumor development and progression.
• Large-scale cohort analyses: Applies to large consortia datasets such as The Cancer Genome Atlas (TCGA) and the Pan-Cancer Analysis of Whole Genomes (PCAWG) for cross-cohort comparisons.
• Cancer cell line genomics: Analyzes genomic rearrangements in cancer cell lines, including datasets such as the Cancer Cell Line Encyclopedia (CCLE).

Methodology:

Integrates copy number variant segmentation profiles and sequencing-based structural variant calls from multiple sources, identifies genes with recurrent SVs, detects complex rearrangements (chromothripsis, chromoplexy), locates hot-spot shattered regions, and computes chromosomal instability and ploidy metrics.