XCAVATOR

XCAVATOR identifies genomic copy-number variants (CNVs) and copy-number alterations (CNAs) from short and long whole-genome sequencing reads to predict their boundaries and estimate absolute DNA copy numbers.

Key Features:

• Read Count Approach: Uses a read-count approach analyzing sequencing read depth to predict CNV/CNA boundaries and absolute copy numbers.
• High-Resolution Detection: Detects CNVs/CNAs at high resolution as demonstrated on simulated and real datasets.
• Versatility Across Sequencing Technologies: Processes short and long reads from whole-genome sequencing across second- and third-generation platforms, including Illumina and Pacific Biosciences.
• Performance Superiority: Outperformed ten state-of-the-art tools in comparative analyses for detection of both germline and somatic CNVs/CNAs.
• Publication: Described in the publication PMID: 28934930.

Scientific Applications:

• Cancer Genomics: Detection and genotyping of somatic CNAs for cancer genomic studies.
• Germline Variation and Genetic Disorders: Genotyping of germline CNVs relevant to genetic disorder research.
• Evolutionary Biology: Analysis of CNV variation for evolutionary and population genomics studies.
• Personalized Medicine: Identification of copy-number changes relevant to patient-specific genomic interpretation.

Methodology:

Analyzes read counts from whole-genome short and long sequencing reads (read-count approach) to predict CNV/CNA boundaries and estimate absolute DNA copy numbers.