TumorCNV

TumorCNV detects germline copy number variations (CNVs) and somatic copy-number alterations (SCNAs) from whole-genome sequencing (WGS) data of matched tumor–normal sample pairs to enable comprehensive characterization of genetic variation in cancer.

Key Features:

• Simultaneous Detection: Performs joint detection of germline CNVs and somatic SCNAs from matched tumor–normal WGS data.
• High Accuracy and Performance: Demonstrated superior performance compared to other methods, achieving higher accuracy in detecting copy number events on simulated data and real datasets, including the COLO-829 melanoma cell line.
• Implementation: Implemented using Java and R.

Scientific Applications:

• Comprehensive Genomic Profiling: Enables comprehensive profiling of germline and somatic copy number alterations from WGS data.
• Biomarker Discovery: Supports the identification of candidate biomarkers for diagnosis, prognosis, and therapeutic targeting.
• Clinical Application: Precise characterization of copy number alterations can inform personalized treatment strategies in clinical contexts.

Methodology:

TumorCNV applies computational algorithms to analyze WGS data from matched tumor–normal pairs, integrating data processing and analysis in a unified framework to jointly detect germline CNVs and somatic SCNAs.