Anaconda

Anaconda detects and annotates somatic copy number variations (CNVs) from tumor whole-exome sequencing (WES) data to identify genes affected by CNVs in cancer.

Key Features:

• Integration of Multiple CNV-Calling Methods: Integrates up to four CNV detection algorithms within a single run to combine calls and reduce false negatives associated with exonic bias.
• Comprehensive Annotation of Shared CNV Regions: Systematically annotates genes within shared CNV regions to provide functional context for detected CNVs.
• Input Data Modality: Operates on tumor whole-exome sequencing (WES) data to analyze exonic copy number alterations.

Scientific Applications:

• Cancer Genomics: Detection and annotation of somatic CNVs in tumor genomes to study genetic contributors to oncogenesis.
• Candidate Gene and Target Identification: Identification of genes affected by CNVs that may contribute to tumor development or serve as potential therapeutic targets.

Methodology:

Processes whole-exome sequencing (WES) data by integrating multiple CNV detection algorithms (up to four) and systematically annotating the resulting CNV regions.