ONCOCNV

ONCOCNV detects copy-number changes from amplicon sequencing data by correcting PCR amplification bias to identify large-scale amplifications and deletions for oncology research and clinical diagnostics.

Key Features:

• Multifactor normalization and annotation: Employs a multifactor normalization and annotation approach to correct biases introduced by PCR amplification in amplicon sequencing read counts.
• Detection of large copy-number changes: Identifies large-scale copy-number alterations, including gene amplifications and deletions.
• Validation across amplicon densities: Validated on both high and low amplicon density datasets.
• Precision comparable to aCGH: Demonstrates precision comparable to array comparative genomic hybridization (aCGH).

Scientific Applications:

• Oncology research and clinical diagnostics: Enables detection of actionable mutations and associated copy-number changes directly from amplicon sequencing data.
• Reduced need for supplementary arrays: Can obviate the requirement for additional experiments such as SNP arrays or CGH arrays by extracting copy-number information from amplicon sequencing alone.

Methodology:

Multifactor normalization and annotation of amplicon sequencing read counts to correct PCR amplification bias and call large copy-number changes (amplifications and deletions).