AluScanCNV2

AluScanCNV2 performs detection and analysis of somatic and germline copy number variations (CNVs) from next-generation sequencing (NGS) data, including AluScan, whole-genome sequencing and targeted sequencing, to support cancer subtyping and germline cancer risk prediction.

Key Features:

• Comprehensive CNV detection: Identifies both somatic and germline CNVs from diverse NGS datasets.
• Cancer subtyping and risk prediction: Uses detected somatic CNVs for cancer subtyping and analyzes recurrent germline CNVs with machine learning to predict individual cancer susceptibility.
• Multi-platform compatibility: Operates on AluScan, whole-genome sequencing, and targeted sequencing data.
• High-throughput analysis: Processes large-scale NGS datasets suitable for high-throughput studies.

Scientific Applications:

• Cancer research: Classification of tumor types and development of prognostic models using somatic CNV profiles.
• Hereditary cancer risk assessment: Germline CNV analysis and machine learning-assisted prediction of individual cancer susceptibility.
• Large-scale genomic studies: Application to high-throughput NGS studies to uncover genetic contributors to cancer.

Methodology:

Analyzes sequencing reads to detect copy number variation across the genome, distinguishes somatic and germline CNVs, uses recurrent germline CNVs with machine learning for risk prediction, and leverages detected somatic CNVs for cancer subtyping.