ExomeCNV

ExomeCNV detects copy number variations (CNVs) and loss of heterozygosity (LOH) from exome sequencing data to identify genomic alterations for applications such as cancer genomics.

Key Features:

• Statistical Methodology: Leverages depth-of-coverage data and B-allele frequencies derived from mapped short sequence reads to improve detection accuracy of CNVs and LOH.
• Application to Cancer Exomes: Applied to cancer exome resequencing datasets to identify oncogenic CNVs and LOH events.
• Assessment of Power and Confounders: Evaluates method power and examines the impact of confounding variables such as depth-of-coverage and capture probe design on accuracy and resolution.

Scientific Applications:

• Cancer Genomics: Detects CNVs and LOH to uncover genetic alterations that contribute to cancer development and progression.
• Genetic Research: Detects genomic variations in studies of complex diseases where CNVs play a role.

Methodology:

Analyzes depth-of-coverage and B-allele frequencies from mapped short sequence reads to detect CNVs and LOH and assesses method power and the impact of confounding variables such as depth-of-coverage and capture probe design.