CNVtools

CNVtools performs likelihood-ratio-based association testing of copy number variants (CNVs) using quantitative CNV measurements to detect associations with binary and quantitative traits in genetic case-control studies.

Key Features:

• Likelihood ratio testing: Applies likelihood ratio tests to quantitative CNV measurements derived from cases and controls.
• Robustness to differential error rates: Maintains resilience against differential measurement errors and noise between case and control groups.
• Maximized theoretical power: Implements methods designed to achieve maximal theoretical power for detecting true CNV–trait associations.
• Support for trait types: Supports association testing for both binary (case-control) and quantitative phenotypes.
• Quantitative CNV analysis: Operates directly on quantitative CNV data rather than relying solely on discrete copy-number calls.
• Accounts for SNP linkage limitations: Addresses CNV effects that may not be captured by linkage disequilibrium with SNPs.

Scientific Applications:

• Case-control CNV association studies: Detects associations between CNVs and disease status in case-control study designs.
• Quantitative trait association: Tests relationships between CNVs and quantitative phenotypes such as biomarker levels.
• False-positive mitigation: Reduces false-positive results caused by differential errors between cases and controls.
• Functional CNV investigation: Investigates functional impacts of CNVs that are poorly captured by SNP-based analyses.

Methodology:

Uses a robust statistical framework employing likelihood ratio testing on quantitative CNV measurements from cases and controls to mitigate differential errors and noisy measurements and to maximize theoretical detection power.