MOCSphaser

MOCSphaser infers haplotypes by integrating copy number variation (CNV) and single nucleotide polymorphism (SNP) data to analyze CNV–SNP linkage disequilibrium and estimate population haplotype frequencies.

Key Features:

• Haplotype Inference: Infers haplotypes composed of CNV alleles and SNP alleles from high-throughput experimental genotypic data.
• Population Frequency Estimation: Estimates population frequencies of CNV and SNP haplotypes.
• Expectation-Maximization Algorithm: Employs the expectation-maximization algorithm to iteratively estimate allele frequencies and haplotype structures from observed data.
• Handling Ambiguous Data: Processes ambiguously determined copy numbers (e.g., 2 or 3 copies) to accommodate experimental noise.

Scientific Applications:

• Genetic Association Studies: Identify potential genetic markers associated with diseases by analyzing CNV–SNP haplotypes.
• Population Genetics: Support studies of evolutionary biology and population structure through estimation of CNV and SNP haplotype distributions.
• Precision Medicine: Characterize individual CNV–SNP haplotype profiles to inform genotype-based diagnostic and therapeutic research.

Methodology:

MOCSphaser applies the expectation-maximization algorithm to high-throughput experimental genotypic data to infer CNV alleles and SNP haplotypes, iteratively refining estimates of allele frequencies and haplotype structures while accommodating ambiguous copy-number states.