CnD

CnD detects copy number variants (CNVs) from short-read sequencing data in homozygous organisms such as inbred mouse strains.

Key Features:

• Algorithmic Approach: CnD employs a hidden Markov model (HMM) that integrates read density and the rate of apparent heterozygous single nucleotide polymorphisms (SNPs) to determine genomic copy number states.
• Input Data: The method processes short-read sequence data (Illumina) to analyze mapped read density and apparent heterozygous SNP rates.
• Optimization for Homozygous Genomes: CnD is optimized for nearly homozygous organisms, such as inbred mouse strains, to enhance CNV detection accuracy.

Scientific Applications:

• Genomic Research in Mice: Applied to re-sequencing data from chromosome 17 of mouse strains A/J and CAST/EiJ using Illumina sequencing to identify CNVs.
• Validation and Performance Assessment: CNV calls were compared to array-comparative genomic hybridization (array CGH) results and a subset of discrepancies were validated by quantitative PCR (qPCR).

Methodology:

Maps short-read sequencing reads across the genome, assesses read density and apparent heterozygous SNP rates, and applies a hidden Markov model (HMM) to interpret patterns for CNV detection.