CopySeq

CopySeq infers copy-number genotypes from personal genome sequencing data by analyzing depth-of-coverage of high-throughput DNA sequencing reads and integrating paired-end and breakpoint junction analyses.

Key Features:

• Statistical Framework: CopySeq employs a statistical framework that analyzes sequencing read coverage to infer locus-specific copy-number genotypes.
• Integration with CNV Analysis Approaches: It integrates paired-end and breakpoint junction analyses with depth-of-coverage information to distinguish homozygous and heterozygous CNVs.
• Benchmarking and Validation: CopySeq was benchmarked on 500 CNV regions across chromosome 1 in 150 low-coverage personal genomes, showing a Pearson correlation coefficient of 0.94 with qPCR and 95-99% concordance with two established microarray platforms.

Scientific Applications:

• Gene Region Analysis: Analyzes gene regions enriched for segmental duplications, exemplified by olfactory receptor (OR) loci, to infer copy-number genotypes.
• Genetic Variant Identification: Identifies deleterious genetic variants, including CNVs and single nucleotide polymorphisms (SNPs), affecting approximately 15% and 20% of the human OR gene repertoire, respectively.
• Reference Genome Evaluation: Detects discrepancies between observed locus copy-numbers and reference genome representations, indicating loci where reference sequences may underrepresent minor-frequency variants.

Methodology:

Uses depth-of-coverage from high-throughput DNA sequencing reads, paired-end and breakpoint-junction analyses, and a statistical framework to infer genomic copy-number genotypes at gene-family and genome-wide scales.