cnvHap: an integrative population and haplotype-based multiplatform model of SNPs and CNVs.

Journal article

Although genome-wide association studies have uncovered single-nucleotide polymorphisms (SNPs) associated with complex disease, these variants account for a small portion of heritability. Some contribution to this 'missing heritability' may come from copy-number variants (CNVs), in particular rare CNVs; but assessment of this contribution remains challenging because of the difficulty in accurately genotyping CNVs, particularly small variants. We report a population-based approach for the identification of CNVs that integrates data from multiple samples and platforms. Our algorithm, cnvHap, jointly learns a chromosome-wide haplotype model of CNVs and cluster-based models of allele intensity at each probe. Using data for 50 French individuals assayed on four separate platforms, we found that cnvHap correctly detected at least 14% more deleted and 50% more amplified genotypes than PennCNV or QuantiSNP, with an 82% and 115% improvement for aberrations containing <10 probes. Combining data from multiple platforms additionally improved sensitivity.

Authors: Coin, L; Asher, J; Walters, R; Moustafa, J; de Smith, A

• Publication status: Published
• Journal: Nature methods
• Volume: 7
• Issue: 7
• Pages: 541-546
• Publication date: 2010-07-01
• DOI: 10.1038/nmeth.1466
• EISSN: 1548-7105
• ISSN: 1548-7091
• Language: English
• Keywords: Chromosomes, Human, Pair 1; Polymorphism, Single Nucleotide; Humans; Databases, Factual; Nucleic Acid Amplification Techniques; Haplotypes; Chromosome Mapping; Reproducibility of Results