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

Nature Methods volume 7, pages 541–546 (2010)Cite this article

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Abstract

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.

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Figure 1: Schematic flow chart showing cnvHap operation.
Figure 2: Visualization of cnvHap population model on chromosome 1 for integrated Illumina 1M and Agilent 244k datasets.
Figure 3: CNV predictions for chromosome 1 25.452 Mb–25.536 Mb.
Figure 4: Cumulative frequency of squared Pearson's correlation coefficient between predicted and benchmark copy number calls.
Figure 5: ROC curves for detecting CNVs using Illumina 1M data.
Figure 6: Combining datasets improved sensitivity.

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Acknowledgements

We thank D. Serre, A. Montpetit and D. Vincent for advice concerning Illumina arrays and D. Peiffer (Illumina) for providing genotype data on HapMap samples. Genome Canada and Genome Quebec funded genotyping on the Illumina Human1M platform. L.J.M.C. is funded by a Research Council UK fellowship. J.E.A. is supported by the Medical Research Council. R.G.W. is supported by Johnson & Johnson and the South East England Development Agency. J.S.E.-S.M. is supported by an Imperial College Division of Medicine PhD studentship.

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Authors and Affiliations

  1. Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St. Mary's Hospital, London, UK

    Lachlan J M Coin

  2. Department of Genomics of Common Disease, School of Public Health, Imperial College London, Hammersmith Hospital, London, UK

    Julian E Asher, Robin G Walters, Julia S El-Sayed Moustafa, Adam J de Smith, Philippe Froguel & Alexandra I F Blakemore

  3. Departments of Medicine and Human Genetics, McGill University and Genome Quebec Innovation Centre, Montreal, Quebec, Canada

    Rob Sladek

  4. Institute of Genetics, University College London, London, UK

    David J Balding

  5. Centre National de la Recherche Scientifique 8090, Institute of Biology, Pasteur Institute, Lille, France

    Philippe Froguel

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  1. Lachlan J M Coin
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Contributions

L.J.M.C. designed the project with A.I.F.B., developed the cnvHap algorithm and software, analyzed data and wrote the paper. J.E.A. ran cnvPartition, PennCNV and QuantiSNP on the data and helped write the paper. R.G.W. and J.S.E.-S.M. provided critical comments and helped to write the paper. D.J.B. provided statistical advice. R.S. provided SNP genotype data, advised on its interpretation and edited the paper. A.J.d.S. provided aCGH data and advised on its interpretation. P.F. provided the DNA samples and coordinated the SNP genotyping. A.I.F.B. designed the project with L.J.M.C., coordinated the aCGH analysis, contributed to writing the paper and oversaw the project.

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Correspondence to Lachlan J M Coin.

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The authors declare no competing financial interests.

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Supplementary Figures 1–9, Supplementary Tables 1–3 and Supplementary Note 1 (PDF 1513 kb)

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Software, documentation and an example. (ZIP 9805 kb)

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Coin, L., Asher, J., Walters, R. et al. cnvHap: an integrative population and haplotype–based multiplatform model of SNPs and CNVs. Nat Methods 7, 541–546 (2010). https://doi.org/10.1038/nmeth.1466

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