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Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel

MPG-Autoren

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Lehrach, Hans
Max Planck Institute for Molecular Genetics, Max Planck Society;

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Sudbrak, R.
Max Planck Institute for Molecular Genetics, Max Planck Society;

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Lienhard, Matthias
Bioinformatics (Ralf Herwig), Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Mertes, Florian
Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Sultan, Marc
Human Chromosome 21 (Marie-Laure Yaspo), Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Timmermann, Bernd
Sequencing (Head: Bernd Timmermann), Scientific Service (Head: Christoph Krukenkamp), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Yaspo, Marie-Laure
Gene Regulation and Systems Biology of Cancer (Marie-Laure Yaspo), Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Herwig, Ralf
Bioinformatics (Ralf Herwig), Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Zitation

Delaneau, O., Marchini, J., 1000 Genomes Project Consortium, Lehrach, H., Sudbrak, R., Amstislavskiy, V., et al. (2014). Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel. Nature Communications, 13(5), 3934. doi:10.1038/ncomms4934.

Zusammenfassung

A major use of the 1000 Genomes Project (1000GP) data is genotype imputation in genome-wide association studies (GWAS). Here we develop a method to estimate haplotypes from low-coverage sequencing data that can take advantage of single-nucleotide polymorphism (SNP) microarray genotypes on the same samples. First the SNP array data are phased to build a backbone (or ‘scaffold’) of haplotypes across each chromosome. We then phase the sequence data ‘onto’ this haplotype scaffold. This approach can take advantage of relatedness between sequenced and non-sequenced samples to improve accuracy. We use this method to create a new 1000GP haplotype reference set for use by the human genetic community. Using a set of validation genotypes at SNP and bi-allelic indels we show that these haplotypes have lower genotype discordance and improved imputation performance into downstream GWAS samples, especially at low-frequency variants.