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

Olivier Delaneau and Jonathan Marchini ()
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Olivier Delaneau: University of Oxford
Jonathan Marchini: University of Oxford

Nature Communications, 2014, vol. 5, issue 1, 1-9

Abstract: Abstract 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.

Date: 2014
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DOI: 10.1038/ncomms4934

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