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

Nat Commun. 2014 Jun 13:5:3934. doi: 10.1038/ncomms4934.

Abstract

A major use of the 1000 Genomes Project (1000 GP) 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 1000 GP 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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Alleles
  • Gene Frequency
  • Genome, Human*
  • Genome-Wide Association Study*
  • Haplotypes
  • Humans
  • Microarray Analysis / statistics & numerical data*
  • Polymorphism, Single Nucleotide