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

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  • Olivier Delaneau

    (University of Oxford)

  • Jonathan Marchini

    (University of Oxford
    Wellcome Trust Centre for Human Genetics, University of Oxford)

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.

Suggested Citation

  • Olivier Delaneau & Jonathan Marchini, 2014. "Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel," Nature Communications, Nature, vol. 5(1), pages 1-9, September.
  • Handle: RePEc:nat:natcom:v:5:y:2014:i:1:d:10.1038_ncomms4934
    DOI: 10.1038/ncomms4934
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    Cited by:

    1. Robin J. Hofmeister & Simone Rubinacci & Diogo M. Ribeiro & Alfonso Buil & Zoltán Kutalik & Olivier Delaneau, 2022. "Parent-of-Origin inference for biobanks," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    2. Tenna Ruest Haarmark Nielsen & Emil Vincent Rosenbaum Appel & Mathilde Svendstrup & Johanne Dam Ohrt & Maria Dahl & Cilius Esmann Fonvig & Mette Hollensted & Christian Theil Have & Haja N Kadarmideen , 2017. "A genome-wide association study of thyroid stimulating hormone and free thyroxine in Danish children and adolescents," PLOS ONE, Public Library of Science, vol. 12(3), pages 1-16, March.
    3. Andrew A. Brown & Juan J. Fernandez-Tajes & Mun-gwan Hong & Caroline A. Brorsson & Robert W. Koivula & David Davtian & Théo Dupuis & Ambra Sartori & Theodora-Dafni Michalettou & Ian M. Forgie & Jonath, 2023. "Genetic analysis of blood molecular phenotypes reveals common properties in the regulatory networks affecting complex traits," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    4. Kerstin Becker & Sabine Siegert & Mohammad Reza Toliat & Juanjiangmeng Du & Ramona Casper & Guido H Dolmans & Paul M Werker & Sigrid Tinschert & Andre Franke & Christian Gieger & Konstantin Strauch & , 2016. "Meta-Analysis of Genome-Wide Association Studies and Network Analysis-Based Integration with Gene Expression Data Identify New Suggestive Loci and Unravel a Wnt-Centric Network Associated with Dupuytr," PLOS ONE, Public Library of Science, vol. 11(7), pages 1-18, July.
    5. Rozaimi Mohamad Razali & Juan Rodriguez-Flores & Mohammadmersad Ghorbani & Haroon Naeem & Waleed Aamer & Elbay Aliyev & Ali Jubran & Andrew G. Clark & Khalid A. Fakhro & Younes Mokrab, 2021. "Thousands of Qatari genomes inform human migration history and improve imputation of Arab haplotypes," Nature Communications, Nature, vol. 12(1), pages 1-16, December.

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