Accuracy of haplotype estimation and whole genome imputation affects complex trait analyses in complex biobanks

Vivek Appadurai*, Jonas Bybjerg-Grauholm, Morten Dybdahl Krebs, Anders Rosengren, Alfonso Buil, Andrés Ingason, Ole Mors, Anders D Børglum, David M Hougaard, Merete Nordentoft, Preben B Mortensen, Olivier Delaneau, Thomas Werge, Andrew J Schork*

*Corresponding author for this work

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

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Sample recruitment for research consortia, biobanks, and personal genomics companies span years, necessitating genotyping in batches, using different technologies. As marker content on genotyping arrays varies, integrating such datasets is non-trivial and its impact on haplotype estimation (phasing) and whole genome imputation, necessary steps for complex trait analysis, remains under-evaluated. Using the iPSYCH dataset, comprising 130,438 individuals, genotyped in two stages, on different arrays, we evaluated phasing and imputation performance across multiple phasing methods and data integration protocols. While phasing accuracy varied by choice of method and data integration protocol, imputation accuracy varied mostly between data integration protocols. We demonstrate an attenuation in imputation accuracy within samples of non-European origin, highlighting challenges to studying complex traits in diverse populations. Finally, imputation errors can bias association tests, reduce predictive utility of polygenic scores. Carefully optimized data integration strategies enhance accuracy and replicability of complex trait analyses in complex biobanks.

Original languageEnglish
Article number101
JournalCommunications Biology
Number of pages12
Publication statusPublished - Dec 2023


  • Biological Specimen Banks
  • Genome
  • Genotype
  • Haplotypes
  • Humans
  • Multifactorial Inheritance


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