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Harmonization of study and reference data by PhaseLift: saving time when imputing study data.

Mathias Gorski1, Thomas W Winkler, Klaus Stark

  • 1Department of Genetic Epidemiology, Institute of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany; Department of Nephrology, University Hospital Regensburg, Regensburg, Germany.

Genetic Epidemiology
|June 26, 2014
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Summary
This summary is machine-generated.

A new postphasing lift-over method harmonizes study and reference haplotypes, saving significant computational time for updating genome-wide association study imputations without rephasing.

Keywords:
1000 GenomesHapMapgenome-wide association studiesgenotype imputationimputation qualitymeta-analysis

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Area of Science:

  • Genomics
  • Bioinformatics
  • Statistical Genetics

Background:

  • Genome-wide association studies (GWAS) utilize imputation to enhance SNP chip data.
  • Current imputation methods separate haplotype phasing from imputation, limiting reference panel updates.
  • Discrepancies in genome build between study and reference data necessitate rephasing and re-imputation.

Purpose of the Study:

  • To introduce a novel postphasing lift-over approach for harmonizing GWAS data with updated reference panels.
  • To evaluate the efficiency and accuracy of the postphasing lift-over method compared to existing prephasing lift-over techniques.
  • To reduce computational burden associated with updating imputed genetic data.

Main Methods:

  • Developed a postphasing lift-over method to harmonize study haplotypes with reference haplotypes.
  • Compared the performance of postphasing lift-over against prephasing lift-over using data from 1,644 individuals.
  • Evaluated imputation accuracy by comparing imputed genotypes with directly typed data.

Main Results:

  • The postphasing lift-over approach achieves comparable imputation accuracy to prephasing lift-over (mean concordance of 93%).
  • Imputation quality metrics (RSQ) were similar between both methods (mean difference < 0.1%).
  • The novel approach significantly reduces computational time, potentially saving up to one month per re-imputation.

Conclusions:

  • Postphasing lift-over is a practical and time-saving alternative for updating imputed GWAS data with new reference panels.
  • This method facilitates the integration of updated reference builds, enhancing the information content of genetic studies.
  • The PhaseLift software implements this novel approach, promoting efficient genomic data analysis.