Dataset Information

Reference-based phasing using the Haplotype Reference Consortium panel.

ABSTRACT: Haplotype phasing is a fundamental problem in medical and population genetics. Phasing is generally performed via statistical phasing in a genotyped cohort, an approach that can yield high accuracy in very large cohorts but attains lower accuracy in smaller cohorts. Here we instead explore the paradigm of reference-based phasing. We introduce a new phasing algorithm, Eagle2, that attains high accuracy across a broad range of cohort sizes by efficiently leveraging information from large external reference panels (such as the Haplotype Reference Consortium; HRC) using a new data structure based on the positional Burrows-Wheeler transform. We demonstrate that Eagle2 attains a ?20× speedup and ?10% increase in accuracy compared to reference-based phasing using SHAPEIT2. On European-ancestry samples, Eagle2 with the HRC panel achieves >2× the accuracy of 1000 Genomes-based phasing. Eagle2 is open source and freely available for HRC-based phasing via the Sanger Imputation Service and the Michigan Imputation Server.

SUBMITTER: Loh PR

PROVIDER: S-EPMC5096458 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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Reference-based phasing using the Haplotype Reference Consortium panel.

Loh Po-Ru PR Danecek Petr P Palamara Pier Francesco PF Fuchsberger Christian C A Reshef Yakir Y K Finucane Hilary H Schoenherr Sebastian S Forer Lukas L McCarthy Shane S Abecasis Goncalo R GR Durbin Richard R L Price Alkes A

Nature genetics 20161003 11

Haplotype phasing is a fundamental problem in medical and population genetics. Phasing is generally performed via statistical phasing in a genotyped cohort, an approach that can yield high accuracy in very large cohorts but attains lower accuracy in smaller cohorts. Here we instead explore the paradigm of reference-based phasing. We introduce a new phasing algorithm, Eagle2, that attains high accuracy across a broad range of cohort sizes by efficiently leveraging information from large external ...[more]

PMID: 27694958

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Project description:BackgroundKnowledge of phase, the specific allele sequence on each copy of homologous chromosomes, is increasingly recognized as critical for detecting certain classes of disease-associated mutations. One approach for detecting such mutations is through phased haplotype association analysis. While the accuracy of methods for phasing genotype data has been widely explored, there has been little attention given to phasing accuracy at haplotype block scale. Understanding the combined impact of the accuracy of phasing tool and the method used to determine haplotype blocks on the error rate within the determined blocks is essential to conduct accurate haplotype analyses.ResultsWe present a systematic study exploring the relationship between seven widely used phasing methods and two common methods for determining haplotype blocks. The evaluation focuses on the number of haplotype blocks that are incorrectly phased. Insights from these results are used to develop a haplotype estimator based on a consensus of three tools. The consensus estimator achieved the most accurate phasing in all applied tests. Individually, EAGLE2, BEAGLE and SHAPEIT2 alternate in being the best performing tool in different scenarios. Determining haplotype blocks based on linkage disequilibrium leads to more correctly phased blocks compared to a sliding window approach. We find that there is little difference between phasing sections of a genome (e.g. a gene) compared to phasing entire chromosomes. Finally, we show that the location of phasing error varies when the tools are applied to the same data several times, a finding that could be important for downstream analyses.ConclusionsThe choice of phasing and block determination algorithms and their interaction impacts the accuracy of phased haplotype blocks. This work provides guidance and evidence for the different design choices needed for analyses using haplotype blocks. The study highlights a number of issues that may have limited the replicability of previous haplotype analysis.

Dataset Information

Reference-based phasing using the Haplotype Reference Consortium panel.

Publications

Reference-based phasing using the Haplotype Reference Consortium panel.

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