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Fast and robust identity-by-descent inference with the templated positional Burrows-Wheeler transform

View ORCID ProfileWilliam A. Freyman, Kimberly F. McManus, Suyash S. Shringarpure, Ethan M. Jewett, Katarzyna Bryc, The 23 and Me Research Team, Adam Auton
doi: https://doi.org/10.1101/2020.09.14.296939
William A. Freyman
123andMe, Inc., Sunnyvale, CA, USA
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  • For correspondence: willf@23andMe.com aauton@23andme.com
Kimberly F. McManus
123andMe, Inc., Sunnyvale, CA, USA
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Suyash S. Shringarpure
123andMe, Inc., Sunnyvale, CA, USA
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Ethan M. Jewett
123andMe, Inc., Sunnyvale, CA, USA
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Katarzyna Bryc
123andMe, Inc., Sunnyvale, CA, USA
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123andMe, Inc., Sunnyvale, CA, USA
Adam Auton
123andMe, Inc., Sunnyvale, CA, USA
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Abstract

Estimating the genomic location and length of identical-by-descent (IBD) segments among individuals is a crucial step in many genetic analyses. However, the exponential growth in the size of biobank and direct-to-consumer (DTC) genetic data sets makes accurate IBD inference a significant computational challenge. Here we present the templated positional Burrows-Wheeler transform (TPBWT) to make fast IBD estimates robust to genotype and phasing errors. Using haplotype data simulated over pedigrees with realistic genotyping and phasing errors we show that the TPBWT outperforms other state-of-the-art IBD inference algorithms in terms of speed and accuracy. For each phase-aware method, we explore the false positive and false negative rates of inferring IBD by segment length and characterize the types of error commonly found. Our results highlight the fragility of most phased IBD inference methods; the accuracy of IBD estimates can be highly sensitive to the quality of haplotype phasing. Additionally we compare the performance of the TPBWT against a widely used phase-free IBD inference approach that is robust to phasing errors. We introduce both in-sample and out-of-sample TPBWT-based IBD inference algorithms and demonstrate their computational efficiency on massive-scale datasets with millions of samples. Furthermore we describe the binary file format for TPBWT-compressed haplotypes that results in fast and efficient out-of-sample IBD computes against very large cohort panels. Finally, we demonstrate the utility of the TPBWT in a brief empirical analysis exploring geographic patterns of haplotype sharing within Mexico. Hierarchical clustering of IBD shared across regions within Mexico reveals geographically structured haplotype sharing and a strong signal of isolation by distance. Our software implementation of the TPBWT is freely available for non-commercial use in the code repository https://github.com/23andMe/phasedibd.

Competing Interest Statement

W.A.F., K.F.M., S.S.S., E.M.J., K.B., and A.A. are employed by 23andMe, Inc.

Footnotes

  • https://github.com/23andMe/phasedibd

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted November 25, 2020.
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Fast and robust identity-by-descent inference with the templated positional Burrows-Wheeler transform
William A. Freyman, Kimberly F. McManus, Suyash S. Shringarpure, Ethan M. Jewett, Katarzyna Bryc, The 23 and Me Research Team, Adam Auton
bioRxiv 2020.09.14.296939; doi: https://doi.org/10.1101/2020.09.14.296939
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Fast and robust identity-by-descent inference with the templated positional Burrows-Wheeler transform
William A. Freyman, Kimberly F. McManus, Suyash S. Shringarpure, Ethan M. Jewett, Katarzyna Bryc, The 23 and Me Research Team, Adam Auton
bioRxiv 2020.09.14.296939; doi: https://doi.org/10.1101/2020.09.14.296939

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