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bioRxiv · 10.1101/2019.12.12.874685

A fast and simple method for detecting identity by descent segments in large-scale data

Zhou, Y.·Browning, S.·Browning, B. L.
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Abstract

Segments of identity by descent (IBD) are used in many genetic analyses. We present a method for detecting identical-by-descent haplotype segments that is optimized for large-scale genotype data. Our method, called hap-IBD, combines a compressed representation of genotype data, the positional Burrows-Wheeler transform, and multi-threaded execution to produce very fast analysis times. An attractive feature of hap-IBD is its simplicity: the input parameters clearly and precisely define the IBD segments that are reported, so that program correctness can be confirmed by users. We evaluate hap-IBD and four state-of-the-art IBD segment detection methods (GERMLINE, iLASH, RaPID, and TRUFFLE) using UK Biobank chromosome 20 data and simulated sequence data. We show that hap-IBD detects IBD segments faster and more accurately than competing methods, and that hap-IBD is the only method that can rapidly and accurately detect short 2-4 cM IBD segments in the full UK Biobank data. Analysis of 485,346 UK Biobank samples using hap-IBD with 12 computational threads detects 231.5 billion autosomal IBD segments with length [≥]2 cM in 24.4 hours.

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Zhou, Y., Browning, S., Browning, B. L.. 2019-12-12. A fast and simple method for detecting identity by descent segments in large-scale data. https://doi.org/10.1101/2019.12.12.874685

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