PT  - JOURNAL ARTICLE
AU  - Ying Zhou
AU  - Sharon R. Browning
AU  - Brian L. Browning
TI  - A fast and simple method for detecting identity by descent segments in large-scale data
AID  - 10.1101/2019.12.12.874685
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 2019.12.12.874685
4099  - http://biorxiv.org/content/early/2019/12/12/2019.12.12.874685.short
4100  - http://biorxiv.org/content/early/2019/12/12/2019.12.12.874685.full
AB  - 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.