| Title: | A Fast and Simple Method for Detecting Identity-by-Descent Segments in Large-Scale Data |
| Journal: | American Journal of Human Genetics |
| Published: | 12 Mar 2020 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/32169169/ |
| DOI: | https://doi.org/10.1016/j.ajhg.2020.02.010 |
| URL: | http://www.cell.com/article/S0002929720300525/pdf |
Publication 3871
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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 in phased genotype data. Our method, called hap-IBD, combines a compressed representation of haplotype 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 centiMorgan (cM) IBD segments in the full UK Biobank data. Analysis of 485,346 UK Biobank samples through the use of hap-IBD with 12 computational threads detects 231.5 billion autosomal IBD segments with length ≥2 cM in 24.4 h.</p>
3 Authors
- Ying Zhou
- Sharon R Browning
- Brian L Browning
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