Fast and Robust Identity-by-Descent Inference with the Templated Positional Burrows–Wheeler Transform

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 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 data sets 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 noncommercial use in the code repository (https://github.com/23andMe/phasedibd, last accessed January 11, 2021).

Open-source benchmarking of IBD segment detection methods for biobank-scale cohorts

“…The RaPID [ 18 ] software package and source code are available at RaPID’s GitHub [ 42 ]. The TPBWT [ 22 ] software package and source code are available at TPBWT’s GitHub [ 43 ].…”

Bonsai: An efficient method for inferring large human pedigrees from genotype data

“…have demonstrated that half-sibling, avuncular, and grandparental relationships, which have been difficult to differentiate historically due to the fact that the total amount of IBD is the same for each of these relationship types, can be differentiated by making use of long-range phasing information. Phased IBD estimates, obtained from programs such as the PhasedIBD method of Freyman et al (2020), could provide a considerable boost in accuracy for close relationships.…”

Current Developments in Detection of Identity-by-Descent Methods and Applications

“…In addition, hap-IBD may run the PBWT in parallel, thus showing the best performance among algorithms benchmarked in UK BioBank data. Similarly, investigators at 23andMe leveraged the same PBWT to develop their new Templated PBWT framework (Freyman et al, 2021) with similar properties and efficient, scalable runtime. TPBWT is notable for attempting to identify and correct phase switch errors, thereby improving IBD tract length estimation and longrange phasing.…”