Rapid, Phase-free Detection of Long Identity-by-Descent Segments Enables Effective Relationship Classification

Seidman, Daniel; Shenoy, Sushila; Kim, Min‐Soo; Babu, R. Buli; Woods, Ian G.; Dyer, Thomas D.; Lehman, Donna M.; Curran, Joanne E.; Duggirala, Ravindranath; Blangero, John; Williams, Amy L.

doi:10.1016/j.ajhg.2020.02.012

Cited by 46 publications

(57 citation statements)

References 41 publications

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“…We compared the performance of TPBWT to an IBD inference algorithm that is robust to phasing errors because it uses unphased data. This algorithm was first described in Henn et al (2012), and was developed independently by Seidman et al (2020), who called it IBIS. We compared TPBWT to the 23andMe C++ implementation of the IBIS algorithm that was used in Henn et al (2012), which we refer to here as IBIS-like.…”

Section: Resultsmentioning

confidence: 99%

“…We compared TPBWT to the 23andMe C++ implementation of the IBIS algorithm that was used in Henn et al (2012), which we refer to here as IBIS-like. The IBIS-like algorithm is known to have a high false positive rate for shorter IBD segments (Henn et al 2012; Seidman et al 2020). To account for this while comparing the accuracy of detecting IBD with IBIS-like and the TPBWT, we replicated the trio validation approach used in Henn et al (2012).…”

Section: Resultsmentioning

confidence: 99%

“…For bins of IBD segment lengths we calculated the proportion of segments that were trio validated ( h mean ) using both TPBWT and IBIS-like, as detailed in Section 4.7.5. Since both Henn et al (2012) and Seidman et al (2020) showed that IBIS-like algorithms have high false positive rates for segments < 7 cM in length, we used 7 cM has the minimum segment length for the IBIS-like algorithm.…”

Section: Resultsmentioning

confidence: 99%

“…In contrast to the limitations previously discussed with phase-aware IBD methods in accurately identifying IBD among closely related individuals, the major limitation in the accuracy of phase-free IBD methods is in accurately detecting short IBD segments shared among distantly related individuals. 23andMe has used the phase-free algorithm described in Henn et al (2012) and Seidman et al (2020) to compute IBD among millions of customers. This approach scans individual’s unphased data for long regions of compatible diplotypes (regions in which two individuals do not have sites with different homozygous genotypes).…”

Section: Discussionmentioning

confidence: 99%

“…We show here that using this approach over half of all 7 cM IBD segments estimated were likely false positive segments. If phase-free IBD detection methods such as Henn et al (2012) and Seidman et al (2020) are used, downstream quality control filtering of shorter segments should be applied (as is done at 23andMe). Regardless, using these phase-free approaches means that massive amounts of very short ( < 7 cM) haplotype sharing among distantly related individuals can never be reliably detected.…”

Section: Discussionmentioning

confidence: 99%

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

Freyman

McManus

Shringarpure

et al. 2020

Preprint

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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 haplotype 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. 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 a 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 the geographic structure of Mexico’s rich genetic diversity. Our software implementation of the TPBWT is freely available in the code repository https://github.com/23andMe/phasedibd.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 3 more Smart Citations

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

Freyman

McManus

Shringarpure

et al. 2020

Preprint

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Including diverse and admixed populations in genetic epidemiology research

Caliebe

Tekola‐Ayele

Darst

et al. 2022

Genetic Epidemiology

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The inclusion of ancestrally diverse participants in genetic studies can lead to new discoveries and is important to ensure equitable health care benefit from research advances. Here, members of the Ethical, Legal, Social, Implications (ELSI) committee of the International Genetic Epidemiology Society (IGES) offer perspectives on methods and analysis tools for the conduct of inclusive genetic epidemiology research, with a focus on admixed and ancestrally diverse populations in support of reproducible research practices. We emphasize the importance of distinguishing socially defined population categorizations from genetic ancestry in the design, analysis, reporting, and interpretation of genetic epidemiology research findings. Finally, we discuss the current state of

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Characterizing identity by descent segments in Chinese interpopulation unrelated individual pairs

Ji,

Yao,

et al. 2024

Mol Genet Genomics

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Rapid, Phase-free Detection of Long Identity-by-Descent Segments Enables Effective Relationship Classification

Cited by 46 publications

References 41 publications

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

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

Including diverse and admixed populations in genetic epidemiology research

Characterizing identity by descent segments in Chinese interpopulation unrelated individual pairs

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