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

Jewett, Ethan M.; McManus, Kimberly F.; Freyman, William A.; Auton, Adam

doi:10.1101/2021.04.06.438656

Cited by 2 publications

(2 citation statements)

References 26 publications

(36 reference statements)

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“…PRIMUS [19] was excluded because it did not run successfully with the IBD values in real and simulated mice analyzed here. Finally, BONSAI [32] was also not evaluated, because it is intended for sparse pedigrees and contains hard-coded IBD and age distributions optimized for humans. We used three datasets to compare the methods: 1) a subset of a population of wild house mice from a long-term study, 2) five simulated datasets based on the genotypes of the founders of the long-term house mice study, and 3) a published dataset of a cattle pedigree and its genotypes [13,33].…”

Section: Comparison To Other Methodsmentioning

confidence: 99%

Parent-offspring inference in inbred populations

Runge

König

Lindholm

et al. 2021

Preprint

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Genealogical relationships are fundamental components of genetic studies. However, it is often challenging to infer correct and complete pedigrees even when genome-wide information is available. For example, inbreeding can obfuscate genetic differences between individuals, making it difficult to even distinguish first-degree relatives such as parent-offspring from full siblings. Similarly, genotyping errors can interfere with the detection of genetic similarity between parents and their offspring. Inbreeding is common in natural, domesticated, and experimental populations and genotyping of these populations often has more errors than in human datasets, so efficient methods for building pedigrees under these conditions are necessary. Here, we present a new method for parent-offspring inference in inbred pedigrees called SPORE (Specific Parent-Offspring Relationship Estimation). SPORE is vastly superior to existing pedigree-inference methods at detecting parent-offspring relationships, in particular when inbreeding is high or in the presence of genotyping errors, or both. SPORE therefore fills an important void in the arsenal of pedigree inference tools.Author SummaryKnowing the genealogical relationships among individuals is critical for genetic analyses, such as for identifying the mutations that cause diseases or that contribute to valuable agricultural traits such as milk production. Although many tools exist for establishing pedigrees using genetic information, these tools fail when individuals are highly inbred, such as in domesticated animals, or in groups of people in which consanguineous matings are common. Furthermore, existing tools do not work well when genetic information has errors at levels observed in modern datasets. Here, we present a novel approach to solve these problems. Our method is significantly more accurate than existing tools and more tolerant of errors in the genetic data. We expect that our method, which is simple to use and computationally efficient, will be a useful tool in a diversity of settings, from the studies of human and natural populations, to agricultural and experimental settings.

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Section: Comparison To Other Methodsmentioning

confidence: 99%

Parent-offspring inference in inbred populations

Runge

König

Lindholm

et al. 2021

Preprint

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“…One notable example is the UK Biobank wherein roughly 30% of genotyped individuals have a third degree (e.g., first cousin) or closer relative in the study 2 . Applications that make use of genetic relatives are numerous and varied and include pedigree reconstruction 3,4 , pedigree-based linkage analysis for disease and trait mapping 5 , heritability estimation 6,7 , forensic genetics 8 , and genetic genealogy 9 -a popular tool among direct-to-consumer genetic testing customers. On the other hand, traditional genome-wide association study tests and many population genetic models assume that the study samples are unrelated, and, as such, must exclude inferred relatives to avoid spurious signals or inaccurate parameter estimates 10 .…”

Section: Introductionmentioning

confidence: 99%

Evaluating the utility of identity-by-descent segment numbers for relatedness inference via information theory and classification

Smith

Qiao

Williams

2021

Preprint

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Despite decades of methods development for classifying relatives in genetic studies, pairwise relatedness methods' recalls are above 90% only for first through third degree relatives. The top-performing approaches, which leverage identity-by-descent (IBD) segments, often use only kinship coefficients, while others, including ERSA, use the number of segments relatives share. To quantify the potential for using segment numbers in relatedness inference, we leveraged information theory measures to analyze exact (i.e., produced by a simulator) IBD segments from simulated relatives. Over a range of settings, we found that the mutual information between the relatives' degree of relatedness and a tuple of their kinship coefficient and segment number is on average 4.6% larger than between the degree and the kinship coefficient alone. We further evaluated IBD segment number utility by building a Bayes classifier to predict first through sixth degree relationships using different feature sets. When trained and tested with exact segments, the inclusion of segment numbers improves the recall by between 0.0028 and 0.030 for second through sixth degree relatives. However, the recalls improve by less than 0.018 per degree when using inferred segments, suggesting limitations due to IBD detection accuracy. Lastly, we compared our Bayes classifier that includes segment numbers with ERSA and IBIS and found comparable results, with the Bayes classifier and ERSA slightly outperforming each other across different degrees. Overall, this study shows that IBD segment numbers can improve relatedness inference but that errors from current SNP array-based detection methods yield dampened signals in practice.

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

Cited by 2 publications

References 26 publications

Parent-offspring inference in inbred populations

Parent-offspring inference in inbred populations

Evaluating the utility of identity-by-descent segment numbers for relatedness inference via information theory and classification

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