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

Pedigree inference from genotype data is a challenging problem, particularly when pedigrees are sparsely sampled and individuals may be distantly related to their closest genotyped relatives. We present a method that infers small pedigrees of close relatives and then assembles them into larger pedigrees. To assemble large pedigrees, we introduce several formulas and tools including a likelihood for the degree separating two small pedigrees, a generalization of the fast DRUID point estimate of the degree separating two pedigrees, a method for detecting individuals who share background identity-by-descent (IBD) that does not reflect recent common ancestry, and a method for identifying the ancestral branches through which distant relatives are connected. Our method also takes several approaches that help to improve the accuracy and efficiency of pedigree inference. In particular, we incorporate age information directly into the likelihood rather than using ages only for consistency checks and we employ a heuristic branch-and-bound-like approach to more efficiently explore the space of possible pedigrees. Together, these approaches make it possible to construct large pedigrees that are challenging or intractable for current inference methods.

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Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of interests E.M.J., K.F.M., W.A.F., and A.A. are employees of and have stocks, stock options, or both in 23andMe. They are authors on the patent application: Methods and systems for determining and displaying pedigrees. Publications: WO 2021/051018, US 2021/0082167, and US 2021/0166452.