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.

从基因型数据推断谱系是一个具有挑战性的问题，特别是当谱系样本稀疏且个体可能与其最近的基因分型亲属有远亲关系时。我们提出了一种方法，可以推断近亲的小谱系，然后将它们组合成更大的谱系。为了组装大谱系，我们引入了几个公式和工具，包括分离两个小谱系的度数的可能性，分离两个谱系的度数的快速 DRUID 点估计的推广，一种用于检测共享背景身份的个体的方法。 (IBD) 不反映最近的共同祖先，以及识别远亲连接的祖先分支的方法。我们的方法还采用了多种方法来帮助提高系谱推断的准确性和效率。特别是，我们将年龄信息直接纳入可能性中，而不是仅将年龄用于一致性检查，并且我们采用启发式分支定界方法来更有效地探索可能的谱系空间。总之，这些方法使得构建对当前推理方法具有挑战性或难以处理的大型谱系成为可能。