Larger pedigrees could be divided into subsets of duos and trios but often there will exist no subdivision that allows all samples to exploit a parental relationship. For example, a family with two parents and two siblings may be divided into two duos, but partitioning a nuclear family with three children means at least one child will be phased without using parental information. There is no obvious optimum way to partition pedigrees of arbitrary size and structure. We investigated a simple method where we enumerate every possible partitioning of a pedigree into duos/trios and choose the partition that minimises the number of individuals that are not included in a duo/trio (many partitions often share the same minimum in which case one is picked at random). We applied this partitioning to the datasets and then ran Beagle (since it was the next most competitive method) taking the implied duo and trio information into account. We refer to this as the Beagle duo/trio method. Beagle was found to use substantially more memory in this setting (over 150 GB for the GPC cohort)
