PT  - JOURNAL ARTICLE
AU  - Monica D. Ramstetter
AU  - Thomas D. Dyer
AU  - Donna M. Lehman
AU  - Joanne E. Curran
AU  - Ravindranath Duggirala
AU  - John Blangero
AU  - Jason G. Mezey
AU  - Amy L. Williams
TI  - Inferring identical by descent sharing of sample ancestors promotes high resolution relative detection
AID  - 10.1101/243048
DP  - 2018 Jan 01
TA  - bioRxiv
PG  - 243048
4099  - http://biorxiv.org/content/early/2018/01/04/243048.short
4100  - http://biorxiv.org/content/early/2018/01/04/243048.full
AB  - As genetic datasets increase in size, the fraction of samples with one or more close relatives increases rapidly, resulting in sets of mutually related individuals. We present DRUID—Deep Relatedness Utilizing Identity by Descent—a method that works by inferring the identical by descent (IBD) sharing profile of an ungenotyped ancestor of a set of close relatives. Using this IBD profile, DRUID infers relatedness between these unobserved ancestors and more distant relatives, thereby combining information from multiple samples to remove one or more generations between the deep relationships to be identified. DRUID constructs sets of close relatives by detecting full siblings and also uses a novel approach to identify the aunts/uncles of two or more siblings, recovering 95.4% of real aunts/uncles with zero false positives. We used DRUID to infer relatedness among individuals in both real and simulated data by applying it to close relatives consisting of full siblings or siblings and their aunts/uncles. Compared to PADRE, DRUID correctly infers up to 10% more relatives when using data from two sets of distantly related siblings, and 10–30% more relatives given two sets of siblings and their aunts/uncles. DRUID frequently infers relationships either correctly or within one degree of the truth, with PADRE classifying 43–58% of tenth degree relatives in this way compared to 78–96% using DRUID.