RT Journal Article
SR Electronic
T1 Inferring identical by descent sharing of sample ancestors promotes high resolution relative detection
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 243048
DO 10.1101/243048
A1 Monica D. Ramstetter
A1 Sushila A. Shenoy
A1 Thomas D. Dyer
A1 Donna M. Lehman
A1 Joanne E. Curran
A1 Ravindranath Duggirala
A1 John Blangero
A1 Jason G. Mezey
A1 Amy L. Williams
YR 2018
UL http://biorxiv.org/content/early/2018/04/13/243048.abstract
AB As genetic datasets increase in size, the fraction of samples with one or more close relatives grows 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 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 92.2% of real aunts/uncles with zero false positives. In real and simulated data, DRUID correctly infers up to 10.5% more relatives than PADRE when using data from two sets of distantly related siblings, and 10.7–31.3% 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 43.3–58.3% of tenth degree relatives in this way compared to 79.6–96.7% using DRUID.