PRIMUS: Rapid Reconstruction of Pedigrees from Genome-wide Estimates of Identity by Descent
Author(s) -
Jeffrey Staples,
Dandi Qiao,
Michael H. Cho,
Edwin K. Silverman,
Deborah A. Nickerson,
Jennifer E. Below
Publication year - 2014
Publication title -
the american journal of human genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.661
H-Index - 302
eISSN - 1537-6605
pISSN - 0002-9297
DOI - 10.1016/j.ajhg.2014.10.005
Subject(s) - pedigree chart , identity by descent , pairwise comparison , identification (biology) , computer science , sampling (signal processing) , statistics , data mining , genetics , artificial intelligence , biology , mathematics , haplotype , botany , filter (signal processing) , gene , genotype , computer vision
Understanding and correctly utilizing relatedness among samples is essential for genetic analysis; however, managing sample records and pedigrees can often be error prone and incomplete. Data sets ascertained by random sampling often harbor cryptic relatedness that can be leveraged in genetic analyses for maximizing power. We have developed a method that uses genome-wide estimates of pairwise identity by descent to identify families and quickly reconstruct and score all possible pedigrees that fit the genetic data by using up to third-degree relatives, and we have included it in the software package PRIMUS (Pedigree Reconstruction and Identification of the Maximally Unrelated Set). Here, we validate its performance on simulated, clinical, and HapMap pedigrees. Among these samples, we demonstrate that PRIMUS can verify reported pedigree structures and identify cryptic relationships. Finally, we show that PRIMUS reconstructed pedigrees, all of which were previously unknown, for 203 families from a cohort collected in Starr County, TX (1,890 samples).
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