Title | PADRE: Pedigree-Aware Distant-Relationship Estimation. |
Publication Type | Journal Article |
Year of Publication | 2016 |
Authors | Staples, J, Witherspoon, DJ, Jorde, LB, Nickerson, DA, Below, JE, Huff, CD |
Corporate Authors | University of Washington Center for Mendelian Genomics |
Journal | Am J Hum Genet |
Volume | 99 |
Issue | 1 |
Pagination | 154-62 |
Date Published | 2016 Jul 07 |
ISSN | 1537-6605 |
Keywords | Algorithms, Female, Haplotypes, Humans, Male, Models, Genetic, Pedigree, Reproducibility of Results |
Abstract | Accurate estimation of shared ancestry is an important component of many genetic studies; current prediction tools accurately estimate pairwise genetic relationships up to the ninth degree. Pedigree-aware distant-relationship estimation (PADRE) combines relationship likelihoods generated by estimation of recent shared ancestry (ERSA) with likelihoods from family networks reconstructed by pedigree reconstruction and identification of a maximum unrelated set (PRIMUS), improving the power to detect distant relationships between pedigrees. Using PADRE, we estimated relationships from simulated pedigrees and three extended pedigrees, correctly predicting 20% more fourth- through ninth-degree simulated relationships than when using ERSA alone. By leveraging pedigree information, PADRE can even identify genealogical relationships between individuals who are genetically unrelated. For example, although 95% of 13(th)-degree relatives are genetically unrelated, in simulations, PADRE correctly predicted 50% of 13(th)-degree relationships to within one degree of relatedness. The improvement in prediction accuracy was consistent between simulated and actual pedigrees. We also applied PADRE to the HapMap3 CEU samples and report new cryptic relationships and validation of previously described relationships between families. PADRE greatly expands the range of relationships that can be estimated by using genetic data in pedigrees. |
DOI | 10.1016/j.ajhg.2016.05.020 |
Alternate Journal | Am J Hum Genet |
PubMed ID | 27374771 |
PubMed Central ID | PMC5005450 |
Grant List | R01 GM104390 / GM / NIGMS NIH HHS / United States U54 HG006493 / HG / NHGRI NIH HHS / United States UM1 HG006493 / HG / NHGRI NIH HHS / United States |