Abstract

Local ancestry, defined as the genetic ancestry at a genomic location of an admixed individual, is widely used as a genetic marker in genetic association and evolutionary genetics studies. Many methods have been developed to infer the local ancestries in a set of unrelated individuals, a few of them have been extended to small nuclear families, but none can be applied to large (e.g. three-generation) pedigrees. In this study, we developed a method, FamANC, that can improve the accuracy of local ancestry inference in large pedigrees by: (1) using an existing algorithm to infer local ancestries for all individuals in a family, assuming (contrary to fact) they are unrelated, and (2) improving its accuracy by correcting inference errors using pedigree structure. Applied on African-American pedigrees from the Cleveland Family Study, FamANC was able to correct all identified Mendelian errors and most of double crossovers.

Details

Title
Local Ancestry Inference in Large Pedigrees
Author
Wang, Heming 1   VIAFID ORCID Logo  ; Sofer Tamar 2   VIAFID ORCID Logo  ; Zhang, Xiang 3 ; Elston, Robert C 4 ; Redline, Susan 5 ; Zhu, Xiaofeng 4 

1  Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital and Harvard Medical School, Boston, USA (GRID:grid.38142.3c) (ISNI:000000041936754X) ; Program in Medical and Population Genetics, Broad Institute, Cambridge, USA (GRID:grid.66859.34) ; Case Western Reserve University, Department of Population and Quantitative Health Sciences, Cleveland, USA (GRID:grid.67105.35) (ISNI:0000 0001 2164 3847) 
2  Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital and Harvard Medical School, Boston, USA (GRID:grid.38142.3c) (ISNI:000000041936754X) ; Program in Medical and Population Genetics, Broad Institute, Cambridge, USA (GRID:grid.66859.34) 
3  College of Information Sciences and Technology, Pennsylvania State University, University Park, USA (GRID:grid.29857.31) (ISNI:0000 0001 2097 4281) 
4  Case Western Reserve University, Department of Population and Quantitative Health Sciences, Cleveland, USA (GRID:grid.67105.35) (ISNI:0000 0001 2164 3847) 
5  Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital and Harvard Medical School, Boston, USA (GRID:grid.38142.3c) (ISNI:000000041936754X) ; Beth Israel Deaconess Medical Center, Department of Sleep Medicine, Boston, USA (GRID:grid.239395.7) (ISNI:0000 0000 9011 8547) 
Publication year
2020
Publication date
2020
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1038/s41598-019-57039-w
ProQuest document ID
2342456630
Copyright
This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.