Document Type
Conference Proceeding
Publication Date
2016
Abstract
Background: Estimating relationships among subjects in a sample, within family structures or caused by population substructure, is complicated in admixed populations. Inaccurate allele frequencies can bias both kinship estimates and tests for association between subjects and a phenotype. We analyzed the simulated and real family data from Genetic Analysis Workshop 19, and were aware of the simulation model.
Results: We found that kinship estimation is more accurate when marker data include common variants whose frequencies are less variable across populations. Estimates of heritability and association vary with age for longitudinally measured traits. Accounting for local ancestry identified different true associations than those identified by a traditional approach. Principal components aid kinship estimation and tests for association, but their utility is influenced by the frequency of the markers used to generate them.
Conclusions: Admixed families can provide a powerful resource for detecting disease loci, as well as analytical challenges. Allele frequencies, although difficult to adequately estimate in admixed populations, have a strong impact on the estimation of kinship, ancestry, and association with phenotypes. Approaches that acknowledge population structure in admixed families outperform those which ignore it.
Recommended Citation
Blue EM, Brown LA, Conomos MP, et al. Estimating relationships between phenotypes and subjects drawn from admixed families. BMC Proceedings. 2016;10(Suppl 7):357-362. doi:10.1186/s12919-016-0056-3.
Included in
Genetic Phenomena Commons, Genetic Processes Commons, Genetic Structures Commons, Medical Genetics Commons
Comments
This conference paper was originally delivered at the Genetic Analysis Workshop 19, Vienna, Austria. 24-26 August 2014. The copy of record is available from the publisher at https://doi.org/10.1186/s12919-016-0056-3. Copyright © The Author(s). 2016. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.