Document Type
Conference Proceeding
Publication Date
2014
Abstract
Most association studies focus on disease risk, with less attention paid to disease progression or severity. These phenotypes require longitudinal data. This paper presents a new method for analyzing longitudinal data to map genes in both population-based and family-based studies. Using simulated systolic blood pressure measurements obtained from Genetic Analysis Workshop 18, we cluster the phenotype data into trajectory subgroups. We then use the Bayesian posterior probability of being in the high subgroup as a quantitative trait in an association analysis with genotype data. This method maintains high power (>80%) in locating genes known to affect the simulated phenotype for most specified significance levels (a). We believe that this method can be useful to aid in the discovery of genes that affect severity or progression of disease.
Recommended Citation
Musolf, A., Nato, A.Q., Londono, D., Zhou, L., Matise, T.C. and Gordon, D., 2014, June. Mapping genes with longitudinal phenotypes via Bayesian posterior probabilities. In BMC Proceedings (Vol. 8, No. 1, p. S81). BioMed Central.
Included in
Genetic Phenomena Commons, Genetic Processes Commons, Genetic Structures Commons, Medical Genetics Commons
Comments
The copy of record is available from the publisher at https://doi.org/10.1186/1753-6561-8-S1-S81. Copyright © 2014 Musolf et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http:// creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.