Gaussian graphical models for phenotypes using pedigree data and exploratory analysis using networks with genetic and nongenetic factors based on Genetic Analysis Workshop 18 data.

ABSTRACT: Graphical models are increasingly used in genetic analyses to take into account the complex relationships between genetic and nongenetic factors influencing the phenotypes. We propose a model for determining the network structure of quantitative traits while accounting for the correlated nature of the family-based samples using the kinship coefficient. The Gaussian graphical model of age, systolic blood pressure, diastolic blood pressure, hypertension, blood pressure medication use, and smoking status was derived for three time points using real data. We also explored binary sparse graphical models of single-nucleotide polymorphisms (SNPs), covariates, and quantitative traits for exploratory analysis of the data. We validated the applicability of this method by producing a network graph us

SUBMITTER: Talluri R 

PROVIDER: S-EPMC4143694 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature