The Statistics Seminar speaker for November 5, 2014 will be Rachael Hageman Blair, from the University at Buffalo.
Title: Belief Propagation in Genotype-Phenotype Networks
Abstract: Graphical models have proven to be a valuable tool for connecting genotypes and phenotypes. Structural learning of phenotype-genotype networks has received considerable attention in the post-genome era. In recent years, a dozen different methods have emerged for network inference, which leverage natural variation that arises in certain genetic populations. The structure of the network itself can be used to form hypotheses based on the inferred direct and indirect network relationships, but represents a premature endpoint to the graphical analyses. In this work, we extend this endpoint. We examine the unexplored problem of perturbing a given network structure, and quantifying the system-wide effects on the network in a node-wise manner. The perturbation is achieved through the setting of values of phenotype node(s), which may reflect an inhibition or activation, and propagating this information through the entire network. We leverage belief propagation methods in Conditional Gaussian Bayesian Networks (CG-BNs), in order to absorb and propagate phenotypic evidence through the network. The system-wide effects of the perturbation are quantified in a node-wise manner through the comparison of perturbed and unperturbed marginal distributions using a symmetric Kullback-Leibler divergence. The method was applied to kidney expression Quantitative Trait Loci (eQTL) data from a mus musculus population. System-wide effects in the network were predicted and visualized across a spectrum of evidence. Sub-pathways and regions of the network responded in concert, suggesting co-regulation and coordination throughout the network in response to phenotypic changes. Predictions of this type cannot be obtained through the examination of the network structure. A software package (gpBP), which implements our approach, was developed in the R programming language.
Refreshments will be served after the seminar in 1181 Comstock Hall.
Please note that this seminar will take place in 406 Malott Hall.