Bayesian analysis for heterosis detection in RNAseq data
Date and time:
Monday, December 7, 2015 - 2:00pm
An important type of heterosis, known as hybrid vigor, refers to the enhancements in the phenotype of hybrid progeny relative to their inbred parents. Although hybrid vigor is extensively utilized in agriculture, its molecular basis is still largely unknown. In an effort to understand phenotypic heterosis at the molecular level, researchers are measuring transcript abundance levels of thousands of genes in parental inbred lines and their hybrid offspring using RNA sequencing (RNA-seq) technology. We build a hierarchical negative binomial model and draw inferences using a computationally tractable empirical Bayes approach to inference. We demonstrate improvements over alternative methods via a simulation study based on a maize experiment and then analyze that maize experiment with our newly proposed methodology. In addition, we are currently developing a fully Bayesian approach utilizing Markov chain Monte Carlo implemented on general purpose graphical processing units to provide computational tractability for exploring the high dimensional posterior distribution.