In this project we propose to develop statistical methods for the analysis of microarray and RNA-sequencing data for expression QTL mapping. Our project is designed to address a number of important methodological issues, with particular relevance to the forthcoming GTEx study. We propose to extend a Bayesian hierarchical model for cis-eQTL mapping to enable simultaneous mapping in multiple tissues, and to improve the use of external biological information. We also propose to develop methods to allow more sensitive detection of trans-acting eQTLs that are correlated with networks or modules of co-regulated genes. Finally, we aim to develop methods for estimating transcript abundances from RNA sequencing data, for use in QTL mapping.
The purpose of this project is to develop new tools for analyzing and interpreting eQTL (expression quantitative trait loci) studies. We will develop analytical tools for both microarray-based and RNA-sequence-based measurements of gene expression.
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