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.

Public Health Relevance

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.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Research Project (R01)
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Special Emphasis Panel (ZRG1-GGG-A (52))
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Bender, Patrick
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University of Chicago
Schools of Medicine
United States
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Zhang, Mingfeng; Lykke-Andersen, Soren; Zhu, Bin et al. (2018) Characterising cis-regulatory variation in the transcriptome of histologically normal and tumour-derived pancreatic tissues. Gut 67:521-533
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