Year: 2019
Type: article
Abstract: The study of gene expression quantitative trait loci (eQTL) is an effective approach to illuminate the functional roles of genetic variants. Computational methods have been developed for eQTL mapping using gene expression data from microarray or RNA-seq technology. Application of these methods for eQTL mapping in tumor tissues is problematic because tumor tissues are composed of both tumor and infiltrating normal cells (e.g. immune cells) and eQTL effects may vary between tumor and infiltrating normal cells. To address this challenge, we have developed a new method for eQTL mapping using RNA-seq data from tumor samples. Our method separately estimates the eQTL effects in tumor and infiltrating normal cells using both total expression and allele-specific expression (ASE). We demonstrate that our method controls type I error rate and has higher power than some alternative approaches. We applied our method to study RNA-seq data from The Cancer Genome Atlas and illustrated the similarities and differences of eQTL effects in tumor and normal cells.
Authors: DouglasR. Wilson, JosephG. Ibrahim, Wei Sun
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: green
Awards: Estimation and association analysis of biomarkers for tumor immune microenvironment, Unlocking complex co-expression network using graphical models, Statistical Methods for Analysis of Tumor Heterogeneity in Genetic Epidemiology, Bayesian Approaches to Model Selection for Survival Data, Statistical Methods for RNA-seq Data Analysis, UNC Center for Environmental Health and Susceptibility
OpenAlex ID: W2950546499