Abstract
Understanding how genetic variation affects gene expression is essential for a complete picture of the functional pathways that give rise to complex traits. Although numerous studies have established that many genes are differentially expressed in distinct human tissues and cell types, no tools exist for identifying the genes whose expression is differentially regulated. Here we introduce DRAB (differential regulation analysis by bootstrapping), a gene-based method for testing whether patterns of genetic regulation are significantly different between tissues or other biological contexts. DRAB first leverages the elastic net to learn context-specific models of local genetic regulation and then applies a novel bootstrap-based model comparison test to check their equivalency. Unlike previous model comparison tests, our pro-posed approach can determine whether population-level models have equal predictive performance by accounting for the variability of feature selection and model training. We validated DRAB on mRNA expression data from a variety of human tissues in the Genotype-Tissue Expression (GTEx) Project. DRAB yielded biologically reasonable results and had sufficient power to detect genes with tissue-specific regulatory profiles while effectively controlling false positives. By providing a framework that facilitates the prioritization of differentially regulated genes, our study enables future discoveries on the genetic architecture of molecular phenotypes.
Original language | English (US) |
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Pages (from-to) | 1840-1857 |
Number of pages | 18 |
Journal | Annals of Applied Statistics |
Volume | 18 |
Issue number | 3 |
DOIs | |
State | Published - Sep 2024 |
Bibliographical note
Publisher Copyright:© Institute of Mathematical Statistics, 2024.
Keywords
- Differential regulation
- gene expression
- model selection test
- penalized regression
- transcriptome prediction