Statistical considerations for the analysis of massively parallel reporter assays data
Year: 2020
Type: article
Abstract: Noncoding DNA contains gene regulatory elements that alter gene expression, and the function of these elements can be modified by genetic variation. Massively parallel reporter assays (MPRA) enable high-throughput identification and characterization of functional genetic variants, but the statistical methods to identify allelic effects in MPRA data have not been fully developed. In this study, we demonstrate how the baseline allelic imbalance in MPRA libraries can produce biased results, and we propose a novel, nonparametric, adaptive testing method that is robust to this bias. We compare the performance of this method with other commonly used methods, and we demonstrate that our novel adaptive method controls Type I error in a wide range of scenarios while maintaining excellent power. We have implemented these tests along with routines for simulating MPRA data in the Analysis Toolset for MPRA (@MPRA), an R package for the design and analyses of MPRA experiments. It is publicly available at http://github.com/redaq/atMPRA.
Source: Genetic Epidemiology
DOI: 10.1002/gepi.22337
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: green
Awards: Functional Genomic Approaches to Dissect COPD GWAS Loci, Identifying Genetic Determinants of Severe, Early-Onset COPD, Identifying functional variants in COPD GWAS loci, Network-based Methods for Understanding Genetic Determinants and Epistasis in COPD, Genetic and Functional Dissection of a Cluster of COPD GWAS Signals on Chromosome 4q, Using Integrative Genomics To Identify and Characterize Emphysema-Associated eQTL, Metabolic Control of Stemness in lung epithelial progenitors by FAM13A, Genetics of Smoke-Altered LTA4H in COPD, Genetic and Genomic Characterization of the Occurrence and Progression of Interstitial Lung Abnormalities
OpenAlex ID: W3043502472