Paper Info
Title
ReQTL: Identifying correlations between expressed SNVs and gene expression using RNA-sequencing data.
Abstract
Motivation: By testing for associations between DNA genotypes and gene expression levels, expression quantitative trait locus (eQTL) analyses have been instrumental in understanding how thousands of single nucleotide variants (SNVs) may affect gene expression. As compared to DNA genotypes, RNA genetic variation represents a phenotypic trait that reflects the actual allele content of the studied system. RNA genetic variation at expressed SNV loci can be estimated using the proportion of alleles bearing the variant nucleotide (variant allele fraction, VAF(RNA)). VAF(RNA) is a continuous measure which allows for precise allele quantitation in loci where the RNA alleles do not scale with the genotype count. We describe a method to correlate VAF(RNA) with gene expression and assess its ability to identify genetically regulated expression solely from RNA-sequencing (RNA-seq) datasets. Results: We introduce ReQTL, an eQTL modification which substitutes the DNA allele count for the variant allele fraction at expressed SNV loci in the transcriptome (VAF(RNA)). We exemplify the method on sets of RNA-seq data from human tissues obtained though the Genotype-Tissue Expression (GTEx) project and demonstrate that ReQTL analyses are computationally feasible and can identify a subset of expressed eQTL loci.
Year
DOI
Venue
2020
10.1093/bioinformatics/btz750
BIOINFORMATICS
Field
DocType
Volume
RNA,Computer science,Gene expression,Bioinformatics,Computational biology
Journal
36
Issue
ISSN
Citations 
5
1367-4803
0
PageRank 
References 
Authors
0.34
0
14
Name
Order
Citations
PageRank
Liam Spurr100.68
Nawaf Alomran200.34
Pavlos Bousounis300.34
Dacian Reece-Stremtan400.34
N M Prashant500.34
Honguy Liu600.34
piotr slowinski741.46
Muzi Li800.34
Qianqian Zhang900.34
Justin Sein1000.34
Gabriel Asher1100.34
Keith Crandall129714.34
Krasimira Tsaneva-Atanasova1303.04
Anelia Horvath1411.05