ReQTL: Identifying correlations between expressed SNVs and gene expression using RNA-sequencing data
dc.contributor.author | Spurr, L | |
dc.contributor.author | Alomran, N | |
dc.contributor.author | Bousounis, P | |
dc.contributor.author | Reece-Stremtan, D | |
dc.contributor.author | Prashant, NM | |
dc.contributor.author | Liu, H | |
dc.contributor.author | Słowiński, P | |
dc.contributor.author | Li, M | |
dc.contributor.author | Zhang, Q | |
dc.contributor.author | Sein, J | |
dc.contributor.author | Asher, G | |
dc.contributor.author | Crandall, KA | |
dc.contributor.author | Tsaneva-Atanasova, K | |
dc.contributor.author | Horvath, A | |
dc.date.accessioned | 2019-10-28T15:33:14Z | |
dc.date.issued | 2019-10-07 | |
dc.description.abstract | 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, VAFRNA). VAFRNA 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 VAFRNA to gene expression, and assess its ability to identify genetically regulated expression solely from RNA-sequencing (RNA-seq) datasets.We introduce ReQTL, an eQTL modification which substitutes the DNA allele count for the variant allele fraction at expressed SNV loci in the transcriptome (VAFRNA). We exemplify the method on sets of RNA-seq data from human tissues obtained though the Genotype-Tissue Expression Project (GTEx) and demonstrate that ReQTL analyses are computationally feasible and can identify a subset of expressed eQTL loci.A toolkit to perform ReQTL analyses is available at https://github.com/HorvathLab/ReQTL.Re_QTL_Supplementary_Data.zip | en_GB |
dc.description.sponsorship | McCormick Genomic and Proteomic Center (MGPC), The George Washington University | en_GB |
dc.description.sponsorship | NIH National Center for Advancing Translational Science | en_GB |
dc.format.medium | btz750 | en_GB |
dc.identifier.doi | 10.1093/bioinformatics/btz750 | |
dc.identifier.grantnumber | MGPC_PG2018 | en_GB |
dc.identifier.grantnumber | UL1TR000075 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/39352 | |
dc.language.iso | en | en_GB |
dc.publisher | Oxford University Press (OUP) | en_GB |
dc.rights | © The Author(s) 2019. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. | en_GB |
dc.title | ReQTL: Identifying correlations between expressed SNVs and gene expression using RNA-sequencing data | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2019-10-28T15:33:14Z | |
dc.identifier.issn | 1367-4803 | |
dc.description | This is the author accepted manuscript. The final version is available on open access from OUP via the DOI in this record | en_GB |
dc.identifier.journal | Bioinformatics | en_GB |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2019-09-26 | |
rioxxterms.version | AM | en_GB |
rioxxterms.licenseref.startdate | 2019-10-07 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2019-10-26T12:11:08Z | |
refterms.versionFCD | AM | |
refterms.dateFOA | 2019-10-28T15:33:18Z | |
refterms.panel | B | en_GB |
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This is an Open Access article distributed under the terms of the Creative Commons Attribution License
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original work is properly cited.