bioRxivBioinformaticsPreprint
RsQTL: correlation of expressed SNVs with splicing using RNA-sequencing data
Justin Sein, Liam Flinn SpurriD, Pavlos BousounisiD, N. M. PrashantiD, Hongyu LiuiD, Nawaf AlomraniD, Jimmy Bernot, Helen IbeawuchiiD, Dacian Reece-Stremtan, Anélia HorvathiD
Abstract
RsQTL is a tool for identification of splicing quantitative trait loci (sQTLs) from RNA-sequencing (RNA-seq) data by correlating the variant allele fraction at expressed SNV loci in the transcriptome (VAFRNA) with the proportion of molecules spanning local exon-exon junctions at loci with differential intron excision (percent spliced in, PSI). We exemplify the method on sets of RNA-seq data from human tissues obtained though the Genotype-Tissue Expression Project (GTEx). RsQTL does not require matched DNA and can identify a subset of expressed sQTL loci. Due to the dynamic nature of VAFRNA, RsQTL is applicable for the assessment of conditional and dynamic variation-splicing relationships. Availability and implementationhttps://github.com/HorvathLab/RsQTL. Contacthorvatha@gwu.edu or jsein@gwmail.gwu.edu Supplementary InformationRsQTL_Supplementary_Data.zip
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
- 1
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