ReQTL

ReQTL identifies correlations between expressed single nucleotide variants (SNVs) and gene expression levels from RNA sequencing (RNA-seq) data to detect RNA-level expression quantitative trait loci (eQTLs).

Key Features:

• Variant Allele Fraction (VAFRNA): ReQTL utilizes VAFRNA as a continuous measure to estimate RNA genetic variation at expressed SNV loci, quantifying allele content within the transcriptome.
• Correlation with Gene Expression: The method correlates VAFRNA with gene expression levels to assess genetically regulated expression directly from RNA-seq datasets.
• Computational Feasibility: ReQTL is designed for computational efficiency to enable large-scale analyses of extensive RNA-seq datasets such as the Genotype-Tissue Expression (GTEx) project.
• Input Preparation and MatrixEQTL Integration: The toolkit provides scripts to transform sequencing files into ReQTL-compatible input formats and to run the MatrixEQTL R package for identifying significant variation–expression relationships.

Scientific Applications:

• Understanding Genetic Regulation: Identifying expressed eQTL loci to elucidate how genetic variants influence gene expression at the RNA level in studies of complex traits and disease.
• Tissue-Specific Analysis: Application to human tissue datasets such as GTEx to explore tissue-specific genetic regulation of gene expression.

Methodology:

ReQTL substitutes DNA allele counts with VAFRNA at expressed SNV loci, correlates VAFRNA with gene expression, and uses scripts to prepare inputs and run the MatrixEQTL R package.