Genetic locus that affects gene expression is often referred to as expression quantitative trait locus (eQTL). eQTL mapping studies assesses the association of SNPs with genome-wide expression levels.
Based on the hg38 reference genome, paired-end reads were mapped by STAR aligner. The mapped reads were used for expression quantification without assembling transcripts (by counting the number of reads that map to an exon) by HTSeq that uses Refseq gene annotations. Then, to correct for systematic variability (such as library fragment size, sequence composition bias, and read depth) the raw counts were normalized as trimmed mean of M-values (TMM) through edgeR.
Beyond quantifying gene expression, the data generated by RNA-Seq facilitate the integration of expression data with genotyping data also known as expression quantitative trait loci (eQTLs) analysis. Matrix eQTL was used to efficiently test the associations by modeling the effect of genotype as additive linear.
Data analysis pipeline for RNA-Seq based eQTL mapping: