The impact of read depth and read length on RNA-seq splicing analysis

Abstract

Alternative splicing (AS) is a key layer of regulation in eukaryotic gene expression that is investigated in all areas of life sciences. Differences in AS between conditions can be quantified from transcriptome-wide short-read RNA sequencing (RNA-seq) data with designated computational tools. However, not all short-read RNA-seq data are equally suited for AS analysis. Here, we perform an exemplary AS analysis to showcase the impact of the RNA-seq library characteristics on the obtained results. Using two standard ENCODE data sets with widespread AS changes, we modulate read length and read depth and compare their influence on the detection, quantification, and classification of AS events with the state-of-the-art AS algorithm MAJIQ. We find that both longer reads and higher read depth are effective measures to improve the sensitivity and precision of the AS analysis. Our results provide valuable insights to help researchers make informed decisions when choosing the short-read RNA-seq library specifications for AS analysis.