SPLICE-q: a Python tool for genome-wide quantification of splicing efficiency

Abstract Background Introns are generally removed from primary transcripts to form mature RNA molecules in a post-transcriptional process called splicing. An efficient splicing of is an essential step gene expression and its misregulation related numerous human diseases. Thus, better understand the dynamics this perturbations that might be caused by aberrant transcript processing it important quantify efficiency. Results Here, we introduce SPLICE-q, fast user-friendly Python tool for genome-wide SPLIC ing E fficiency q uantification. It supports studies focusing on implications efficiency dynamics. SPLICE-q uses aligned reads strand-specific RNA-seq each intron individually allows user select different levels restrictiveness concerning introns’ overlap with other genomic elements such as exons genes. We applied globally assess excision yeast nascent RNA-seq. also show application using total patient-matched prostate cancer sample. Conclusions Our analyses illustrate suitable detect progressive increase throughout time course useful when comes understanding progression beyond mere levels. available at: https://github.com/vrmelo/SPLICE-q