Abstract
Motivation The association of splicing signatures with disease is a leading area of study for prognosis, diagnosis and therapy, frequently requiring detailed analysis of splicing events across multiple samples. We present a novel fast-performing annotation-dependent tool called SCANVIS for scoring and annotating splice junctions by gene name, junction type and any frame shifts incurred. SCANVIS has a novel and fast visualization technique that distinguishes annotated splice junctions from unannotated ones in the context of nearby variants and read coverage. It also allows users to merge samples across cohorts, thereby allowing for quick comparisons of splice junctions across diseases and tissue types.
Results We show that SCANVIS generates reasonable PSI scores by demonstrating that tissue/cancer types in GTEX and TCGA are well separated and easily predicted from a few thousand SJs. We also show how SCANVIS can be used to map out junctions overlaid with variants and read coverage for one or more samples, with line types and colors delineating frame shifts and junction types.
Availability SCANVIS is available for download at https://github.com/nygenome/SCANVIS
Contact pagius{at}nygenome.org