MOTIVATION: The association of splicing signatures with disease is a leading area of study for prognosis, diagnosis and therapy. We present a novel fast-performing annotation-dependent tool called SCANVIS for scoring and annotating splice junctions (SJs), with an efficient visualization tool that highlights SJ details such as frame-shifts and annotation support for individual samples or a sample cohort. RESULTS: Using publicly available samples, we show that the tissue specificity inherent in splicing signatures is maintained with the Relative Read Support scoring method in SCANVIS, and we showcase some visualizations to demonstrate the usefulness of incorporating annotation details into sashimi plots. AVAILABILITY AND IMPLEMENTATION: https://github.com/nygenome/SCANVIS and https://bioconductor.org/packages/SCANVIS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
MOTIVATION: The association of splicing signatures with disease is a leading area of study for prognosis, diagnosis and therapy. We present a novel fast-performing annotation-dependent tool called SCANVIS for scoring and annotating splice junctions (SJs), with an efficient visualization tool that highlights SJ details such as frame-shifts and annotation support for individual samples or a sample cohort. RESULTS: Using publicly available samples, we show that the tissue specificity inherent in splicing signatures is maintained with the Relative Read Support scoring method in SCANVIS, and we showcase some visualizations to demonstrate the usefulness of incorporating annotation details into sashimi plots. AVAILABILITY AND IMPLEMENTATION: https://github.com/nygenome/SCANVIS and https://bioconductor.org/packages/SCANVIS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: Alexander Dobin; Carrie A Davis; Felix Schlesinger; Jorg Drenkow; Chris Zaleski; Sonali Jha; Philippe Batut; Mark Chaisson; Thomas R Gingeras Journal: Bioinformatics Date: 2012-10-25 Impact factor: 6.937
Authors: Yang I Li; David A Knowles; Jack Humphrey; Alvaro N Barbeira; Scott P Dickinson; Hae Kyung Im; Jonathan K Pritchard Journal: Nat Genet Date: 2017-12-11 Impact factor: 38.330