SpliceWiz: Interactive analysis and visualization of alternative splicing in R

Wong, Alex C.H., Wong, Justin J.-L., Rasko, John E.J., and Schmitz, Ulf (2023) SpliceWiz: Interactive analysis and visualization of alternative splicing in R. Briefings in Bioinformatics, 25 (1).

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Abstract

Alternative splicing (AS) is a crucial mechanism for regulating gene expression and isoform diversity in eukaryotes. However, the analysis and visualization of AS events from RNA sequencing data remains challenging. Most tools require a certain level of computer literacy and the available means of visualizing AS events, such as coverage and sashimi plots, have limitations and can be misleading. To address these issues, we present SpliceWiz, an R package with an interactive Shiny interface that allows easy and efficient AS analysis and visualization at scale. A novel normalization algorithm is implemented to aggregate splicing levels within sample groups, thereby allowing group differences in splicing levels to be accurately visualized. The tool also offers downstream gene ontology enrichment analysis, highlighting ASEs belonging to functional pathways of interest. SpliceWiz is optimized for speed and efficiency and introduces a new file format for coverage data storage that is more efficient than BigWig. Alignment files are processed orders of magnitude faster than other R-based AS analysis tools and on par with commandline tools. Overall, SpliceWiz streamlines AS analysis, enabling reliable identification of functionally relevant AS events for further characterization. SpliceWiz is a Bioconductor package and is also available on GitHub (https://github.com/alexchwong/SpliceWiz).

Item ID: 81205
Item Type: Article (Research - C1)
ISSN: 1477-4054
Copyright Information: © The Author(s) 2023. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Funders: National Health and Medical Research Council (NHMRC) Australia
Projects and Grants: NHMRC #2010647, NHMRC #1128175, NHMRC #1177305, NHMRC #1196405
Date Deposited: 01 Jan 2024 23:13
FoR Codes: 31 BIOLOGICAL SCIENCES > 3102 Bioinformatics and computational biology > 310201 Bioinformatic methods development @ 80%
49 MATHEMATICAL SCIENCES > 4905 Statistics > 490501 Applied statistics @ 20%
SEO Codes: 28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280103 Expanding knowledge in the biomedical and clinical sciences @ 50%
28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280102 Expanding knowledge in the biological sciences @ 50%
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