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Alternative RNA Splicing02:18

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Identification of Alternative Splicing and Polyadenylation in RNA-seq Data
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SpliceWiz: interactive analysis and visualization of alternative splicing in R.

Alex C H Wong1,2,3, Justin J-L Wong2,3, John E J Rasko1,3,4

  • 1Gene and Stem Cell Therapy Program, Centenary Institute, the University of Sydney, Camperdown, NSW 2050, Australia.

Briefings in Bioinformatics
|December 28, 2023
PubMed
Summary
This summary is machine-generated.

SpliceWiz simplifies alternative splicing (AS) analysis from RNA sequencing data. This R package offers efficient visualization and identification of AS events, making complex data accessible for researchers.

Keywords:
data visualizationdifferential splicingexon usagegene isoformsintron retentionread coverage

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Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Alternative splicing (AS) generates diverse gene isoforms, crucial for eukaryotic gene expression regulation.
  • Analyzing and visualizing AS events from RNA sequencing (RNA-Seq) data presents significant computational challenges.
  • Existing visualization methods like sashimi plots have limitations and can be misleading, requiring specialized bioinformatics skills.

Purpose of the Study:

  • To develop an accessible and efficient tool for analyzing and visualizing alternative splicing events from RNA-Seq data.
  • To address the limitations of current AS analysis tools by providing an interactive and scalable solution.
  • To enable reliable identification and functional characterization of alternative splicing events.

Main Methods:

  • Development of SpliceWiz, an R package featuring an interactive Shiny interface for AS analysis.
  • Implementation of a novel normalization algorithm for accurate visualization of splicing level differences between sample groups.
  • Introduction of an efficient file format for coverage data storage, outperforming BigWig.
  • Optimization for speed, achieving processing times comparable to command-line tools.

Main Results:

  • SpliceWiz enables easy and efficient large-scale analysis and visualization of AS events.
  • The novel normalization algorithm accurately visualizes group-wise splicing level differences.
  • The tool integrates downstream gene ontology enrichment analysis for functional pathway identification.
  • SpliceWiz significantly accelerates alignment file processing compared to other R-based tools.

Conclusions:

  • SpliceWiz streamlines the process of alternative splicing analysis, enhancing accessibility for researchers.
  • The package provides reliable identification of functionally relevant AS events.
  • SpliceWiz is available as a Bioconductor package and on GitHub, promoting widespread adoption.