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Computational Analysis of Alternative Splicing Using VAST-TOOLS and the VastDB Framework.

André Gohr1, Federica Mantica1, Antonio Hermoso-Pulido1

  • 1Centre for Genomic Regulation, Barcelona Institute of Science and Technology, Barcelona, Spain.

Methods in Molecular Biology (Clifton, N.J.)
|July 27, 2022
PubMed
Summary

The VastDB framework aids researchers in studying alternative splicing (AS) by providing computational tools to quantify AS events and analyze their regulation and conservation. This resource simplifies complex analyses for identifying biologically significant AS events.

Keywords:
Alternative splicingBioinformaticsCassette exonsDatabaseIntron retentionOrthology

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Area of Science:

  • Genomics
  • Computational Biology
  • Molecular Biology

Background:

  • Alternative splicing (AS) significantly expands the transcriptome and proteome diversity in animals.
  • Key challenges in AS research include understanding its regulation across different cell types and diseases, and elucidating the functional roles of various AS events.

Purpose of the Study:

  • To introduce the VastDB computational framework, designed to facilitate alternative splicing research.
  • To provide accessible tools for biomedical researchers, particularly those without extensive computational expertise.

Main Methods:

  • Development of the VastDB framework, integrating multiple complementary software and resources.
  • Utilizing vast-tools for quantifying AS and identifying differential splicing from RNA-seq data.
  • Employing Matt for genomic and sequence analyses, ExOrthist for conservation studies, and VastDB/PastDB for biological interpretation and experiment design.

Main Results:

  • VastDB offers a comprehensive suite of tools for analyzing alternative splicing.
  • The framework enables quantification, differential splicing analysis, genomic/sequence analysis, and conservation studies of AS events.
  • Tools are designed for ease of use by biomedical researchers to aid in identifying AS events for wet-lab validation.

Conclusions:

  • The VastDB framework significantly lowers the barrier for conducting sophisticated alternative splicing research.
  • It empowers researchers to explore AS regulation, function, and conservation more effectively.
  • VastDB facilitates the translation of computational findings into experimental validation for AS events.