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Related Experiment Videos

An 'eFP-Seq Browser' for visualizing and exploring RNA sequencing data.

Alexander Sullivan1, Priyank K Purohit1, Nowlan H Freese2

  • 1Department of Cell and Systems Biology/CAGEF, University of Toronto, Toronto, ON, Canada.

The Plant Journal : for Cell and Molecular Biology
|July 28, 2019
PubMed
Summary

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This summary is machine-generated.

Researchers can now explore gene expression patterns more easily with the eFP-Seq Browser. This user-friendly tool visualizes RNA sequencing (RNA-seq) data, aiding in understanding gene function and identifying alternative splicing events.

Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Next-generation sequencing has reduced costs, leading to widespread use of RNA sequencing (RNA-seq) for transcriptomic analysis.
  • Analyzing global gene expression patterns helps understand organismal biology and gene function.
  • Existing tools for large RNA-seq datasets aid analysis and hypothesis generation.

Purpose of the Study:

  • To present a user-friendly tool, the eFP-Seq Browser, for exploring RNA sequencing data.
  • To provide visualization of gene expression levels and read map coverage.
  • To facilitate the identification of alternative splicing events.

Main Methods:

  • Development of the eFP-Seq Browser, a web-based tool for RNA-seq data exploration.
  • Integration of 'electronic fluorescent pictographic' (eFP) images for expression visualization.
Keywords:
Arabidopsis thalianaRNA processingRNA-seqdata visualizationplant growthtemperature stress

Related Experiment Videos

  • Automated computation of expression summaries (RPKM) and correlation scores for sample sorting.
  • Linking to the Integrated Genome Browser for detailed alignment visualization.

    • Main Results:

    • The eFP-Seq Browser displays gene read map coverage and eFP images for visual representation of expression.
    • The tool automatically computes RPKM and point biserial correlation scores to sort samples.
    • Case studies demonstrate the tool's utility in examining expression levels and identifying alternative splicing for specific genes (ABI3, SR34, SR45a, U2AF65B).

    Conclusions:

    • The eFP-Seq Browser is an effective tool for exploring RNA-seq data, aiding in gene expression analysis and alternative splicing identification.
    • The tool enhances biological understanding by providing accessible visualizations and data summaries.
    • Open access to data and code supports reproducibility and further research.