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Updated: Nov 26, 2025

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ideal: an R/Bioconductor package for interactive differential expression analysis.

Federico Marini1,2, Jan Linke3,4, Harald Binder5

  • 1Center for Thrombosis and Hemostasis (CTH), University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstr. 1, 55131, Mainz, Germany. marinif@uni-mainz.de.

BMC Bioinformatics
|December 10, 2020
PubMed
Summary
This summary is machine-generated.

We developed ideal, a user-friendly R package for reproducible RNA sequencing (RNA-seq) analysis. This tool streamlines transcriptome profiling and generates visualizations for easier data interpretation.

Keywords:
BioconductorData visualizationDifferential expressionInteractive data analysisRRNA-SeqReproducible researchShinyTranscriptomicsWeb application

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • RNA sequencing (RNA-seq) is a vital tool for transcriptome profiling.
  • Existing bioinformatics tools lack comprehensive, accessible, and reproducible methods for RNA-seq analysis.
  • There is a need for user-friendly software that balances flexibility and transparency in RNA-seq data analysis.

Purpose of the Study:

  • To develop a software package for streamlined, interactive, and reproducible RNA sequencing analysis.
  • To provide researchers with an accessible tool for transcriptome profiling.
  • To enhance data interpretation through comprehensive visualizations.

Main Methods:

  • Developed 'ideal', an R package utilizing the Shiny framework for web application development.
  • Integrated 'ideal' with the Bioconductor project for seamless workflow execution.
  • Implemented assisted analysis steps for differential gene expression and functional analysis.

Main Results:

  • 'ideal' offers interactive and reproducible RNA-seq analysis via a web application.
  • The package generates a wide array of publication-ready visualizations for data interpretation.
  • Users can create comprehensive HTML reports with embedded code for enhanced reproducibility.

Conclusions:

  • 'ideal' is an R package available on Bioconductor, simplifying RNA-seq data analysis.
  • The tool empowers researchers across various profiles, including life scientists, clinicians, and bioinformaticians.
  • It facilitates optimal utilization of RNA-seq data through interactive and reproducible analysis.