ideal – an R/Bioconductor package for Interactive Differential Expression Analysis

RNA-sequencing is nowadays the standard experimental approach for accurate transcriptome profiling. A key factor to help a wide range of researchers in making the best use of the available data is to provide software tools that are at the same time easy to use, but still provide flexibility and transparency in the adopted methods. Many packages focused on detecting differential expression are available (and compared in the companion website), yet a method to streamline this type of bioinformatics analysis in a comprehensive, accessible, and reproducible way is lacking.

Researchers at the University Medical Center in Mainz, developed the ideal software package, which serves as a web application for interactive and reproducible RNA-seq analysis to facilitate data interpretation (possibly one of the main bottlenecks in bulk RNA-seq data analysis). ideal is implemented in R using the Shiny framework, and is fully integrated with the existing core structures of the Bioconductor project. Users can perform the essential steps of the differential expression analysis workflow in an assisted way, and generate a broad spectrum of publication-ready outputs, including diagnostic and summary visualizations in each module, all the way down to functional analysis. ideal also offers the possibility to seamlessly generate a full HTML report for storing and sharing results together with code for reproducibility.

Overview of the ideal workflow

rna-seq

Top section: The typical analysis with ideal starts by providing the count matrix for the samples of interest, together with the corresponding experimental design information.  Middle section: The interactive session spans from the overview on the provided input, to the generation of differential expression analysis results and their visualization, while supporting downstream operations such as functional analysis, to assist in the interpretation of the data. Bottom section: All the generated output elements can be downloaded (images, tables), as well as exported in form of a R Markdown/HTML report, a document that guarantees reproducible analyses and can be readily shared or stored. (Icons contained in this figure are contained in the collections released by Font Awesome under the CC BY 4.0 license)

By providing a solution for performing interactive and reproducible analyses of summarized RNA-seq expression data, ideal empowers researchers with many different profiles (life scientists, clinicians, but also experienced bioinformaticians) to make the ideal use of the data at hand.

Availability – ideal is distributed as an R package in the Bioconductor project (http://bioconductor.org/packages/ideal/)

Marini F, Linke J, Binder H. (2020) ideal: an R/Bioconductor package for Interactive Differential Expression Analysis. bioR Xiv [Epub ahead of print]. [abstract]

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