The Risa R/Bioconductor package: integrative data analysis from experimental metadata and back again

Area of Science:

• Bioinformatics
• Computational Biology
• Data Science

Background:

• The ISA-Tab format addresses data silos and metadata tracking challenges in experimental research.
• Its growing popularity stems from its pragmatic approach to describing investigations, studies, and assays.
• Reproducible research and data reusability are critical goals in modern science.

Purpose of the Study:

• To introduce the Risa package, a novel R-based tool for seamless integration with the ISA-Tab format.
• To facilitate the processing and analysis of experimental data described using ISA-Tab.
• To enhance reproducible research by improving metadata handling and data provenance.

Main Methods:

• The Risa package parses ISA-Tab datasets into R objects for analysis.
• It supports augmenting metadata and interfacing with domain-specific R packages.
• Functionality includes saving augmented data back to ISA-Tab format.

Main Results:

• Risa bridges the gap between ISA-compliant metadata and R-based data analysis.
• Demonstrated use cases include mass spectrometry and DNA microarray data.
• The package enables annotation augmentation and suggests relevant R packages for data processing.

Conclusions:

• The Risa package is freely available as open-source software via Bioconductor.
• It aims to simplify experimental data processing and promote uniform data representation.
• Risa provides tools for enhanced traceability and provenance tracking in research.