Glimma: interactive graphics for gene expression analysis.

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• Gene expression analyses using RNA-sequencing and microarrays generate large datasets with tens of thousands of data points.
• Dense summary plots can obscure critical details about specific genes or samples.
• Interactive visualizations are needed for on-demand information display and intuitive data exploration.

Purpose of the Study:

• To develop an open-source R package for creating interactive graphics for gene expression analysis.
• To enhance the exploration of complex biological data from RNA-sequencing and microarray experiments.
• To facilitate the sharing of reproducible results between bioinformaticians and biologists.

Main Methods:

• The Glimma R package was developed using D3/JavaScript to produce interactive HTML pages.
• Glimma extends existing plotting functions from the limma package, including multi-dimensional scaling and mean-difference plots.
• The package allows users to query individual data points and display additional annotation information upon interaction.

Main Results:

• Glimma provides interactive graphics for exploring gene expression data with simple R commands.
• Users can hover over or select data points to reveal detailed annotation information.
• The package supports popular Bioconductor workflows such as limma, edgeR, and DESeq2.
• Interactive displays enhance data exploration and reporting capabilities, improving reproducibility.

Conclusions:

• Glimma offers an effective solution for visualizing and exploring complex gene expression datasets.
• The interactive nature of Glimma graphics facilitates deeper data insights and better communication of results.
• The package promotes reproducibility and collaboration in bioinformatics and biological research.