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Shian Su, Charity Law, Matthew Ritchie (Walter and Eliza Hall Institute, 1G Royal Parade, Parkville 3052 Australia)
RNA-sequencing is a popular technology for studying changes in gene expression across tens of thousands of transcripts simultaneously. To make exploration of gene expression data easier, we developed Glimma, an R package which generates interactive plots for gene expression analyses. Glimma plots connect the many layers of information in a single html page using d3.js. For example, a Glimma-style mean-difference plot, allows one to select a point from a display of summary statistics to reveal the sample-wise expression levels alongside the original plot. This feature enables researchers to interrogate the data more easily by allowing searches for genes or samples of interest and zooming for better resolution. Unlike the traditional multi-dimensional scaling (MDS) plot, Glimma’s MDS plot shows several dimensions and group combinations on the same page. Results from Glimma can be easily shared between bioinformaticians and biologists, enhancing reporting capabilities while maintaining reproducibility. Besides bulk RNA-sequencing data, Glimma can also handle data from microarray, single-cell RNA-sequencing and methylation experiments.