Fig. 1

Overview of the ideal workflow. 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. The optional gene annotation information can also be retrieved at runtime. The combination of a DESeqDataSet and a DESeqResults objects can be given as an alternate input. Package documentation includes tooltips, collapsible help elements, and instructions in the app. Together with the vignette as a detailed reference, the interactive tours guide users through the fundamental components in each step, coupled to the embedded demo dataset. 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)