ggDNAvis interactive suite instructions

‘ggplot2’-based tools for visualising DNA sequences and modifications

The ggDNAvis interactive suite provides a user-friendly interface for using the ggDNAvis R package. There are three core visualisation functions, which are accessed via the tabs along the top bar:

  • Visualising a single DNA/RNA sequence
  • Visualising multiple DNA/RNA sequences
  • Visualising modification (e.g. methylation) of multiple DNA sequences

Within each tab, the sequence/modification information to be visualised can be read from the input text boxes or via file upload. Once it has been read, a visualisation will be created with all the default parameters. Parameters can then be adjusted as desired from the list on the left-hand side. Note that menus and sub-menus can be opened by clicking the arrows to access the full array of settings.

Parameters can be exported to and restored from a JSON file from the “Restore settings” tab at the bottom of the sidebar. Note that this does not store uploaded file information, and will only store text input information if the checkbox to do so is selected.

Final images can be downloaded at full resolution from the “Download image” button at the bottom of the sidebar.

v0.3.2.9013

This software is freely available under the open MIT licence, but please make sure to cite the ggDNAvis paper when using in publications or presentations.

Please report any bugs, difficulties, or feature requests to the issues page.

These interactive tools provide most of the functionality of the full R package, and enable a level of reproducibility via the settings import/export options. However, using the full R package via re-runable scripts improves reproducibility, as well as enabling advanced usage such as annotating returned ggplot2 objects (see example of adding ggplot2 elements to visualisation). To get started with the code-based R package, read the documentation.

From an R session with ggDNAvis installed, a local version of this Shiny application can be launched via ggDNAvis_shinyapp().