Degust

• Visualise RNA-seq differential expression data.
• Perform your own DGE analysis, or use the inbuilt server to analyse from your own "counts" file.

Access a public web service running Degust

View a short video of the interface in use.

Read a summary on the Degust home page.

Example Screenshots

FAQ

See FAQ.md

Installation

If you do not want to use the public Degust installation, you may install your own.

You first need to grab a copy of Degust.

    git clone [email protected]:Victorian-Bioinformatics-Consortium/degust.git

Degust can be installed in two ways:

1. Perform your own DGE analysis, and use only the web frontend from Degust
2. Install the frontend and back-end software to perform analysis and visualise the results.

Frontend installation only

To use the frontend visualisation, you will need to have done your own DGE analysis with a tool like edgeR or voom. You will need CSV file contain a line per gene, and the following columns:

• ID - containing a unique identifier for each gene (required)
• Adjusted p-value - The adjusted p-value (FDR or similar) for that gene (required)
• Log intensity for each condition - Used to compute the log fold-change (required)
• Average intensity across the conditions - Used for the MA-plot (required)
• Gene info - Arbitrary information columns to display in the gene list table (optional)
• Read counts - Read counts for each replicate, only used for display purposes (optional)

The simplest approach is to download degust.py then run it with your csv file as a parameter. This will create a single HTML page that you view or share. Run ``degust.py --help` to find the parameters to specify the column names for your CSV.

Full installation

See INSTALL.md

License

Degust is released under the GPL v3 (or later) license, see COPYING.txt