DGE-Vis

• 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 DGE-Vis.

View a short video of the interface in use.

Example Screenshot

Installation

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

You first need to grab a copy of DGE-Vis.

    git clone [email protected]:Victorian-Bioinformatics-Consortium/dge-vis

DGE-Vis can be installed in two ways:

1. Perform your own DGE analysis, and use only the web frontend from DGE-Vis
2. Install the frontend and backend 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)
• 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)

You need to create a settings.js file to specify the columns of you CSV file. As an example, see the examples/basic-settings.js

Full installation

Requirements:

• GHC 6.12 or later
• Python
• CoffeeScript

It can be installed as an apache CGI site, or run in "dev" mode using a standalone python server. Here we describe how to run in "dev" mode.

Run tests locally

There are javascript tests which can be run locally. Ensure you have compiled the CoffeeScript:

coffee -c -o tests/js/js-build coffee
coffee -c -o tests/js/js-build tests/js

Then you can either run the tests in your browser (navigate to http://localhost:8000/)

(cd tests/js/ ; python -mSimpleHTTPServer)

Or, if you have phantomjs installed you can run the tests from the command line: ./test-js.sh

Known Issues

Heatmap

• will only compute clustering (and be useful) if fewer than 4000 points. Needs a faster algorithm
• Clustering algorithm is naive greedy N^2. So, not fast, and not a great clustering.

Documentation

• Installing the full backend is barely documented