Genotet: An Interactive Web-based Visual Exploration Framework to Support Validation of Gene Regulatory Networks
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Failed to load latest commit information.
dev
gulp
imgs
server
src
templates
test
.gitignore
.travis.yml
LICENSE
README.md
bower.json
doc.html
favicon.ico
gulpfile.js
mongo-init.js
package.json
progress.php
setup.sh
start.sh
uploadBatch.py

README.md

Genotet

Master Build Status Master Build Status

Development Build Status Development Build Status

An Interactive Web-based Visual Exploration Framework to Support Validation of Gene Regulatory Networks

Installation

Note: The installtion steps were verified on Ubuntu Desktop 14.04.

  • Install node.js, JRE, mongoDB on the server machine.

  • Clone the Genotet repository and serve it at {server_url/genotet}.

  • Install required packages for the web pages and the nodejs server.

    # at genotet/
    npm install
    # at genotet/
    cd server
    # now at genotet/server
    npm install
  • Create and edit a server configuration file to set the data paths. The file shall be located at genotet/server/config.

    mongoDatabase = genotet
    origin = {server_url}
    dataPath = .../genotet_data/data/
    bigWigToWigPath = .../genotet_data/bigWigToWig
    
  • Run the setup script. The script initializes the mongo database. Make sure mongod is running in the background. The script downloads the UCSC bigWigToWig tool. Note that the default version is for linux x86_64. If you are on a Mac or Windows machine, you need to change the downloading url in setup.sh.

    bash setup.sh
    
  • Run the server.

    bash start.sh
    

Python batch upload script (uploadBatch.py)

  • Modify line 14 to set the upload server url.
url = 'http://{genotet_server_url}'
  • Write a tsv file that describes the data file. Each line describes one data file as follows.
file_path data_name data_type description
  • Note that data_type must be one of "network", "binding", "expression" and "bed". Tokens are [tab] or [\t] seperated. White spaces are allowed in the file description.
  • Run the script with your username and tsv file.
python uploadBatch.py {username} {tsv_file_name}
  • Enter the account password and monitor the command line output. It should output 200 on success.