Skip to content

Segmentation and Annotation DataBase (interactive DNA copy number analysis using supervised machine learning)

License

Notifications You must be signed in to change notification settings

alanfwilliams/SegAnnDB

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

35d54d8 · May 29, 2018

History

78 Commits
May 8, 2018
May 13, 2018
Aug 4, 2016
May 13, 2018
Oct 22, 2015
May 13, 2018
Oct 22, 2015
Jan 27, 2017
Sep 6, 2017
May 25, 2018
Nov 19, 2015
Aug 4, 2016
Nov 18, 2015
Nov 18, 2015
Jan 27, 2017
May 29, 2016
May 29, 2016
May 29, 2016
May 29, 2016
May 29, 2016
May 29, 2016
May 29, 2016
May 29, 2016
Jan 27, 2017
Sep 6, 2017
May 29, 2016
May 29, 2016
Nov 18, 2015

Repository files navigation

https://travis-ci.org/tdhock/SegAnnDB.png?branch=master

SegAnnDB: supervised machine learning for interactive DNA copy number analysis

Background, usage

Background: please read our Bioinformatics 2014 paper.

Usage demos on YouTube:

Installation

See INSTALL.sh to install on your own server, or Abhishek’s blog post to use our docker image.

Testing

We use selenium webdriver for testing. To start the test suite, first install selenium using

pip install selenium=2.53.2

Then install Firefox, run recover-restart.sh, and then tests/tests.py.

If running tests on Travis, Google may think that the test account is being hacked and lock it, causing tests to fail. To work around this do the following:

  1. Login to Google from your computer using the test account (and log out all other google accounts).
  2. Open https://www.google.com/accounts/DisplayUnlockCaptcha and push the button on the page.
  3. Push code and/or restart the Travis build.

It is important to realize that this link provides unlimited access for 10 minutes only, so it is best to click it immediately prior to pushing code or running a build.

Scripts

About

Segmentation and Annotation DataBase (interactive DNA copy number analysis using supervised machine learning)

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 69.0%
  • JavaScript 20.3%
  • CSS 7.6%
  • R 1.9%
  • Shell 1.2%