confine

identifying disease module


License
BSD-3-Clause-No-Nuclear-License
Install
pip install confine==6.17

Documentation

License: SharmaLab - Channing Division of Network Medicine

To better use the package install "pip" and "python 2.7"

TO INSTALL: sudo pip install confine

PACKAGE REQUIREMENTS: The code can install all required packages for you.

  1. pickle
  2. networkx
  3. os
  4. time
  5. pylab
  6. pkg_resources

To INSTALL PACKAGES:

  1. call python
  2. import confine
  3. confine.check()

To TEST:

  1. call python
  2. import confine
  3. confine.run('test')

INPUT FORMAT: it should be either in csv or txt format. It includes 2 Comma-delimited columns in which the first column is reserved for gene id and the second is reserved for corresponding gene p.value.

OUTPUTS:

  1. a text file that includes gene id and gene symbol of LCC.
  2. a png file that shows how the significance of LCC varies with P.value cut-off over LCC thresholds given by user. directory: Outputs are being generated at directory where the user is running python

TO RUN:

  1. call python
  2. import confine
  3. confine.run('optional_name')
  4. Answer 1st question "Enter your file name located at INPUT folder: " path/filename
  5. Answer 2nd question Enter the minimum size of LCC, we recommend a number between 30 and 50: " 50
  6. Answer last question Enter the maximum size of LCC, we recommend a number between 300 and 500: " 400

TO ACCESS OUTPUT FILES: two output files are being generated in a directory that is names the same as 'optional_name' followed by a unique number.

GOAL: Identifying the most significant region of connections between disease-related proteins with a limited size by user.