Skip to content

redHUMAN: analyzing human metabolism and growth media through systematic reductions of thermodynamically curated genome-scale models

License

Notifications You must be signed in to change notification settings

EPFL-LCSB/redhuman

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

16 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

redHUMAN

Reduction of human genome-scale models. Paper: Maria Masid, Meriç Ataman and Vassily Hatzimanikatis. "redHUMAN: analyzing human metabolism and growth media through systematic reductions of thermodynamically curated genome-scale models"

Requirements

You will need to have Git LFS in order to properly download some binary files:

git clone https://github.com/EPFL-LCSB/redhuman.git /path/to/redhuman
cd /path/to/redhuman
git lfs install
git lfs pull

The scripts have been developed with Matlab 2017b, and CPLEX 12.7 (freely downloadable with the IBM Academic initiative), and successfully ran on several other versions of both softwares. However, it is important to respect the IBM compatibility specs sheets between Matlab, CPLEX, and the computer OS - available on IBM's website.

This module requires matTFA and redGEM.

Generating reduced models

  1. Place the corresponding thermodynamic data from the redhuman data folder into the matTFA thermoDatabases folder.
  2. Place the corresponding curated GEM from the redhuman GEMs folder into the redGEM GEMs folder.
  3. Place the corresponding get_redHUMAN file from the redhuman folder into the redGEM runFileExample folder.
  4. Modify the get_redHUMAN file to add the paths and the dessired parameters
  5. Run the get_redHUMAN file

Model validation

Run the scripts from the postprocessing folder to test the metabolic tasks, the gene essentiality analysis and the flux variability analysis as they are done for the paper.

License

The software in this repository is put under an APACHE licensing scheme - please see the LICENSE file for more details.

About

redHUMAN: analyzing human metabolism and growth media through systematic reductions of thermodynamically curated genome-scale models

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published