This package contains my implementation of the Matlab code for the method described in Wang et al., 2012(1). The method is designed to take a generic global metabolic reconstruction (e.g., Human Recon 1) plus a collection of tissue-specific gene expression evidence and produce a draft context-specific model for the selected tissue or cell type.
All code was tested in Matlab R2014a, but should be compatible with earlier versions of the software (at least back to 2011-2012). mcadre requires the following tools to be installed and added to the Matlab path:
- COBRA Toolbox: can be cloned from this GitHub repo
- fastFVA(2): available for download here
- fastcc(2): available for download as part of the FASTCORE package here
To run the mCADRE method, simply clone this repo and add the directory to your Matlab path. The script run_mcadre provides an example of how to call the main function mcadre. The command to run mcadre is structured as follows:
[PM, GM, C, NC, Z, model_C, pruneTime, cRes] = …
mcadre(model, G, U, confidenceScores, salvageCheck, C_H_genes, method);
2) The fastFVA and fastcc methods perform the same function, so only one is required; the fastFVA function uses the free glpk solver, which comes with the COBRA Toolbox, while fastcc uses the commercial cplex solver (available with an academic license).
For details on running mCADRE and on various input data and options, please refer to the Manual.md file under docs. Further information about the algorithm and published results can be found in the original paper referenced above.
Any errors or bugs with the code in this repository should be reported as issues on GitHub. Additional questions about using or further developing the method can be directed to the Nathan Price lab at the Institute for Systems Biology.
NOTE: no future releases or new features are planned for this package, so any users looking to modify the method are encouraged to fork this repo and do so on their own.