Authors : Nantia Leonidou
The pymCADRE tool is an advanced re-implementation of the metabolic Context-specificity Assessed by Deterministic Reaction Evaluation (mCADRE) algorithm in Python. It constructs tissue-specific metabolic models by leveraging gene expression data and literature-based evidence, along with network topology information.
The reactions within the generic global model are being ranked, and the ones with the lowest supporting evidence for the tissue of interest are given the highest priority for removal:
GM, C, NC, P, Z, model_C = rank_reactions(model, G, U, confidence_scores, C_H_genes, method)
If the generic functionality test is passed, the model undergoes pruning, which results in a context-specific reconstruction:
PM, cRes = prune_model(GM, P, C, Z, eta, precursorMets, salvage_check, C_H_genes, method)
pip install pymcadre
This tool has the following dependencies:
python 3.8
Packages:
- pandas
- numpy
- cobra
- requests
- os
model
: COBRA model structure for the metabolic model of interestprecursorMets
: list of precursor, key, metabolites in form of .txt fileconfidence_scores
: literature/experimental-based confidence assigned to reactions inmodel
Tissue-specific expression evidence:
G
: list of Entrez IDs for all genes inmodel
U
: list of ubiquity scores calculated for all genes inmodel
salvageCheck
: flag whether to perform a functional check for the nucleotide salvage pathway (1) or not (0)C_H_genes
: list with Entrez IDs for genes with particularly strong evidence of activity in the tissue of interestmethod
: method to use internal optimizations, (1) flux variability analysis or (2) fastcc
PM
: pruned COBRA tissue-specific modelGM
: COBRA model after removing blocked reactions from the input global modelC
: core reactions inGM
NC
: non-core reactions inGM
Z
: reactions with zero expression across all samples after binarizationmodel_C
: core reactions in the generic model (including blocked reactions)pruneTime
: total reaction pruning timecRes
: result of model checks (consistency/function) during pruning
To run pymCADRE, execute the notebook named main_pymcadre.ipynb or the python script named pymcadre.py. The scripts can be modified to the preferred parameters and input files. Jupyter notebooks with test runs and test scripts are also provided as reference points.