Join GitHub today
GitHub is home to over 28 million developers working together to host and review code, manage projects, and build software together.Sign up
Fetching latest commit…
Cannot retrieve the latest commit at this time.
|Failed to load latest commit information.|
This is the readme for the py_emra package, developed in Python 2.7. To use on your system, copy the py_emra folder to the folder you are working in, or your library folders. Check your library paths with the following python commands: 'import sys','sys.path' py_emra is the Python module for Ensemble Modeling Robustness Analysis. For more information about the package and the algorithm, see the biorXiv paper here: http://biorxiv.org/content/early/2016/07/21/065177 You must have the following packages installed: +numpy +scipy +matplotlib +xlrd To install a convenient version of Python with these packages preloaded, check out Anaconda: https://www.continuum.io/downloads These are the functions contained. Access these functions by first writing 'import py_emra' in your python Script. +++ py_emra.Main.Main(Path,**kwargs) +++ This is the main function performing all the math, model construction, parameter sampling and integration. It ouputs results in a dictionary which can be saved and plotted. Arguments: Path = String of path to your model (r'C:\path\pathy\model.xls') **kwargs PertUp = 10.0 - magnitude of upward perturbation PertDown = 0.1 - magnitude of downward perturbation EnsembleSize = 100 Number of models to simulate RandFloor = 0.1 - minimum for enzyme parameter values RandCap = 10 - maximum for enzyme parameter values StepNo = 25 - number of integration steps. lower number of steps will not harm numerical integrity of results as integration is handled by a variable step-size but it will affect resolution of instability detection. fast = False - decreases accuracy and increases speed of integration if set to True Enzr=[All Enzymes] - list of enzyme indices to perturb Output: Dictionary containing resulting perturbation, metabolite, and +++ py_emra.stabplot.resultProc(Results,**kwargs) +++ The is the main results processing, plotting, and saving function. Will produce stability profiles and save results in csv format. Results = Results variable as from py_emra.Main.Main **kwargs Enzr = list of enzymes to plot & save save=True - whether or not to save a csv of results plot=True - whether or not to plot results +++Model format+++ +Currently py_emra supports .xls based models. The .xls should contain 'S','Enz','Met','Vref' & 'Rev' tabs. 'S'=Stoichiometric matrix of integers defining model network. 'Enz'=Column of enzyme names in same order as 'S' 'Met'=Column of metab names in same order as 'S' 'Vref'=Column of reference steady state enzyme fluxes defining a steady state for network defined in 'S' 'Rev'=Column of enzyme reversibilities (0 = irrev, 1 = reversibile). ***See Test.py for example of how the functions work together*** ***See Mcc.xls for example of model format.*** ***See MCC.png for example of EMRA stability plot.***