Code to load and fit dose response curves in a Bayesian inference framework
Python C++ Matlab
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chaste Plot histograms of drug ranks using APD samples Nov 1, 2017
data Capped Crumb data Oct 17, 2017
distribution_analysis "Establish what the PDF and CDF look like" May 9, 2016
python Improved cma version checker using distutils May 31, 2018
.gitignore Should have runnable hierarchical and non-hierarchical MCMC scripts, … Oct 18, 2016
LICENSE Update LICENSE Oct 18, 2016 Update Aug 30, 2017

PyHillFit - python code to perform Bayesian inference of Hill curve parameters from dose-response data

Code to load dose-response data and fit dose Hill response curves in a Bayesian inference framework.

This code is associated with the paper "Hierarchical Bayesian inference for ion channel screening dose-response data". Wellcome Open Research 1:6. doi:10.12688/wellcomeopenres.9945.2.

Schematic of inputs and outputs

schematic of PyHillFit inputs and outputs


The following python packages are pre-requisites for running PyHillFit:

On most linux distributions you can install these via pip, which itself can be installed, if it isn't already present, following the instructions on the pip homepage.

Then all the above dependencies can be installed in one go with:

sudo pip install numpy cma matplotlib scipy pandas seaborn

Crumb dataset

We have made a .csv file of the Crumb et al. dataset, which is available in the data folder, together with some example python scripts for reading it. You can fit your own data by putting them into a similar format to this .csv file. Note that doses/concentrations should be given in microMolar.

Running PyHillFit

To run the python-based dose-response fitting code, see the README in the python folder.

Uncertainty Propagation

To run the Uncertainty Propagation example based on PyHillFit output, see the README in the chaste folder.