ApPredict - Action Potential Prediction project
ApPredict is a free open source program for prediction of action potential changes under drug-block of ion channels. The ion channel block is modelled as conductance block, and it can be used with a number of action potential models (specified using CellML), different pacing rates, and blockade of the following ion channels can be included: IKr (hERG), IKs (KCNQ1), ICaL (CaV1.2), INa (NaV1.5), Ito (Kv4.3), IK1 (KCNN4).
If you have any questions/comments, please get in touch with email@example.com.
A web-based portal interface to this program is now available: https://chaste.cs.ox.ac.uk/ActionPotential/ (feedback welcome), if you use this you can ignore all the instructions below - it's all set up for you!
For an overview of what ApPredict is doing, why, and how well it is performing, please see the user guide which is hosted on Figshare and the ApPredict paper (also linked to from https://chaste.cs.ox.ac.uk/ActionPotential/about).
N.B. you don't need to do any of the below to use the web portal version of ApPredict.
Code User: Stable Release Version
A stable version of ApPredict, compatible with the latest release of Chaste, is available either to download, or as a tag within github.
Option 1: Download
- the latest release of Chaste from https://www.cs.ox.ac.uk/chaste/downloads, and
- the corresponding release of ApPredict from https://github.com/Chaste/ApPredict/releases.
Option 2: Get from Github
To get both the release of Chaste and ApPredict do:
git clone https://chaste.cs.ox.ac.uk/git/chaste.git Chaste cd Chaste git checkout tags/release_3.4 cd projects git clone --recursive https://github.com/Chaste/ApPredict.git cd ApPredict git checkout tags/release_3.4
Code Developer: Development Version
Alternatively the development version can be downloaded using subversion, using the following instructions.
git clone -b develop https://chaste.cs.ox.ac.uk/git/chaste.git Chaste
(as per ChasteGuides/AccessCodeRepository)
If you are not using the InstallGuides/UbuntuPackage then the hostconfig settings in Chaste/python/hostconfig will need to be updated to give the correct paths to all of Chaste's dependencies.
then similarly in the same folder
git clone --recursive https://github.com/Chaste/ApPredict.git cd Chaste/projects ln -s ../../ApPredict cd ..
The project can be kept up to date by simply navigating to the Chaste folder and running
git pull cd projects/ApPredict git pull
The page ChasteGuides/ExternalDeveloperGuide provides a guide as to the latest revision that passed all tests.
scons cl=1 b=GccOptNative exe=1 projects/ApPredict/apps/src
The executable will then display a list of command line arguments.
(N.B. you may have to add Chaste libraries under the Chaste libs folder to your LD_LIBRARY_PATH variable, along with some other dependencies, e.g. libpetsc.so. One way to find out what these should be is to run scons cl=1 b=GccOptNative exe=1 offline_mode=1 projects/ApPredict/apps/src, which will create a supercomputer script called run-tests.sh in the Chaste source folder that contains the correct LD_LIBRARY_PATH at the bottom when you open it.)
- Nov 2016 - the code has moved to a github repository
- In 2361a19 downsampling was improved to provide nicer visual plots.
- Feb 2016 - Release 3.4 of ApPredict is available to download. Important changes since the Release 3.3 version of ApPredict are listed here:
- In r25668:
- New command line arguments have been added that allow the 'saturation level' of a dose response curve to be specified with options like --saturation-herg or --saturation-na etc.. The value(s) that follow are given as percentages, where 0% is the default (full block of the ion channel), 50% would mean an infinite amount of drug can only halve the conductance. Additionally, this allows agonists (activators) to be modelled by specifying saturation levels above 100% (in which case the IC50 is really an EC50, but interface still says IC50).
- As of r24408: A number of additional options to:
- Allow any CellML model to be used (when tagged with Chaste metadata - all the ones included in ApPredict/src/cellml are ready to use).
- Allow the downsampling associated with voltage traces to be switched off (it is on as default to make online plotting fast).
- Allow the stimulus current properties to be changed.
- The new flags for these options can be seen by running the executable with no arguments.
- In r25668: