PatchView perform data analysis and visualization on multi channel whole-cell recording (multi-patch) data, including firing pattern analysis, event analysis, synaptic connection detection, morphological analysis and more.
- Free software: BSD 3-Clause license
- Documentation: https://patchview.readthedocs.io.
PatchView integrates multiple open-source tools (see credit page) and wrap them using an intuitive graphic user interface (GUI). Thus users can perform most analysis quickly for the data collected in a typical patch-clamp experiment without installing Python and these tools or writing any Python scripts.
- Importing both Heka data and Axon Instruments data (Both ABF1 and ABF2). Exporting to Python pickle file or NWB (Neurodata Without Borders) file format.
- Visualizing single and multiple traces with zoom, pan operations.
- Automatically sorting experiments data according to predefined labels.
- Performing analysis on intrinsic membrane properties, action potential detection, firing pattern analysis.
- Synaptic connection analysis.
- Visualizing and quantification of neuron's morphological reconstruction from Neurolucida
Download zip file from latest release. Unzip it, double click Patchview excutable file.
It is recommended to install Patchview in an virtual enviroment with Python3.10+. After activating your virtual environment, run this command in your terminal:
pip install git+https://github.com/ZeitgeberH/NeuroM@patchview#egg=NeuroM git+https://github.com/ZeitgeberH/dictdiffer#egg=dictdiffer git+https://github.com/jeremysanders/pyemf3#egg=pyemf3
pip --no-cache-dir install patchviewMore details or documentation for installation from source, please refer to the Installation page.
If you find our work useful for your research, please cite:
Hu et al., (2022). PatchView: A Python Package for Patch-clamp Data Analysis and Visualization. Journal of Open Source Software, 7(78), 4706, https://doi.org/10.21105/joss.04706