Investigation of the contribution of intracellular calcium to the rundown of the L-type calcium current
This repository contains all data, protocols, codes, and figure generating files used in this study.
- extract_data.py analyses the raw data, post-processes it, and outputs the ICaL extracted from the selected cells and the rundown rate
- helpers.py provides supporting functions used by extract_data.py
- extensions.py provides supporting functions used to analyse the results and generate figures
- regression.r runs a multi-linear regression on the rundown rate with three independent variables
- The raw_data directory has the raw data of the current measured by patch-clamp experiments
- The resources directory has files that are generated by extract_data.py and outputs of the ExtendedData.ipynb that are used as input for analysis of other results
- The output directory has the output from extract_data.py
- The figures directory has the files that generate all figures in the paper and their output
- Figure 1 is generated by figure1.py
- Figure 2 is generated by figure2.py
- Figure 4 is generated by figure4.py
- Figure 5 is generated by figure5.py
- Figures 6, 7, and 8 are genrated by figure6_7_8.py
- Figure 9 is generated by figure9.py
- Supporting material for the paper is provided at ExtendedData.ipynb
- run.py runs extract_data.py and all figure generating files in the figures directory
- Python The code requires Python (version 3.3+) and the Python dependencies
pandas
,scipy
, andstatsmodels
- The Python packages used in this project can be installed by running
pip install -r requirements.txt
in an environment withPython 3.9.5
- The Python packages used in this project can be installed by running
- R The linear regression requires R (version 4+)