Here you will find a series of scripts and functions used to analyse the bulk of the electrophysiology data present in Antinucci, Dumitrescu et al 2020. Each script has an indepth README at the begining comprising a full description of the process of data extraction and analysis.
As an overview the following figures (both main and supplemental) from the paper contain data extracted with:
Fig 4: Gapfree_AP_stim & Excitatory_Opsin_Voltage_Clamp
Fig 5: Excitatory_Opsin_Current_Clamp and Excitatory_Opsin_Current_Clamp_Frequency
Fig 8: Inhibitory_Opsin_Voltage_Clamp
Fig 9: Inhibitory_Opsin_Current_Clamp, Inhibitory_Opsin_CC_Short_AP_Inhibit, Inhibitory_Opsin_CC_Long_AP_Inhibit
Due to script and path dependencies it is important to maintain the current folder nomenclature and organisation.
All the scripts except Gapfree_AP_stim are dependant on the functions: exponentialFitGetTau & exponentialFitGetTauInhibitory (details within scripts) and the 2 excel files Rig_1_LED_power & Rig_2_LED_power. For this reason these 4 files need to be in same location as the python analysis scripts.
The Sample_data folder contains several .abf files that can be used to test every script. The details of each .abf file and which script it can be used with are in the Sample_data_info excel sheet.
The Analysis_output folder contains the data extracted organised per script type. For the analysis to run correctly, this folder also needs to be present in the same location as the .py files
The current scripts were run with Python 3.6.6 in Spyder 3.6 and are dependant on several additional packages which need to be present. Please install them using your favourite method (pip, anaconda etc) if they are not already part of your instalation:
numpy 1.16.2 https://numpy.org
matplotlib 3.0.2 https://matplotlib.org
seaborn 0.9.0 https://seaborn.pydata.org
pyabf 2.1.6 https://pypi.org/project/pyabf/
pandas 0.24.1 https://pandas.pydata.org
scipy 1.3.0 https://www.scipy.org
Open the Sample_data_info excel sheet which is in the Sample_data folder and select one trace for analysis. For example let's assume we want to analyse the trace 18n270027_1. Reading the info sheet we can see that it should be analysed with the script: Excitatory_Opsin_Voltage_Clamp.py
If you run Excitatory_Opsin_Voltage_Clamp.py you will get some prompts that you need to respond to as part of the analysis. The information that matches each .abf file is in the Sample_data_info excel sheet.
For trace 18n270027_1 analysed with Excitatory_Opsin_Voltage_Clamp.py you will first have to provide the full file path where the data is located. Paste in the python console the full path where trace 18n270027_1 is located.
Next you will be asked to provide the ID of the rig used to collect data. For this trace enter 2.
Next you will be able to select which opsin was tested. Enter the number associated with Chrimson.
Next you will be able to select which wavelenght was used to stimulate cell. Enter the number associated with 630nm.
Finally you will be asked to select the irradiance max range used to stimulate cell. Enter the number associated with option LED_630_100%.
The data will be extracted, colated and you will also see a figure produced with key data once the script has finished running.
Open Analysis_output folder and check that (1) the VC_excitatory_opsin_master.csv file has one new row containing your newly extracted data and (2) open Single_Trace_data/VC_excitatory folder and check that a .csv file named after your trace is present.
To check that the analysis was run correctly you can open either the single or the master file containing the extracted data and check that the value of the 1st LED stimulation performed in trace 18n270027_1 is 7.44 mW/mm2 and that it resulted in a photocurrent response with a max amplitude of 223.234 pA etc.
If you have problems running the example scripts with the example .abf files provided or you spot any mistakes please get in touch at adna.siana@gmail.com