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Python scripts for processing single molecule photobleaching data

Authors: Clark, Sarah; Elferich, Johannes;

Python scripts for processing single molecule photobleaching data

Abstract

These scripts are intended for processing single molecule photobleaching movies that have been acquired on a Leica DMi8 TIRF microscope. To use the scripts: 1. Copy both the BleachProcess.py and SessionState.py scripts into the folder that contains the photobleaching movies. 2. Install all required dependencies that are listed at the top of the BleachProcess script. 3. Open a terminal, navigate to the folder with movies and scripts, and start Streamlit with the command: streamlit run BleachProcess.py. An interactive window will open in your default internet browser. 4. Select the input file, series, and channel on the left. 5. To change the number of spots picked, change the 'H-height' and 'Exclude based on final H-height' parameters. View the image and spots by clicking on the "show image" button below the photobleaching trace. 6. To change the extraction radius of the spots that are picked, change 'Extraction radius' parameter. A larger extraction radius will result in a smoother trace. 7. When you are satisfied the the number of spots being picked, manually score each photobleaching trace based on the number of observed photobleaching steps. 8. Select the 'skip', '1 step', '2 step', etc. buttons at the top of the screen based on the number of photobleaching steps in the displayed trace. A new trace will appear when the button is selected and the number of each selection will be tallied above the trace window. 9. Selecting a new movie or refreshing the page will clear the tally and peak picking parameters. 10. For each trace, the X,Y coordinates are printed into the terminal window. This feature allows you to manually plot the trace in a graphing program of your choice

Keywords

Photobleaching, SiMPull, Single molecule pulldown, TIRF

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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