https://github.com/arjunrajlaboratory/process_incucyte_tiff_data
https://github.com/arjunrajlaboratory/process_incucyte_tiff_data
Science Score: 13.0%
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Repository
Basic Info
- Host: GitHub
- Owner: arjunrajlaboratory
- License: apache-2.0
- Language: Python
- Default Branch: main
- Size: 18.6 KB
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- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 3
- Releases: 0
Metadata Files
README.md
processincucytetiff_data
This is a Python package for processing TIFF images generated by the Incucyte imaging system. The script processes TIFF files nested in folders within the input directory and saves the processed images with modified filenames in the output directory.
Input Directory Structure Example:
OriginalData/
│
├── phase/
│ ├── VID1630_C4_1_01d23h34m.tif
│ ├── VID1630_C4_1_00d23h56m.tif
│ ├── VID1630_C4_1_00d00h00m.tif
│ ├── ...
│
├── red/
│ ├── VID1630_C4_1_01d23h34m.tif
│ ├── VID1630_C4_1_00d23h56m.tif
│ ├── VID1630_C4_1_00d00h00m.tif
│ ├── ...
│
└── gfp/
├── VID1630_C4_1_01d23h34m.tif
├── VID1630_C4_1_00d23h56m.tif
├── VID1630_C4_1_00d00h00m.tif
└── ...
Expected Output Directory Structure:
fixed_files/
│
├── phase_VID1630_C4_1_01d23h34m.tif
├── phase_VID1630_C4_1_00d23h56m.tif
├── phase_VID1630_C4_1_00d00h00m.tif
├── ...
├── red_VID1630_C4_1_01d23h34m.tif
├── red_VID1630_C4_1_00d23h56m.tif
├── red_VID1630_C4_1_00d00h00m.tif
├── ...
├── gfp_VID1630_C4_1_01d23h34m.tif
├── gfp_VID1630_C4_1_00d23h56m.tif
└── gfp_VID1630_C4_1_00d00h00m.tif
...
For each TIFF file in the input directory, the script takes the folder name, removes any underscores, appends it to the filename with an underscore, and then saves it to the output directory.
Installation
Navigate to the repository directory and run the following command:
bash
pip install .
Usage
After installation, you can use the command-line interface to process your TIFF images. Here are the available options:
``` usage: process-incucyte-tiff-data [-h] [-i INPUT_DIRECTORY] [-o OUTPUTDIRECTORY] [-t THRESHOLD] [-r] [-rd REGISTRATIONDIRECTORY]
Process Incucyte TIFF data.
optional arguments:
-h, --help show this help message and exit
-i INPUTDIRECTORY, --input-directory INPUTDIRECTORY
Input directory (default: current working directory)
-o OUTPUTDIRECTORY, --output-directory OUTPUTDIRECTORY
Output directory (default: ./fixedfiles)
-t THRESHOLD, --threshold THRESHOLD
Threshold value (default: 65000)
-r, --register Enable registration of images using transformation matrices
-rd REGISTRATIONDIRECTORY, --registration-directory REGISTRATION_DIRECTORY
Directory within the input directory to use for calculating registration matrices (default: "phase")
``
Theinput-directoryparameter is used to specify the directory where your folders with TIFF files are located. Theoutput-directoryparameter is used to specify the directory where you want to save the processed TIFF files. Thethreshold` parameter is used to specify the value above which pixel values in the 16-bit images will be set to 0.
- The -r flag enables the registration of images. This will first compute transformation matrices from images in a specified subdirectory (default "phase") and then apply these matrices to all images during processing.
- The -rd option allows you to specify which subdirectory within the input-directory to use for calculating the registration matrices. The default is "phase". Note that it uses the middle section of the phase image for registration. In practice, it works... okay.
For example, to process TIFF files in the folder /path/to/tiff/files, and save the processed files to /path/to/fixed/files with a threshold value of 40000, you would run:
bash
process-incucyte-tiff-data -i /path/to/tiff/files -o /path/to/fixed/files -t 40000
If you don't specify any parameters, the script will use the current working directory as the input directory, ./fixed_files as the output directory, and 65000 as the threshold value.
Owner
- Name: Arjun Raj's systems biology lab
- Login: arjunrajlaboratory
- Kind: organization
- Repositories: 40
- Profile: https://github.com/arjunrajlaboratory
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