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myoquant

myoquant Analysis Command Line Interface

Usage:

$ myoquant [OPTIONS] COMMAND [ARGS]...

Options:

  • --version
  • --help: Show this message and exit.

Commands:

  • atp-analysis: Run the fibre type 1 vs type 2 analysis on...
  • docs: Generate documentation
  • he-analysis: Run the nuclei position analysis on HE and...
  • sdh-analysis: Run the mitochondiral analysis and...

myoquant atp-analysis

Run the fibre type 1 vs type 2 analysis on ATP images. First input arguments and option are printed in stdout and all modules are imported. Then the input image is mask with the binary mask if provided. Then depending on the presence of cellpose , Cellpose is run or not and mask accordingly if binary mask is provided. Finally the ATP analysis is run with run_atp_analysis() function and the results are saved in the output folder and some info are printed in stdout.

Usage:

$ myoquant atp-analysis [OPTIONS] IMAGE_PATH

Arguments:

  • IMAGE_PATH: The ATP image file path to analyse. [required]

Options:

  • --mask-path FILE: The path to a binary mask to hide slide region during analysis. It needs to be of the same resolution as input image and only pixel marked as 1 will be analyzed.
  • --cellpose-path FILE: The pre-computed CellPose mask to use for analysis. Will run Cellpose if no path provided. Required as an image file.
  • --output-path PATH: The path to the folder to save the results. Will save in the same folder as input image if not specified.
  • --intensity-threshold INTEGER RANGE: Fiber intensity threshold to differenciate between the two fiber types. If not specified, the analysis will try to deduce it. [1<=x<=254]
  • --cellpose-diameter INTEGER: Approximative single cell diameter in pixel for CellPose detection. If not specified, Cellpose will try to deduce it.
  • --channel INTEGER: Image channel to use for the analysis. If not specified, the analysis will be performed on all three channels.
  • --channel-first / --no-channel-first: If the channel is the first dimension of the image, set this to True. False by default. [default: no-channel-first]
  • --rescale-exposure / --no-rescale-exposure: Rescale the image exposure if your image is not in the 0 255 forma, False by default. [default: no-rescale-exposure]
  • --n-classes INTEGER RANGE: The number of classes of cell to detect. If not specified this is defaulted to two classes. [default: 2; x<=10]
  • --intensity-method TEXT: The method to use to compute the intensity of the cell. Can be either 'median' or 'mean'. [default: median]
  • --erosion INTEGER RANGE: Perform an erosion on the cells images to remove signal in the cell membrane (usefull for fluo). Expressed in percentage of the cell radius [default: False; x<=45]
  • --export-map / --no-export-map: Export the original image with cells painted by classification label. [default: export-map]
  • --export-stats / --no-export-stats: Export per fiber and per nuclei stat table. [default: export-stats]
  • --help: Show this message and exit.

myoquant docs

Generate documentation

Usage:

$ myoquant docs [OPTIONS] COMMAND [ARGS]...

Options:

  • --help: Show this message and exit.

Commands:

  • generate: Generate markdown version of usage...

myoquant docs generate

Generate markdown version of usage documentation

Usage:

$ myoquant docs generate [OPTIONS]

Options:

  • --name TEXT: The name of the CLI program to use in docs.
  • --output FILE: An output file to write docs to, like README.md.
  • --help: Show this message and exit.

myoquant he-analysis

Run the nuclei position analysis on HE and fluo images. First input arguments and option are printed in stdout and all modules are imported. Then the input image is mask with the binary mask if provided. Then depending on the presence of cellpose and stardist path, Cellpose and Stardist are run or not and mask accordingly if binary mask is provided. Finally the nuclei analysis is run with run_he_analysis() function and the results are saved in the output folder and some info are printed in stdout.

Usage:

$ myoquant he-analysis [OPTIONS] IMAGE_PATH

Arguments:

  • IMAGE_PATH: The HE image file path to analyse. If using single channel images, this will be used as cytoplasm image to run CellPose. Please use the --fluo-nuc option to indicate the path to the nuclei single image to run Stardist. [required]

Options:

  • --mask-path FILE: The path to a binary mask to hide slide region during analysis. It needs to be of the same resolution as input image and only pixel marked as 1 will be analyzed.
  • --cellpose-path FILE: The pre-computed CellPose mask to use for analysis. Will run Cellpose if no path provided. Required as an image file.
  • --stardist-path FILE: The pre-computed Stardist mask to use for analysis. Will run Stardist if no path provided. Required as an image file.
  • --output-path PATH: The path to the folder to save the results. Will save in the same folder as input image if not specified.
  • --cellpose-diameter INTEGER: Approximative single cell diameter in pixel for CellPose detection. If not specified, Cellpose will try to deduce it.
  • --nms-thresh FLOAT RANGE: NMS Threshold for Stardist nuclei detection. [default: 0.4; 0<=x<=1]
  • --prob-thresh FLOAT RANGE: Probability Threshold for Stardist nuclei detection. [default: 0.5; 0.5<=x<=1]
  • --eccentricity-thresh FLOAT RANGE: Eccentricity threshold value for a nucleus to be considered as internalized during nuclei classification. When very close to 1 almost all nuclei are considered as internalized. [default: 0.75; 0<=x<=1]
  • --export-map / --no-export-map: Export the original image with cells painted by classification label. [default: export-map]
  • --export-stats / --no-export-stats: Export per fiber and per nuclei stat table. [default: export-stats]
  • --fluo-nuc FILE: The path to single channel fluo image for nuclei.
  • --help: Show this message and exit.

myoquant sdh-analysis

Run the mitochondiral analysis and quantification on the image. First input arguments and option are printed in stdout and all modules are imported and latest SDH model is downloaded. Then the input image is mask with the binary mask if provided. Then depending on the presence of cellpose path, Cellpose is run or not and mask accordingly if binary mask is provided. Finally the mitochondiral classificaiton is run with run_sdh_analysis() function and the results are saved in the output folder and some info are printed in stdout.

Usage:

$ myoquant sdh-analysis [OPTIONS] IMAGE_PATH

Arguments:

  • IMAGE_PATH: The image file path to analyse. [required]

Options:

  • --mask-path FILE: The path to a binary mask to hide slide region during analysis. It needs to be of the same resolution as input image and only pixel marked as 1 will be analyzed.
  • --model-path FILE: The SDH model path to use for analysis. Will download latest one if no path provided.
  • --cellpose-path FILE: The pre-computed CellPose mask to use for analysis. Will run Cellpose if no path provided. Required as an image file.
  • --output-path PATH: The path to the folder to save the results. Will save in the current folder if not specified.
  • --cellpose-diameter INTEGER: Approximative single cell diameter in pixel for CellPose detection. If not specified, Cellpose will try to deduce it.
  • --export-map / --no-export-map: Export the original image with cells painted by classification label. [default: export-map]
  • --export-stats / --no-export-stats: Export per fiber stat table. [default: export-stats]
  • --help: Show this message and exit.