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Staging module for Akoya - CODEX to MCMICRO

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The codex2mc.py script stages CODEX data sets for being registered with ASHLAR in MCMICRO.

The script takes as main input the path to the cycle folder that cointains the raw tiles generated by the Akoya CODEX platform. codex2mc.py reads these tiles and distributes them into acquisition groups. i.e tiles with common rack, well, ROI and exposure levels will be written into an ome.tiff file with the necessary metadata for registration. To be more precise two such ome.tiff files will be generated per cycle, one corresponds to the background signal and the other to the markers signal.

Installation

We recommend installing codex2mc on a clean environment using Python=3.12 and pip. To install codex2mc run the following command:

pip install codex2mc

Usage

Display help message:

codex2mc -h

Display version:

codex2mc -v

CLI

Required arguments

Argument Long name Type Description Default value
-i string/path --input Absolute path to the the parent folder of the raw tiles, i.e. the cycle folder whose name follows the pattern X_Cycle_N,where N represents the cycle number NA
-o string/path --output Absolute path to the directory in which the outputs will be saved. If the output directory doesn't exist it will be created. NA

Optional arguments

Argument Type Long name Description Default value
-rm string --reference_marker Name of the reference marker for registration 'DAPI'
-od string --output_dir String specifying the name of the subfolder in which the staged images will be saved. 'raw'
-ic boolean flag --illumination_correction Give this flag to apply illumination correction to all tiles, the illumination profiles are calculated with basicpy FALSE
-he boolean flag --hi_exposure_only Give this flag to extract only the set of images with the highest exposure time FALSE

Container usage

download container:

  • Docker
docker pull ghcr.io/schapirolabor/multiplex_codex:v1.1.0
  • Singularity
singularity pull docker://ghcr.io/schapirolabor/multiplex_codex:v1.1.0

Script execution

  • Singularity
singularity exec --bind $path_to_your_local_cycle_folder:/mnt,$path_to_your_local_output_folder:/media --no-home $path_to_container python staging/codex2mc/codex2mc.py -i /mnt/$path_to_your_local_cycle_folder -o /media/$path_to_your_local_output_folder

Metadata

Release files for codex2mc 0.0.3

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Source distribution for codex2mc 0.0.3
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Table of built distributions (wheels) for codex2mc 0.0.3
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