macsima2mc 1.2.6

stages MACSima tiles for registration with ASHLAR in MCMICRO.

Staging module for Miltenyi - MACSIMA to MCMICRO

The macsima2mc.py script stages MACSima data sets for being registerd with ASHLAR in MCMICRO.

The script takes as main input the path to the cycle folder that cointains the raw tiles generated by the Miltenyi-MACSima platform. macsima2mc.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.

CLI

You can run macsima2mc by using the following command

macsima2mc -h

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'
-osd	string	--output_subdir	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
-rr	boolean flag	--remove_reference_marker	mark the removal of the reference marker ,e.g. DAPI, for all cycles except the first one	FALSE
-qc	boolean flag	--qc_metrics	measure features of contrast, intensity and sharpness of each tile in the cycle and appends them to a table	FALSE
-wt	boolean flag	--write_table	writes a table with the acquisition parameters, metadata and,if enabled, qc metrics of each tile. Table will be saved in --output/cycle_info	FALSE

Installation

pip install macsima2mc

Container usage

download container:

• Docker

docker pull ghcr.io/schapirolabor/macsima2mc:v1.1.1

• Singularity

singularity pull docker://ghcr.io/schapirolabor/macsima2mc:v1.1.1

Script execution

• Singularity

singularity exec --bind $path_to_your_local_cycle_folder:/mnt,$path_to_your_local_output_folder:/media --no-home $path_to_container python staging/macsima2mc/macsima2mc.py -i /mnt/$path_to_your_local_cycle_folder -o /media/$path_to_your_local_output_folder