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Extracting and analysing MERFISh tif images for better cellpose segmentation

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Dana162001/merfish_tif_analysis

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MERFISH images data analysis

Extracting and analysing MERFISH tif files into multiple channel images for better cellpose segmentation

Workflow

Better to create new conda env for this project

  1. Convert from original .dax to .tif file

Dependencies:

  • conda install -c conda-forge tifffile
  • conda install -c anaconda numpy
python dax_converter.py input/path/with/.das_and_.inf/files

(Optional) copy files from original dir to the smaller dir with copy_files.sh

  1. Extraction of 3 border staining + DAPI
python extract_tiff_images.py --i /input/dir/with/.tif/files --o output/empty/dir 
  1. Split 1 .tif into 4 different channels
python split_tif.py -i /input/dir/with/.tif/files/4_images -o output/empty/dir/for/splited/files 
  1. Add colors and merge together
python merged_tif.py -i /input/dir/with/splited/files -o output/empty/dir/for/merged/files 
  1. (Optional) add export annotation of masks into QuPath
  • For the annotation script to work one need to create a project in QuPath, then paste it in automate > script editor > runs script (delete empty lines, because otherwise it will get an error)
export_annotation.groovy

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Extracting and analysing MERFISh tif images for better cellpose segmentation

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