• rename "wrap.sh" - more informative name (confoc_metrics or ...)
• use command line arguments for each of the pepeline modules and make them comprehensible (AND add description) specify the folder with the pictures of the hierarchy: .. script mkdir's an confoc_output_specified_folder folder puts the things from the specified folder in the raw folder inside the above mentiopned one and the rest of analysis folders, too
• how to make it a whole? (Fiji problematic)
• make the scripts check for each channel and only analyse those that are existent, printing into a log file which channel is which? OR dummy channels (better: results in consistent naming of columns in output)
• make install / uninstall scripts

The script takes .lsm confocal microscopy images as an input. It allows for the quantification of dyes and of the colocalised region of two of them. Also counts the cells and returns the mean per cell value for the dye intesity. Run wrap.sh with the full path to the directory with ImageJ and the directory named "input"

Make sure the channels of your .lsm picture are in follwing order: 1 - red, 2 - green, 3 - blue. Make sure there is a directory 'raw' in the dir passed as an arg to wrap Please put all the pictures in the "raw" folder according to the scheme: "raw/date/staining/treatment/cell.line/treatment.or.control/image.name.lsm" ?

To use a certain step in pipeline, comment/uncomment wrap.sh lines near the end. Can give it a -swap_channels option Example: ./wrap.sh /mnt/DATAPART1/Sasi --swap-channels

"exploratory.R" is a mess. Not pipeline... able.

The output file is a .csv matrix:

variable | description --- | ---| --- file | name of the .lsm file from the 'input' folder date | date when data was recorded, i.e. when the picure was taken cell_line | cell line treatment | whether Control, Zinc treated or Zna/Zinc treated image | name of original image green_area_fraction | fraction of image area that shows any green (Fluozin showing free intracellular zinc) yellow_area_fraction | fraction of image area that shows any yellow (region where green colocalises with red stain, which is a lysotracker) green_mean | mean intensity of green on image yellow_mean | mean intensity of the colocalisation region green_stdev | intensity standard deviation of the green region yellow_stdev | intensity standard deviation of the yellow region cell_count | number of cells on image green_mean_per_cell | mean intensity of green divided by the number of cells yellow_mean_per_cell | mean intensity of colocalisation region divided by the number of cells