oif

Extract images and metadata from .oif files.

Write data contained in a .oif file to directories. Directories are structured such that the basename of the .oif file (e.g. /path/to/my/<basename>.oif) is used as the parent directory. Each parent directory then contains subdirectories for every channel contained in the .oif file. Every channel subdirectory contains .png images for each z-stack contained for that channel. Within each parent directory, a file metadata.json, is also created to house annotated data for the embryo.

File structure example using /path/to/my/<basename>.oif with 3 Channels:

• out_dir
  • metadata.json
  • basename
  • Channel1
    • z0.png
    • z1.png
    • ...
  • Channel2
    • z0.png
    • z1.png
    • ...
  • Channel3
    • z0.png
    • z1.png
    • ...

If a PMC channel is present, the associated channel directory will break into two sub directories.

• PMCChannel
  • ContrastImages
  • IntensityImages

The directory ContrastImages has the contrast between intensity values increased. IntensityImages keeps the raw intensity values. PMC labelling should be done on ContrastImages, while downstream analysis should use the raw data in IntensityImages.

The main script, parse_oif.py takes a single .json file as input with the following format:

{
"oif_file": <location to oif file>,
"stains": {"1": <stain used in first channel>,
           "2": <stain used in second channel>,
           "3": <stain used in third channel>,
           "4": <stain used in fourth channel>},
"person": <name of person who collected the data>,
"hpf": <hours past fertilization>,
"treatment": <treatment applied to embryo>,
"out_dir": <desired location to write output directories>,
"prefix": <optinal string to write in front of output files>
}

To run the script, issue the following command:

python parse_oif.py <input.json>

Both oiffile.py and tiffile.py were taken from here: https://www.lfd.uci.edu/~gohlke/