omeify
is a Python package designed to streamline the conversion of various image files, such as TIFF files, into the OME-TIFF format. The generated OME-TIFF files are deidentified following the MITI standard. This package relies on two Java tools: bioformats2raw 0.6.1
and raw2ometiff 0.4.1
.
$ docker pull vacation/omeify:latest
$ docker run --rm -v $(pwd):$(pwd) -u $(id -u):$(id -g) vacation/omeify:latest omeify -h
usage: omeify [-h] --type {qptiff_mif,qptiff_he} [--series SERIES]
[--rename_channels_json RENAME_CHANNELS_JSON] [--omit_uuid]
[--output_json OUTPUT_JSON] [--cache_directory CACHE_DIRECTORY]
[--compression {LZW,JPEG,Uncompressed}] [-v] [--version]
input output
omeify: Convert images into OME-TIFF format
positional arguments:
input Input image file path
output Output OME-TIFF file path
options:
-h, --help show this help message and exit
--type {qptiff_mif,qptiff_he}
Input image type (qptiff_mif: Akoya mIF qptiff,
qptiff_he: Akoya H&E qptiff) (default: None)
--series SERIES Series number (integer) (default: 0)
--rename_channels_json RENAME_CHANNELS_JSON
JSON file that contains channel renaming dictionary
(default: None)
--omit_uuid Omit UUID in OME tag (default: False)
--output_json OUTPUT_JSON
Output file for run info (default: None)
--cache_directory CACHE_DIRECTORY
Path to a directory for storing temporary Zarr
directories. Defaults to the system temporary folder.
(default: None)
--compression {LZW,JPEG,Uncompressed}
Compression type for output OME-TIFF file (LZW, JPEG)
(default: LZW)
-v, --verbose Enable verbose logging (default: False)
--version Display omeify and constituent programs versions
(default: False)
bioformats2raw
: A Java application that converts various image file formats, including .mrxs, to an intermediate Zarr structure compatible with the OME-NGFF specification. This tool is used in conjunction withraw2ometiff
to produce a Bio-Formats 5.9.x ("Faas") or Bio-Formats 6.x (true OME-TIFF) pyramid.raw2ometiff
: A Java application that converts a directory of tiles to an OME-TIFF pyramid. This tool is the second half of the iSyntax/.mrxs to OME-TIFF conversion process.
Note: As omeify
is licensed under the MIT license, the GPL-licensed dependencies (bioformats2raw
and raw2ometiff
) are not included. Instructions on how to install these dependencies will be provided later.
omeify
follows the Minimum Information guidelines for highly multiplexed tissue images (MITI) to ensure the highest standards in data and metadata handling. The MITI standard is specifically designed for tissue atlases that combine multi-channel microscopy with single cell sequencing and other omics data from normal and diseased specimens. This standard guides data deposition, curation, and release.
- Install the
omeify
package:
pip install omeify
You can use omeify
through the command line interface by running the following command:
$ omeify -h
usage: omeify [-h] --type {qptiff_mif,qptiff_he} [--series SERIES]
[--rename_channels_json RENAME_CHANNELS_JSON] [--omit_uuid] [--output_json OUTPUT_JSON]
[--cache_directory CACHE_DIRECTORY] [--compression {LZW,JPEG,Uncompressed}] [-v]
[--version]
input output
omeify: Convert images into OME-TIFF format
positional arguments:
input Input image file path
output Output OME-TIFF file path
options:
-h, --help show this help message and exit
--type {qptiff_mif,qptiff_he}
Input image type (qptiff_mif: Akoya mIF qptiff, qptiff_he: Akoya H&E qptiff)
(default: None)
--series SERIES Series number (integer) (default: 0)
--rename_channels_json RENAME_CHANNELS_JSON
JSON file that contains channel renaming dictionary (default: None)
--omit_uuid Omit UUID in OME tag (default: False)
--output_json OUTPUT_JSON
Output file for run info (default: None)
--cache_directory CACHE_DIRECTORY
Path to a directory for storing temporary Zarr directories. Defaults to the
system temporary folder. (default: None)
--compression {LZW,JPEG,Uncompressed}
Compression type for output OME-TIFF file (LZW, JPEG) (default: LZW)
-v, --verbose Enable verbose logging (default: False)
--version Display omeify and constituent programs versions (default: False)
You can also use omeify
within your Python scripts:
from omeify.inputs import AkoyaMIFQptiff, AkoyaHEQptiff
input_processor = AkoyaMIFQptiff(input_file_path, series=series_number)
input_processor.rename_channels = rename_channels_dict
output_info = input_processor.convert(output_file_path, display_uuid=True)
Replace AkoyaMIFQptiff
with AkoyaHEQptiff
if you are working with H&E qptiff files.
This project is licensed under the MIT License. Please note that the bioformats2raw
and raw2ometiff
dependencies are licensed under the GPL License and are not included in this repository.