vacation/omeify repository overview

⁠omeify

https://github.com/jason-weirather/omeify⁠

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 and raw2ometiff⁠.

⁠Dependencies

• 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 with raw2ometiff 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.

⁠MITI Standard

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.

⁠Installation

1. Install the omeify package:

pip install omeify

⁠Usage

⁠Command Line Interface (CLI)

You can use omeify through the command line interface by running the following command:

omeify input output --type TYPE --series SERIES --rename_channels_json RENAME_CHANNELS_JSON --omit_uuid --output_json OUTPUT_JSON -v

• input: Input image file path.
• output: Output OME-TIFF file path.
• --type: Input image type (qptiff_mif: Akoya mIF qptiff, qptiff_he: Akoya H&E qptiff).
• --series: Series number (integer).
• --rename_channels_json: JSON file that contains a channel renaming dictionary.
• --omit_uuid: Omit UUID in OME tag (optional).
• --output_json: Output file for run info (optional).
• -v --verbose: Enable verbose logging (optional).

⁠Python API

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.

⁠License

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.