megafish 0.1.2

Multi-omics Extensible GPU-Accelerated FISH analysis framework

MEGA-FISH

MEGA-FISH (Multi-omics Extensible GPU-Accelerated FISH analysis framework) is a Python package designed to process large-scale fluorescence images for spatial omics applications, including SeqFISH, SeqIS, and decoding-based FISH methods.

MEGA-FISH stitches sequentially captured tile images into a large, chunked single image and utilizes efficient computational resources (GPU or multi-threaded/multi-process CPU) for each processing step.

Users can generate a cell-by-gene expression matrix by combining simple functions such as image registration, segmentation, and spot detection.

Please see documentation for more information about MEGA-FISH.

Installation

MEGA-FISH supports GPU acceleration on Linux systems and Windows PCs with WSL2. See the documentation for more information.

MEGA-FISH supports multi-core CPU parallel computation and is available on Linux, Windows, and macOS. Below are the installation steps for setting up CPU-only MEGA-FISH.

conda create -n megafish python=3.11
conda activate megafish
pip install megafish

Getting Started

Once you have installed MEGA-FISH, you can start by following the tutorial using the example data.

Data Structure

MEGA-FISH is designed not to create a MEGA-FISH-specific data structure, but to use simple naming rules for xarray. This allows users to easily customize the analysis pipeline and transfer the data to other packages. See the documentation for the data structure and functions.

Contributing

We welcome contributions to MEGA-FISH. Please see the contribution guide for more information.

Citing

If MEGA-FISH was useful for your research, please consider citing the following our paper:

Coming soon.

License

MEGA-FISH is licensed under the BSD 3-Clause License.