WARNING: alpha software. We are sharing this early in case it is useful to other groups. Please expect breaking changes. Examples of running the package are found in /Examples.
GPU accelerated post-processing for 2D / 3D iterative barcoded FISH data. This package currently Nvidia only and Linux only due to RAPIDS.AI package availabilty. Documentation is available at https://qi2lab.github.io/merfish3d-analysis/.
Create a python 3.12 environment using your favorite package manager, e.g.
mamba create -n merfish3d python=3.12
Activate the environment and install the GPU dependencies. This install method assumes an Nvidia GPU capable of running CUDA 12.8.
mamba activate merfish3d
mamba install -c conda-forge -c nvidia -c pytorch -c rapidsai cupy=13.4 cucim=25.02 cuvs=25.02 pycudadecon "cuda-version>=12.0,<=12.8" cudnn cutensor nccl onnx onnxruntime pytorch torchvision 'pytorch=*=*cuda*' cellpose
Next, clone the repository using git clone https://github.com/QI2lab/merfish3d-analysis and install using pip install .. For interactive editing use pip install -e ..
If you plan on re-segmenting cells using decoded RNA, please follow the Baysor installation instructions.
To build the documentation, install using pip install .[docs]. Then execute mkdocs build --clean and mkdocs serve. The documentation is available in your web browser at http://127.0.0.1:8000/.