ClearEx

Scalable Analytics for Cleared and Expanded Tissue Imaging.

ClearEx is an open source Python package for scalable analytics of cleared and expanded tissue imaging data. It relies heavily on next-generation file formats and cloud-based chunk computing to accelerate image analysis workflows, enabling tissue-scale computer vision and machine learning.

Installation with UV

You can also manage dependencies using [uv](https://github.com/astral-sh/uv), which provides faster installs and lockfile support. First, install `uv` via the official script:

Install uv

curl -LsSf https://astral.sh/uv/install.sh | sh

Confirm that uv is installed

uv --version

Install ClearEx

Then, in the root directory of the cloned ClearEx repository, run:

uv sync

# Optional - Install development dependencies
uv sync --extra dev 

# Optional - Install all additional dependencies.
uv sync --all-extras

uv is compatible with existing pip or conda workflows, so you can continue to use those tools if preferred.

Installation with pip

We recommend installing ClearEx in a dedicated Anaconda environment:

conda create -n clearex python=3.12
conda activate clearex

# Install core dependencies to circumvent BioHPC-specific issues.
conda install -c conda-forge pyarrow "numpy>=1.25" cython 
cd to/your/cloned/clearex/directory
pip install -e .

Installation with conda-forge

If you encounter compilation issues during installation, you can install ClearEx entirely from conda-forge:

cd to/your/cloned/clearex/directory
conda env create -f environment.yml
conda activate clearex

This installs all dependencies from conda-forge and the ClearEx package in editable mode. The environment is named clearex by default (specified in environment.yml).