Installation

We recommend using a virtual environment such as conda, mamba, venv or others. Instructions below are for conda, but are completely analogous for other solutions.

The installation has been tested on windows10, almaLinux 9.6, rockyLinux 9.5 and mac.

1. Create the environment

Create a and activate new environment with Python 3.10:

conda create -n napari-sparrow python=3.10 -c conda-forge
conda activate napari-sparrow

2. Install SPArrOW

Installing SPArrOW can be done by cloning the repository and installing locally:

git clone https://github.com/saeyslab/napari-sparrow.git
cd napari-sparrow
pip install .

Alternatively, pip can install SPArrOW directly from github as follows:

pip install git+https://github.com/saeyslab/napari-sparrow.git

Optional dependencies

SPArrOW includes a number of optional dependencies for specific use cases. Note that to run the whole tutorial, the easiest option is to install the testing version. These are listed below.

To use the function sp.im.tiling_correction:

pip install .[tiling]
# alternatively:
pip install "git+https://github.com/saeyslab/napari-sparrow.git#egg=sparrow[tiling]"

To use the Napari plugin:

pip install .[plugin]
# alternatively:
pip install "git+https://github.com/saeyslab/napari-sparrow.git#egg=sparrow[plugin]"

To run SPArrOW from the cli:

pip install .[cli]
# alternatively:
pip install "git+https://github.com/saeyslab/napari-sparrow.git#egg=sparrow[cli]"

To be able to run the unit tests:

pip install .[testing]
# alternatively:
pip install "git+https://github.com/saeyslab/napari-sparrow.git#egg=sparrow[testing]"