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Getting Started

Installation

Sopa can be installed on every OS with pip or poetry.

The preferred Python version is python==3.10, but we also support 3.9 to 3.11.

Advice (optional)

We advise creating a new environment via a package manager (except if you use Poetry, which will automatically create the environment).

For instance, you can create a new conda environment:

conda create --name sopa python=3.10
conda activate sopa

Choose one of the following, depending on your needs (it should take at most a few minutes):

pip install sopa

# or to install extras
pip install 'sopa[cellpose,baysor,tangram]'

git clone https://github.com/gustaveroussy/sopa.git
cd sopa

pip install .

git clone https://github.com/gustaveroussy/sopa.git
cd sopa

poetry install --all-extras

Baysor usage

Even though pip install 'sopa[baysor]' will install some dependencies related to baysor, you still have to install the baysor command line (see the official repository) if you want to use it.

Snakemake setup

To use the Snakemake pipeline, the installation process is slightly different because you'll need the whole repository.

  1. Clone the sopa repository, and move to the root of the project: 

    git clone https://github.com/gustaveroussy/sopa.git
cd sopa

  2. Create a conda environment called sopa: 

    conda create --name sopa python=3.10

  3. At the root of the sopa directory, install the package in dev mode, and choose the extras you want (among cellpose/baysor/tangram, depending on your desired usage): 

    conda activate sopa
pip install -e ".[snakemake,cellpose,baysor,tangram]"

Now, follow our snakemake tutorial to run your first pipeline.

Note

You can also use a separate environment for snakemake. In this case, you don't need to install the 'snakemake' extra when installing sopa. But you may still need to install other extras, for instance, 'cellpose' if you plan to run Cellpose.

Usage

Sopa comes in three different flavours, each corresponding to a different use case:

  • Snakemake pipeline: choose a config, and run our pipeline on your spatial data in a few minutes. See our snakemake tutorial.
  • CLI: use our command-line-interface to prototype quickly your own pipeline
  • API: use directly sopa as a Python package for full flexibility and customization (see a tutorial here)