SCIMAP 2.0.3

Spatial Single-Cell Analysis Toolkit

Single-Cell Image Analysis Package

Scimap is a scalable toolkit for analyzing spatial molecular data. The underlying framework is generalizable to spatial datasets mapped to XY coordinates. The package uses the anndata framework making it easy to integrate with other popular single-cell analysis toolkits. It includes preprocessing, phenotyping, visualization, clustering, spatial analysis and differential spatial testing. The Python-based implementation efficiently deals with large datasets of millions of cells.

Installation

We strongly recommend installing scimap in a fresh virtual environment.

# If you have conda installed
conda create --name scimap python=3.10
conda activate scimap

Install scimap directly into an activated virtual environment:

By default, we recommend installing scimap alongside napari for visualization purposes. Please note that napari requires a GUI toolkit like PyQt. If you encounter any errors due to your operating system, you should install scimap and napari separately, following napari's documentation.

pip install scimap[napari]

If installation fails due to pyqt6; install scimap without napari.

pip install scimap

After installation, the package can be imported as:

$ python
>>> import scimap as sm

Get Started

Detailed documentation of scimap functions and tutorials are available here.

SCIMAP development was led by Ajit Johnson Nirmal, Harvard Medical School.
Check out other tools from the Nirmal Lab.

Contibute

Interested in contributing to the package? Check out our guidelines at https://scimap.xyz/contribute/ for detailed instructions.

Funding

This work was supported by the following NIH grant K99-CA256497