sainsc 0.4.0

Segmentation-free Analysis of In Situ Capture data

sainsc

/ˈsaiəns/

"Segmentation-free Analysis of In Situ Capture data" or alternatively "Stupid Acronyms In Science"

sainsc is a segmentation-free analysis tool for spatial transcriptomics from in situ capture technologies (but also works for imaging-based technologies). It is easily integratable with the scverse (i.e. scanpy and squidpy) by exporting data in AnnData or SpatialData format.

Installation

sainsc is available on PyPI and bioconda.

# PyPI
pip install sainsc

# or conda
conda install bioconda::sainsc

For detailed installation instructions please refer to the documentation.

Documentation

For an extensive documentation of the package please refer to the ReadTheDocs page

Versioning

This project follows the SemVer guidelines for versioning.

Citations

If you are using sainsc for your research please cite

N. Müller-Bötticher, S. Tiesmeyer, R. Eils, N. Ishaque, "Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data" Small Methods (2025) https://doi.org/10.1002/smtd.202401123

@article{sainsc2025,
  author = {Müller-Bötticher, Niklas and Tiesmeyer, Sebastian and Eils, Roland and Ishaque, Naveed},
  title = {Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data},
  journal = {Small Methods},
  year = {2025},
  volume = {9},
  number = {5},
  pages = {2401123},
  doi = {10.1002/smtd.202401123},
}

License

This project is licensed under the MIT License - for details please refer to the LICENSE file.