/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.
sainsc is available on PyPI and bioconda.
# PyPI
pip install sainsc# or conda
conda install bioconda::sainscFor detailed installation instructions please refer to the documentation.
For an extensive documentation of the package please refer to the ReadTheDocs page
This project follows the SemVer guidelines for versioning.
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},
}
This project is licensed under the MIT License - for details please refer to the LICENSE file.