/scPrisma

scPrisma is a spectral analysis method, for pseudotime reconstruction, informative genes inference, filtering, and enhancement of underlying cyclic signals

Primary LanguageJupyter NotebookMIT LicenseMIT

scPrisma

scPrisma is a spectral analysis method, for pseudotime reconstruction, informative genes inference, filtering, and enhancement of underlying topological signals. workflow

Manuscript

Karin, J., Bornfeld, Y. & Nitzan, M. scPrisma infers, filters and enhances topological signals in single-cell data using spectral template matching. Nat Biotechnol (2023)

Getting Started

For documentation please refer to scPrisma documentation.

Tutorials

For tutorials, please refer to:Tutorials

Reproducibility

For reproducibility of scPrisma manuscript, please refer to:
https://github.com/nitzanlab/scPrisma_notebooks

Installation

git clone https://github.com/nitzanlab/scPrisma.git
cd scPrisma
pip install .
For running the gpu version install it like so pip install ."[gpu]"

Running the tests

I recommend creating two separate virtual environments for running the cpu/gpu test suite. On my laptop, I use conda but this can be replaced any other virtual environment manager of your choice.

Running the cpu only tests

conda create -n scprisma_cpu python=3.10
conda activate scprisma_cpu
pip install .
pytest tests/cpu

Running the gpu only tests

conda create -n scprisma_gpu python=3.10
conda activate scprisma_gpu
pip install .[gpu]
pytest tests/gpu

To cite:

@article{karin2023scprisma,
  title={sc{P}risma infers, filters and enhances topological signals in single-cell data using spectral template matching},
  author={Karin, Jonathan and Bornfeld, Yonathan and Nitzan, Mor},
  journal={Nature Biotechnology},
  pages={1--10},
  year={2023},
  publisher={Nature Publishing Group US New York}
}

Contact

Jonathan Karin - jonathan.karin [at ] mail.huji.ac.il
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