gifford-lab / prescient

Codebase for PRESCIENT (Potential eneRgy undErlying Single Cell gradIENTs) for generative modeling of single-cell time-series.

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prescient

Software for PRESCIENT (Potential eneRgy undErlying Single Cell gradIENTs), a generative model for modeling single-cell time-series.

Documentation

Documentation is available at https://cgs.csail.mit.edu/prescient.

Requirements

  • pytorch 1.4.0
  • geomloss 0.2.3, pykeops 1.3
  • numpy, scipy, pandas, sklearn, tqdm, annoy
  • scanpy, pyreadr, anndata
  • Recommended: An Nvidia GPU with CUDA support for GPU acceleration (see paper for more details on computational resources)

Bugs & Suggestions

Please report any bugs, problems, suggestions or requests as a Github issue

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Codebase for PRESCIENT (Potential eneRgy undErlying Single Cell gradIENTs) for generative modeling of single-cell time-series.

License:MIT License


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