Method for simulating single cells using longitudinal scRNA-seq.
Project description
prescient
Software for PRESCIENT (Potential eneRgy undErlying Single Cell gradIENTs), a generative model for modeling single-cell time-series.
- Current paper version: https://www.biorxiv.org/content/10.1101/2020.08.26.269332v1
- For paper pre-processing scripts, training bash scripts, pre-trained models, and visualization notebooks please visit https://github.com/gifford-lab/prescient-analysis.
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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