scDiffEq: modeling single-cell dynamics using neural differential equations.
Project description
An analysis framework for modeling dynamical single-cell data with neural differential equations, most notably stochastic differential equations allow us to build generative models of single-cell dynamics.
Install the development package:
git clone https://github.com/mvinyard/sc-neural-diffeqs.git; cd ./sc-neural-diffeqs;
pip install -e .
Main API
import scdiffeq as sdq
model = sdq.scDiffEq(
adata=adata, potential_type="fixed", train_lr=1e-4, train_step_size=1200
)
model.fit(train_epochs = 1500)
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