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scDiffEq: modeling single-cell dynamics using neural differential equations.

Project description

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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
from neural_diffeqs import NeuralSDE

model = sdq.models.scDiffEq(
    adata, func=NeuralSDE(state_size=50, mu_hidden=[400, 400], sigma_hidden=[400, 400])
)
model.fit()

Built on:

pytorch_logopytorch_lightning_logo neural_diffeqs_logo

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