def runScGen(adata,
batch,
cell_type,
epochs=100,
hvg=None,
model_path='/localscratch'):
"""
Parametrization taken from the tutorial notebook at:
https://nbviewer.jupyter.org/github/M0hammadL/scGen_notebooks/blob/master/notebooks/scgen_batch_removal.ipynb
"""
import scgen
checkSanity(adata, batch, hvg)
# Fit the model
network = scgen.VAEArith(x_dimension=adata.shape[1], model_path=model_path)
network.train(train_data=adata, n_epochs=epochs, save=False)
corrected_adata = scgen.batch_removal(network,
adata,
batch_key=batch,
cell_label_key=cell_type)
network.sess.close()
return corrected_adata
def test_batch_removal():
train = sc.read("./tests/data/pancreas.h5ad",
backup_url="https://goo.gl/V29FNk")
train.obs["cell_type"] = train.obs["celltype"].tolist()
network = scgen.VAEArith(x_dimension=train.shape[1],
model_path="./models/batch")
network.train(train_data=train, n_epochs=0)
corrected_adata = scgen.batch_removal(network, train)
network.sess.close()
def test_batch_removal():
train = sc.read(
"./data/pancreas.h5ad",
backup_url=
"https://www.dropbox.com/s/qj1jlm9w10wmt0u/pancreas.h5ad?dl=1")
train.obs["cell_type"] = train.obs["celltype"].tolist()
network = scgen.VAEArith(x_dimension=train.shape[1],
model_path="./models/batch")
network.train(train_data=train, n_epochs=1, verbose=1)
corrected_adata = scgen.batch_removal(network, train)
print(corrected_adata.obs)
network.sess.close()