Hi, thanks for releasing STATE.
I am using preprocess_train, train, and then infer, and I have two brief questions.
First, how should perturbation direction be encoded? For example, if my dataset contains activation and knowckdown, does STATE distinguish them only through the labels in pert_col? Should direction be explicitly included in the perturbation name?
And if it's just one direction, it just assumes all data goes in the same perturbation direction?
Second, how should I interpret the outputs of infer?
Wrote predictions to adata.obsm['X_hvg']
Saved count predictions to adata.X
Are these predicted counts, normalized values, log-transformed values, or model-space outputs?
For example, adata.X contains values like:
[0. 0. ... 0. 0. ]
[0.13628182 0. ... 0.11327718 0. ]]```
But these are not counts. What should I do? Is there anything that I am missing?
Hi, thanks for releasing STATE.
I am using
preprocess_train,train, and theninfer, and I have two brief questions.First, how should perturbation direction be encoded? For example, if my dataset contains activation and knowckdown, does STATE distinguish them only through the labels in
pert_col? Should direction be explicitly included in the perturbation name?And if it's just one direction, it just assumes all data goes in the same perturbation direction?
Second, how should I interpret the outputs of
infer?Are these predicted counts, normalized values, log-transformed values, or model-space outputs?
For example, adata.X contains values like: