Running and saving PCA on different anndata layers

• Additional function parameters / changed functionality / changed defaults?
• New analysis tool: A simple analysis tool you have been using and are missing in sc.tools?
• New plotting function: A kind of plot you would like to seein sc.pl?
• External tools: Do you know an existing package that should go into sc.external.*?
• Other?

I find using the adata.layers really useful to compare normalisation strategies. I’d like to also be able to seamlessly run sc.tl.pca on data stored in different layers of the same anndata object.

At the moment my workaround is to set adata.X before PCA and changing the key to the adata.obsm element after:

adata.X = adata.layers["mylayer"]
sc.tl.pca(adata)
adata.obsm["mylayer_pca"] = adata.obsm["X_pca"]

Ideally I’d like to just be able to set a layer argument in sc.tl.pca, as in the plotting functions.

Any plans on linking data layers to dimensionality reductions?

[Ebony-Watson]

Is there any update on the progress of this?

[Koncopd]

Hi, you can also do this directly adata.obsm["mylayer_pca"] = sc.tl.pca(adata.layers["mylayer"])