Access to the reference dataset with dimensionality reductions info

[mariafiruleva]

Dear Linnarson team,

First of all, thanks for the great dataset.

I was wondering, if there is any possibility to provide a loom file with dim reductions (PCA, tSNE)? Especially these dim reductions, that were used for the article (e.g., for Figure 1; https://github.com/linnarsson-lab/adult-human-brain/blob/main/notebooks/Figure1.ipynb script).

Thank you!

Best wishes,
Mariia

[DiracZhu1998]

Dear Mariia and Linnarson team,
I was wondering have you solved this issue? I checked about the latest adult_human_20221007.agg.loom, adult_human_20221007.loom, and human_adult_GRCh38-3.0.0.loom but none of them contain PCA TSNE or supercluster.

Best wishes,
Yuanzhen

[nvaulin]

Dear Mariia @mariafiruleva and Yuanzhen @DiracZhu1998 ,

I suppose the things you are looking for are located within Neurons.h5ad and Nonneurons.h5ad files.

adata = sc.read_h5ad('Nonneurons.h5ad')
print(adata.obsm)
>>> AxisArrays with keys: X_UMAP, X_tSNE

Then you can simply use this data and the figure (at least for nonneurons) is nearly the same:

sc.pl.umap(adata, color='supercluster_term', frameon=False, size=5)

However, for me to do this with scanpy I had to rename the keys, just like that:

adata.obsm['X_umap'] = adata.obsm['X_UMAP']

Hope this helps.

Best wishes,
Nikita