t-sne interpretation

[robertzeibich]

I ran pyscenic on the same dataset twice, but the input was filtered differently.

cellbender - mad filtering (based on https://www.sc-best-practices.org/preprocessing_visualization/quality_control.html) aucell umap

qclus pipeline aucell umap

aucell tsne

I still identify the same regulons, but in the 2nd run, regulons lighten up more.

These are epilepsy related TFs, claimed to be therapeutic targets (https://pmc.ncbi.nlm.nih.gov/articles/PMC9549512/).

What is more trustworthy now? Any suggestions for further investigations?

[ruoyeruolan]

It seems that qclus pipeline removed much more cells than cellbender. How about the qc result of the raw expression matrix?