Marcel Schilling

@Zethson: Thank you for the fast follow up. I'll check tomorrow and will report back.

``` Successfully installed arviz-0.21.0 ``` Regardless, is arviz even really required to run scCODA or just for (optional) visualization of the MCMC diagnostics?

I think if we can get rid of the PyQt dependency alone for scCODA, both M1 Mac and conda installs should be possible already. Adding tascCODA support would be another...

Just fyi: I hope to fix this 'soon' via https://github.com/scverse/pertpy/issues/294.

@SNOL2: > It could be extremely useful... Do you have any data backup up that claim? In my hands this function never really yielded trustworthy results and I ended up...

Are the resources linked here still relevant or outdated by now? I don't know the ins and outs of DE in pertpy well enough to tackle this myself but I...

I noticed that the existing documentation even for the simple cases seems to be outdated: The [tutorial](https://pertpy.readthedocs.io/en/stable/tutorials/notebooks/differential_gene_expression.html#pseudobulks) uses > ```python > pertpy.tools.PseudobulkSpace().compute( > adata, target_col="Patient", groups_col="Cluster", > layer_key="counts", mode="sum", >...

No worries, just wanted to report it here. Especially since I saw your plans to (re-)enable all notebooks via CI and I noticed that this is even still included in...

Passing the output of `pertpy.tools.PseudobulkSpace().compute()` to `dc.pl.filter_samples()` (as shown in the docs) is also not possible anymore: ``` AssertionError: psbulk_* columns not present in adata.obs, this function should be used...

There are also examples still using the unsupported parameters: https://github.com/scverse/pertpy/blob/e6aaeb28537c382a5d714763e6ae0d645eb22ef7/pertpy/tools/_differential_gene_expression/_base.py#L92-L93