Has something changed for the differential expression in the most recent version of scvi-tools? Previously, plots of bayes_factor vs. lfc_median were very similar to plots of prob_de vs. lfc_median. prob_de plots still look ok, but bayes_factor plots look like this:
Additionally, comparing lfc changes to ground truth simulated data gives wildly inaccurate results. Pseudobulk differential expression on the same dataset gives a perfect correlation (pearson=1.0)
Does the second plot look better in the old scVI-tools version? See other post about changes.
Could you try with a manual very small pseudocounts like 1e-10?
The Bayes factor plot likely looks find for a two-way comparison (change or not change vs the new three way comparison up/unchanged/down). There might be something wrong in computation there.
Changing pseudo counts gives the same results. Changing test_mode=‘two’ does reproduce the bayes factor plots as before, but the lfc estimates are still off. I applied the LFC changes to only genes expressed in >10% of cells and this increased the correlation to ~0.75, but I am still getting better LFC estimates with pseudobulk. I don’t have the plot on the bottom from a previous version (it was years ago I first tested this), but the results were certainly more accurate. I’ll keep an eye on the other post for the kwargs to reproduce previous versions
