fix: preserve dtypes when running scrublet

docs/release-notes/3939.fix.md

@@ -0,0 +1 @@
+Ensure `scanpy.pp.scrublet()` preserves (categorical) data types within `.obs`

src/scanpy/preprocessing/_scrublet/__init__.py

@@ -262,7 +262,6 @@ def _run_scrublet(ad_obs: AnnData, ad_sim: AnnData | None = None):
 
         # Run Scrublet independently on batches and return just the
         # scrublet-relevant parts of the objects to add to the input object
-
         batches = np.unique(adata.obs[batch_key])
         scrubbed = [
             _run_scrublet(
@@ -271,29 +270,27 @@ def _run_scrublet(ad_obs: AnnData, ad_sim: AnnData | None = None):
             )
             for batch in batches
         ]
-        scrubbed_obs = pd.concat([scrub["obs"] for scrub in scrubbed])
+        scrubbed_obs = pd.concat([scrub["obs"] for scrub in scrubbed]).astype(
+            adata.obs.dtypes
+        )
 
         # Now reset the obs to get the scrublet scores
-
         adata.obs = scrubbed_obs.loc[adata.obs_names.values]
 
         # Save the .uns from each batch separately
-
         adata.uns["scrublet"] = {}
         adata.uns["scrublet"]["batches"] = dict(
             zip(batches, [scrub["uns"] for scrub in scrubbed], strict=True)
         )
 
         # Record that we've done batched analysis, so e.g. the plotting
         # function knows what to do.
-
         adata.uns["scrublet"]["batched_by"] = batch_key
 
     else:
         scrubbed = _run_scrublet(adata_obs, adata_sim)
 
         # Copy outcomes to input object from our processed version
-
         adata.obs["doublet_score"] = scrubbed["obs"]["doublet_score"]
         adata.obs["predicted_doublet"] = scrubbed["obs"]["predicted_doublet"]
         adata.uns["scrublet"] = scrubbed["uns"]

tests/test_scrublet.py

@@ -228,3 +228,13 @@ def test_scrublet_simulate_doublets():
         adata_sim.obsm["doublet_parents"],
         np.array([[13, 132], [106, 43], [152, 3], [160, 103]]),
     )
+
+
+def test_scrublet_dtypes() -> None:
+    """Test that Scrublet does not change dtypes of existing data.obs cols."""
+    adata = pbmc200()
+    adata.obs["batch"] = pd.Categorical(100 * ["a"] + 100 * ["b"])
+
+    sc.pp.scrublet(adata, use_approx_neighbors=False, batch_key="batch")
+
+    assert adata.obs["batch"].dtype == "category"