Fix dependency-gated validation flow in DE/SCTransform/Numbat paths

chatspatial/tools/cnv_analysis.py

@@ -430,10 +430,20 @@ def _infer_cnv_numbat(
     # Lazy import and check for Numbat availability
     # Note: Numbat requires rpy2 + R + Numbat R package - cannot use centralized manager
     try:
-        import anndata2ri
-        import rpy2.robjects as ro
-        from rpy2.rinterface_lib import openrlib
-        from rpy2.robjects import conversion, default_converter, numpy2ri, pandas2ri
+        import importlib
+        import sys
+
+        anndata2ri = importlib.import_module("anndata2ri")
+        ro = sys.modules.get("rpy2.robjects") or importlib.import_module("rpy2.robjects")
+        rinterface_lib = sys.modules.get("rpy2.rinterface_lib") or importlib.import_module(
+            "rpy2.rinterface_lib"
+        )
+        openrlib = rinterface_lib.openrlib
+
+        conversion = ro.conversion
+        default_converter = ro.default_converter
+        numpy2ri = ro.numpy2ri
+        pandas2ri = ro.pandas2ri
 
         # Test if Numbat R package is available
         ro.r("suppressPackageStartupMessages(library(numbat))")

chatspatial/tools/differential.py

@@ -472,11 +472,6 @@ async def _run_pydeseq2(
             "sample_key='sample')"
         )
 
-    # Import pydeseq2 (require() raises ImportError if not available)
-    require("pydeseq2", ctx, feature="DESeq2 differential expression")
-    from pydeseq2.dds import DeseqDataSet
-    from pydeseq2.ds import DeseqStats
-
     # Get data
     adata = await ctx.get_adata(data_id)
 
@@ -617,6 +612,12 @@ async def _run_pydeseq2(
             f"Current counts: {condition_counts.to_dict()}"
         )
 
+    # Import pydeseq2 only after precondition checks so users get actionable
+    # validation errors even when optional dependency is unavailable.
+    require("pydeseq2", ctx, feature="DESeq2 differential expression")
+    from pydeseq2.dds import DeseqDataSet
+    from pydeseq2.ds import DeseqStats
+
     # Run PyDESeq2
     try:
         # Design: ~condition (standard for pseudobulk DE).

chatspatial/tools/preprocessing.py

@@ -367,11 +367,6 @@ async def preprocess_data(
         vst_flavor = "v2" if params.sct_method == "fix-slope" else "v1"
 
         try:
-            # Import rpy2 modules
-            import rpy2.robjects as ro
-            from rpy2.robjects import numpy2ri
-            from rpy2.robjects.conversion import localconverter
-
             # Note: counts layer is already created earlier in this preprocessing workflow.
             # It will be properly subsetted if SCT filters genes
             # Convert to sparse CSC matrix (genes × cells) for R's dgCMatrix
@@ -380,6 +375,18 @@ async def preprocess_data(
             else:
                 counts_sparse = scipy.sparse.csc_matrix(adata.X.T)
 
+            # Import rpy2 modules
+            try:
+                import rpy2.robjects as ro
+                from rpy2.robjects import numpy2ri
+                from rpy2.robjects.conversion import localconverter
+            except ImportError as e:
+                raise DependencyError(
+                    "SCTransform requires rpy2. "
+                    "Install with: pip install 'rpy2>=3.5.0' "
+                    "or use normalization='pearson_residuals'/'log'."
+                ) from e
+
             # Transfer sparse matrix components to R
             with localconverter(ro.default_converter + numpy2ri.converter):
                 ro.globalenv["sp_data"] = counts_sparse.data.astype(np.float64)

tests/unit/test_cnv_analysis_utils.py

@@ -190,6 +190,7 @@ def test_infer_cnv_numbat_requires_allele_dataframe(
 ):
     adata = minimal_spatial_adata.copy()
     adata.obs["cell_type"] = ["A"] * 30 + ["B"] * 30
+    monkeypatch.setitem(__import__("sys").modules, "rpy2", ModuleType("rpy2"))
 
     fake_ro = ModuleType("rpy2.robjects")
     fake_ro.r = lambda *_a, **_k: None