feat(panel): validate hashing marker ids and keep collapsed bases

src/pixelator/pna/anndata.py

@@ -41,14 +41,19 @@ def add_panel_information(adata: AnnData, panel: PNAAntibodyPanel) -> AnnData:
 
 
 def pna_edgelist_to_anndata(
-    pixel_connection: duckdb.DuckDBPyConnection, panel: PNAAntibodyPanel
+    pixel_connection: duckdb.DuckDBPyConnection,
+    panel: PNAAntibodyPanel,
+    markers: list[str] | None = None,
 ) -> AnnData:
     """Build an AnnData object from a DuckDB connection to a pixel file and a panel object.
 
     Args:
         pixel_connection: A DuckDB connection to a pixel file. The connection must contain an 'edgelist' table
             with the required columns (e.g., component, marker_1, marker_2, umi1, umi2, read_count).
         panel: The antibody panel object containing marker metadata.
+        markers: Marker ids to use as the count-matrix columns. Defaults to
+            every marker on ``panel``. Sample calling passes the markers left
+            after hashing clones collapse to their base name.
 
     Returns:
         An AnnData object with counts and panel information.
@@ -73,10 +78,11 @@ def pna_edgelist_to_anndata(
         .tolist()
     )
 
+    marker_list = list(panel.markers if markers is None else markers)
     n_components = len(components)
-    n_markers = len(panel.markers)
+    n_markers = len(marker_list)
     component_to_idx = {c: i for i, c in enumerate(components)}
-    marker_to_idx = {m: i for i, m in enumerate(panel.markers)}
+    marker_to_idx = {m: i for i, m in enumerate(marker_list)}
 
     X = np.zeros((n_components, n_markers), dtype=np.uint32)
     n_umi1_arr = np.zeros(n_components, dtype=np.uint64)
@@ -152,7 +158,7 @@ def pna_edgelist_to_anndata(
     node_counts_df = pd.DataFrame(
         X,
         index=component_index,
-        columns=pd.Index(panel.markers, name="marker_id"),
+        columns=pd.Index(marker_list, name="marker_id"),
     )
 
     logger.debug("Computing component metrics.")
@@ -182,7 +188,7 @@ def pna_edgelist_to_anndata(
 
     logger.debug("Computing antibody metrics.")
     antibody_metrics_df = calculate_antibody_metrics(counts_df=node_counts_df)
-    antibody_metrics_df = antibody_metrics_df.reindex(index=panel.markers, fill_value=0)
+    antibody_metrics_df = antibody_metrics_df.reindex(index=marker_list, fill_value=0)
     antibody_metrics_df.index.name = "marker_id"
     # Do a dtype conversion of the columns here since AnnData cannot handle
     # a pyarrow arrays.
@@ -201,7 +207,7 @@ def pna_edgelist_to_anndata(
     adata = add_panel_information(adata, panel)
 
     total_marker_counts = node_counts_df.sum(axis=1)
-    isotype_markers = adata.var[adata.var["control"]].index
+    isotype_markers = panel.df.index[panel.df["control"]]
     isotype_counts = node_counts_df[isotype_markers].sum(axis=1)
     adata.obs["isotype_fraction"] = isotype_counts / total_marker_counts
 

src/pixelator/pna/cli/sample_calling.py

@@ -118,9 +118,13 @@ def sample_calling_cli(
             pool_metadata=PxlFile(Path(input_pxl_file)).metadata(),
         )
         return
-    hashing_antibodies_in_panel = set(
-        panel_info.df[panel_info.df["sample_hashing"] == "yes"].index.to_list()
-    )
+    if "sample_hashing" not in panel_info.df.columns:
+        raise ValueError(
+            "Sample calling requires a sample_hashing column on the panel "
+            "so hashing markers can be identified. This panel has no "
+            "sample_hashing column."
+        )
+    hashing_antibodies_in_panel = panel_info.hashing_marker_ids
     samplesheet_df = pl.read_csv(samplesheet)
     _reject_reserved_samplesheet_names(
         samplesheet_df["sample"].to_list(),