Minor bug fixes and improvements manual testing notes

pandasaurus_cxg/anndata_analyzer.py

@@ -69,9 +69,9 @@ def __init__(self, anndata: AnnData, author_cell_type_list: Optional[List[str]]
                 raise ValueError(
                     "AnndataAnalyzer initialization error:\n\n"
                     "The 'obs_meta' field is missing in anndata.uns!\n"
-                    "If this field is absent, you can provide a list of field names from the AnnData file "
-                    "using the free_text_fields parameter.\n"
-                    f"Available free text fields are: {', '.join(available_free_text_fields)}"
+                    "If this field is absent, you can provide a list of field names from the "
+                    "AnnData file using the author_cell_type_list parameter.\n"
+                    f"Available author cell type fields are: {', '.join(available_free_text_fields)}"
                 )
         self.report_df = pd.DataFrame()
 

pandasaurus_cxg/anndata_enricher.py

@@ -33,8 +33,10 @@ def __init__(
             anndata: The AnnData object.
             cell_type_field: The cell type information in the anndata object.
                 Defaults to "cell_type_ontology_term_id".
-            context_field: The context information in the anndata object.
+            context_field: Ontology ID of the context information in the anndata object.
                 Defaults to "tissue_ontology_term_id".
+            context_field_label: Label of the context information in the anndata object.
+                Defaults to "tissue".
             ontology_list_for_slims: The ontology list for generating the slim list.
                 The slim list is used in minimal_slim_enrichment and full_slim_enrichment.
                 Defaults to "Cell Ontology"
@@ -62,6 +64,7 @@ def from_file_path(
         file_path: str,
         cell_type_field: Optional[str] = "cell_type_ontology_term_id",
         context_field: Optional[str] = "tissue_ontology_term_id",
+        context_field_label: Optional[str] = "tissue",
         ontology_list_for_slims: Optional[List[str]] = None,
     ):
         """Initialize the AnndataEnricher instance with file path.
@@ -71,8 +74,10 @@ def from_file_path(
             file_path: The path to the file containing the anndata object.
             cell_type_field: The cell type information in the anndata object.
                 Defaults to "cell_type_ontology_term_id".
-            context_field: The context information in the anndata object.
+            context_field: Ontology ID of the context information in the anndata object.
                 Defaults to "tissue_ontology_term_id".
+            context_field_label: Label of the context information in the anndata object.
+                Defaults to "tissue".
             ontology_list_for_slims: The ontology list for generating the slim list.
                 The slim list is used in minimal_slim_enrichment and full_slim_enrichment.
                 Defaults to "Cell Ontology"
@@ -83,6 +88,7 @@ def from_file_path(
             AnndataLoader.load_from_file(file_path),
             cell_type_field,
             context_field,
+            context_field_label,
             ontology_list_for_slims,
         )
 

pandasaurus_cxg/enrichment_analysis.py

@@ -8,7 +8,7 @@
 
 
 class AnndataEnrichmentAnalyzer:
-    def __init__(self, file_path: str, author_cell_type_list: Optional[str] = None):
+    def __init__(self, file_path: str, author_cell_type_list: Optional[List[str]] = None):
         """
         Initializes the AnndataEnrichmentAnalyzer, a wrapper for AnndataEnricher and AnndataAnalyzer.
 

pandasaurus_cxg/graph_generator/graph_generator.py

@@ -17,6 +17,7 @@
     add_edge,
     add_node,
     add_outgoing_edges_to_subgraph,
+    colour_mapping,
     find_and_rotate_center_layout,
     generate_subgraph,
     select_node_with_property,
@@ -292,7 +293,17 @@ def visualize_rdf_graph(
             if isinstance(o, URIRef) and p != RDF.type:
                 add_edge(nx_graph, s, p, o)
             elif p == RDFS.label:
-                add_node(nx_graph, s, o)
+                add_node(nx_graph, s, {"label": str(o)})
+            elif p == RDF.type:
+                add_node(nx_graph, s, {"type": str(o)})
+
+        # Identify and remove nodes without any edge
+        # cell cluster type generate a node independent of the whole graph. this fix it
+        if len(nx_graph.nodes()) != 1:
+            nodes_to_remove = [
+                node for node, degree in dict(nx_graph.degree()).items() if degree == 0
+            ]
+            nx_graph.remove_nodes_from(nodes_to_remove)
 
         # Identify and remove nodes without any edge
         # cell cluster type generate a node independent of the whole graph. this fix it
@@ -307,6 +318,17 @@ def visualize_rdf_graph(
             (u, v, nx_graph.edges[u, v]) for u, v in transitive_reduction_graph.edges
         )
 
+        node_colors = []
+        # Get node colors based on node types
+        for node in transitive_reduction_graph.nodes:
+            node_colors.append(
+                colour_mapping.get(transitive_reduction_graph.nodes[node]["type"], "red")
+            )
+        # node_colors = [
+        #     colour_mapping[transitive_reduction_graph.nodes[node]["type"]]
+        #     for node in transitive_reduction_graph.nodes
+        # ]
+
         pos = find_and_rotate_center_layout(transitive_reduction_graph)
         plt.figure(figsize=(10, 10))
 
@@ -321,17 +343,20 @@ def visualize_rdf_graph(
             with_labels=True,
             labels=node_labels,
             node_size=2000,
-            node_color="skyblue",
+            node_color=node_colors,
             font_size=8,
             font_weight="bold",
         )
         # Draw edge labels on the graph
         edge_labels = nx.get_edge_attributes(transitive_reduction_graph, "label")
-        edge_labels_formatted = {edge: label for edge, label in edge_labels.items()}
+        edge_labels = {
+            edge: "\n".join(textwrap.wrap(label, width=10)) for edge, label in edge_labels.items()
+        }
+        # edge_labels_formatted = {edge: label for edge, label in edge_labels.items()}
         nx.draw_networkx_edge_labels(
             transitive_reduction_graph,
             pos,
-            edge_labels=edge_labels_formatted,
+            edge_labels=edge_labels,
             font_size=8,
             font_color="red",
         )
@@ -423,6 +448,7 @@ def set_label_adding_priority(self, label_priority: Union[List[str], Dict[str, i
                 order for adding labels.
 
         """
+        label_priority.append("cell_type") if "cell_type" not in label_priority else None
         if isinstance(label_priority, list):
             self.label_priority = {
                 label: len(label_priority) - i for i, label in enumerate(label_priority)

pandasaurus_cxg/graph_generator/graph_generator_utils.py

@@ -1,12 +1,31 @@
 import networkx as nx
-from rdflib import BNode, RDF, RDFS, Graph, Literal, Namespace, OWL, URIRef
+from rdflib import OWL, RDF, RDFS, BNode, Graph, Literal, Namespace, URIRef
+
+from pandasaurus_cxg.graph_generator.graph_predicates import (
+    CLUSTER,
+    CONSIST_OF,
+    SUBCLUSTER_OF,
+)
+
+colour_mapping = {
+    "http://www.w3.org/2002/07/owl#Class": "deepskyblue",
+    "http://purl.obolibrary.org/obo/PCL_0010001": "cyan",
+}
 
 
 def add_edge(nx_graph: nx.Graph, subject, predicate, obj):
     edge_data = {
-        "label": str(predicate).split("#")[-1]
-        if "#" in predicate
-        else str(predicate).split("/")[-1]
+        "label": (
+            CONSIST_OF["label"]
+            if str(predicate) == CONSIST_OF["iri"]
+            else SUBCLUSTER_OF["label"]
+            if str(predicate) == SUBCLUSTER_OF["iri"]
+            else CLUSTER["label"]
+            if str(predicate) == CLUSTER["iri"]
+            else str(predicate).split("#")[-1]
+            if predicate and "#" in predicate
+            else str(predicate).split("/")[-1]
+        )
     }
     nx_graph.add_edge(
         str(subject),
@@ -15,8 +34,9 @@ def add_edge(nx_graph: nx.Graph, subject, predicate, obj):
     )
 
 
-def add_node(nx_graph: nx.Graph, subject, obj):
-    nx_graph.add_node(str(subject), label=str(obj))
+def add_node(nx_graph: nx.Graph, subject, annotation):
+    # nx_graph.add_node(str(subject), annotation=str(obj))
+    nx_graph.add_node(str(subject), **annotation)
 
 
 def add_outgoing_edges_to_subgraph(graph, predicate_uri=None):
@@ -61,6 +81,7 @@ def find_and_rotate_center_layout(graph):
     rotated_pos = {node: (2 * x_center - x, 2 * y_center - y) for node, (x, y) in pos.items()}
     return rotated_pos
 
+
 def generate_subgraph(graph, predicate_uri, stack, bottom_up):
     subgraph = Graph()
     visited = set()
@@ -70,7 +91,7 @@ def generate_subgraph(graph, predicate_uri, stack, bottom_up):
             visited.add(node)
             for s, p, o in graph.triples((node, predicate_uri, None)):
                 # Add all outgoing edges of the current node
-                if isinstance(o, Literal):
+                if isinstance(o, Literal) or p == RDF.type and not isinstance(o, BNode):
                     subgraph.add((s, p, o))
             if bottom_up:
                 triples = graph.triples((node, predicate_uri, None))
@@ -90,22 +111,9 @@ def generate_subgraph(graph, predicate_uri, stack, bottom_up):
                         stack.append(_o)
                     else:
                         stack.append(_s)
-        # for s, p, next_node in graph.triples((node, predicate_uri, None)):
-        #     if not isinstance(next_node, BNode):
-        #         stack.append(next_node)
-        #     else:
-        #         _p = next(graph.objects(next_node, OWL.onProperty))
-        #         _o = next(graph.objects(next_node, OWL.someValuesFrom))
-        #         subgraph.add(
-        #             (
-        #                 node,
-        #                 _p,
-        #                 _o,
-        #             )
-        #         )
-        #         stack.append(_o)
     return subgraph
 
+
 def select_node_with_property(graph: Graph, _property: str, value: str):
     ns = Namespace({k: v for k, v in graph.namespaces()}.get("ns"))
     if _property == "label":

pandasaurus_cxg/graph_generator/graph_predicates.py

@@ -1,4 +1,4 @@
-CONSIST_OF = {"iri": "http://purl.obolibrary.org/obo/RO_0002473", "label": "composed_primarily_of"}
+CONSIST_OF = {"iri": "http://purl.obolibrary.org/obo/RO_0002473", "label": "composed primarily of"}
 
 SUBCLUSTER_OF = {"iri": "http://purl.obolibrary.org/obo/RO_0015003", "label": "subcluster of"}