ENH map_to_aro now returns None if no match

Handle mapping not in ARO in map_to_aro function & simplify map_to_aro() code

The previous `map_to_aro` code also dealt with multiple ARO mappings which is not an issue anymore since gene clusters, reverse complements and CDSs being dealt as contigs have been solved for all databases (except megares which is currently being looked into)

Also, removes unnecessary warning in map_to_aro and document return of empty list if ARO invalid in map_to_aro

argnorm/lib.py

@@ -50,6 +50,8 @@ def map_to_aro(gene, database):
 
     Returns:
         ARO[result] (pronto.term.Term): A pronto term with the ARO number of input gene. ARO number can be accessed using 'id' attribute and gene name can be accessed using 'name' attribute.
+
+        If ARO mapping is doesn't exist, None is returned.
     """
 
     if database not in ['ncbi', 'deeparg', 'resfinder', 'sarg', 'megares', 'argannot']:
@@ -62,10 +64,8 @@ def map_to_aro(gene, database):
     except KeyError:
         raise Exception(f'{gene} is not in {database} database')
     else:
-        # Dealing with duplicated genes in ARO mapping table.
-        # Getting only one ARO number
+        if pd.isna(result):
+            return None
+
         ARO = pronto.Ontology.from_obo_library('aro.obo')
-        if type(result) != str:
-            return ARO[list(set(result))[0]]
-        else:
-            return ARO[result]
+        return ARO.get(result)

tests/test_lib.py

@@ -7,15 +7,17 @@ def test_map_to_aro():
         ["(AGly)AAC(6')-Isa:NG_047311:101-574:474", 'argannot'],
         ["MEG_21|Drugs|Aminoglycosides|Aminoglycoside_N-acetyltransferases|AAC3", 'megares'],
         ["1028085756|WP_063844287.1|1|1|cpt|cpt|phosphotransferase|2|CHLORAMPHENICOL|PHENICOL|chloramphenicol_phosphotransferase_CPT", 'ncbi'],
-        ["gb|AAG57600.1|ARO:3000318|mphB", "sarg"]
+        ["gb|AAG57600.1|ARO:3000318|mphB", "sarg"],
+        ["(Phe)cpt_strepv:U09991:AAB36569:1412-1948:537", "argannot"]
     ]
 
     ARO = pronto.Ontology.from_obo_library('aro.obo')
     expected_output = [
         ARO.get_term('ARO:3002563'),
         ARO.get_term('ARO:3004623'),
         ARO.get_term('ARO:3000249'),
-        ARO.get_term('ARO:3000318')
+        ARO.get_term('ARO:3000318'),
+        None
     ]
 
     for t, e in zip(test_cases, expected_output):