neighborhood field removed from string-relations endpoint

Author: mauri101-Ar

README.md

@@ -696,7 +696,6 @@ For a given gene, this service gets from the String database a list of genes and
   - Content: The response you get is a list of relations containing the targeted gene. More information about each field in the response and how the different scores are calculated can be found in the [scientific publication](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825434/) of the STRING database. Unless otherwise indicated in this documentation, values for fields are scores in the range 1-1000.  
     - `gene_1`: Gene 1 in the bidirectional relationship.
     - `gene_2`: Gene 2 in the bidirectional relationship.
-    - `neighborhood`: It will always come with a NULL value since STRING does not calculate this data for Eukaryotic organisms.
     - `neighborhood_transferred`: score  reflecting the strength of supporting evidence from neighborhood done in other organisms.
     - `fusion`: score that is derived from fused proteins in other species.
     - `cooccurence`: is a type of score that is derived from similar absence/presence patterns of genes in different species.
@@ -734,7 +733,6 @@ For a given gene, this service gets from the String database a list of genes and
                   "gene_1": "MX2",
                   "gene_2": "MX1",
                   "homology": 961,
-                  "neighborhood": null,
                   "neighborhood_transferred": null,
                   "textmining": 77,
                   "textmining_transferred": 102
@@ -752,7 +750,6 @@ For a given gene, this service gets from the String database a list of genes and
                   "gene_1": "MX2",
                   "gene_2": "ISG15",
                   "homology": null,
-                  "neighborhood": null,
                   "neighborhood_transferred": null,
                   "textmining": 862,
                   "textmining_transferred": 162

bio-api/bioapi.py

@@ -624,7 +624,7 @@ def associated_string_genes(gene_symbol: str, min_combined_score: int = 400) ->
             "gene_1": gene_symbol,
             "combined_score": {"$gt": min_combined_score}
         },
-        {"_id": 0}
+        {"_id": 0, "neighborhood": 0}
     )
     res = list(relations)
     gene_list = [relation["gene_2"] for relation in relations]
@@ -633,7 +633,7 @@ def associated_string_genes(gene_symbol: str, min_combined_score: int = 400) ->
             "gene_2": gene_symbol,
             "combined_score": {"$gt": min_combined_score}
         },
-        {"_id": 0}
+        {"_id": 0, "neighborhood": 0}
     )
     res.extend(list(relations_2))
 

databases/string/string2mongodb.py

@@ -54,15 +54,16 @@
 gene_relations = []
 for line in tqdm(protein_relations):
     line = line.split(" ")
+    line.pop(2)
     if not skipped_first_line:
         fields = line
         fields[0] = "gene_1"
         fields[1] = "gene_2"
-        fields[15] = "combined_score"
+        fields[14] = "combined_score"
         skipped_first_line = True
     else:
         rel = {}
-        for f in range(16):
+        for f in range(15):
             if f <= 1:
                 rel[fields[f]] = alias_dict[line[f]]
             elif int(line[f]) > 0: