Merge pull request #46 from BackofenLab/workMalek

Updated functional enrichment (With genes now)

backend/src/enrichment.py

@@ -13,32 +13,32 @@
 from util.stopwatch import Stopwatch
 
 
-def calc_proteins_pval(curr, alpha, in_pr, bg_proteins, num_in_prot):
+def calc_genes_pval(curr, alpha, in_gene, bg_genes, num_in_genes):
     # Lists are read as strings, evaluate to lists using JSON.
     # alternative is using eval() which is slower
-    prot_list = curr.replace("'", '"')
-    prot_list = json.loads(prot_list)
+    gene_list = curr.replace("'", '"')
+    gene_list = json.loads(gene_list)
 
     # get the protein length of term
-    num_term_prot = len(prot_list)
+    num_term_prot = len(gene_list)
 
     # Get intersection of proteins
-    prots_term = list(set(prot_list) & in_pr)
-    num_inter = len(prots_term)
+    gene_term = list(set(gene_list) & in_gene)
+    num_inter = len(gene_term)
 
     if num_inter == 0:
         # Condition reduces runtime by 60%, needs to be tested carefully!
         # Check if enriched terms with and without that condition are
         # more or less the same
         p_value = alpha
     else:
-        p_value = hypergeo_testing(num_inter, bg_proteins, num_term_prot, num_in_prot)
+        p_value = hypergeo_testing(num_inter, bg_genes, num_term_prot, num_in_genes)
 
-    return (p_value, prots_term)
+    return (p_value, gene_term)
 
 
 @lru_cache(maxsize=None)
-def hypergeo_testing(intersec, total_proteins, term_proteins, in_proteins):
+def hypergeo_testing(intersec, total_genes, term_genes, in_genes):
     """Perfoms hypergeometric testing and returns a p_value
     Args:
         intersec(int): number of intersections between input and
@@ -52,16 +52,16 @@ def hypergeo_testing(intersec, total_proteins, term_proteins, in_proteins):
     mpmath.mp.dps = 64
 
     # Do the relevant calculations for the hypergeometric testing
-    term_one = mpmath.binomial(term_proteins, intersec)
-    term_two = mpmath.binomial(total_proteins - term_proteins, in_proteins - intersec)
-    term_three = mpmath.binomial(total_proteins, in_proteins)
+    term_one = mpmath.binomial(term_genes, intersec)
+    term_two = mpmath.binomial(total_genes - term_genes, in_genes - intersec)
+    term_three = mpmath.binomial(total_genes, in_genes)
 
     # Calculate final p_value
     p_value = (term_one * term_two) / term_three
     return float(p_value)
 
 
-def functional_enrichment(driver: neo4j.Driver, in_proteins, species_id: Any):
+def functional_enrichment(driver: neo4j.Driver, in_genes, species_id: Any):
     """inhouse functional enrichment - performs gene set enrichment analysis
     for a given set of proteins. Calculates p-value and Benjamini-Hochberg FDR
     for every functional term
@@ -76,9 +76,9 @@ def functional_enrichment(driver: neo4j.Driver, in_proteins, species_id: Any):
     stopwatch = Stopwatch()
 
     # Get number of all proteins in the organism (from Cypher)
-    bg_proteins = queries.get_number_of_proteins(driver, species_id)
-    num_in_prot = len(in_proteins)
-    prots = set(in_proteins)
+    bg_proteins = queries.get_number_of_genes(driver, species_id)
+    num_in_gene = len(in_genes)
+    genes = set(in_genes)
     # pandas DataFrames for nodes and edges
     csv.field_size_limit(sys.maxsize)
 
@@ -92,18 +92,18 @@ def functional_enrichment(driver: neo4j.Driver, in_proteins, species_id: Any):
     alpha = 0.05
 
     # calculate p_value for all terms
-    new_prots = []
+    new_genes = []
     new_p = []
-    arguments = [(value, alpha, prots, bg_proteins, num_in_prot) for value in df_terms["proteins"]]
+    arguments = [(value, alpha, genes, bg_proteins, num_in_gene) for value in df_terms["symbols"]]
 
     with multiprocessing.Pool() as pool:
         # Apply the function to each input value in parallel and collect the results
-        for a, b in pool.starmap(calc_proteins_pval, arguments):
+        for a, b in pool.starmap(calc_genes_pval, arguments):
             new_p.append(a)
-            new_prots.append(b)
+            new_genes.append(b)
 
     # Update Dataframe and sort by p_value (descending)
-    df_terms["proteins"] = new_prots
+    df_terms["genes"] = new_genes
     df_terms["p_value"] = new_p
     df_terms.sort_values(by="p_value", ascending=False, inplace=True)
     df_terms = df_terms.reset_index(drop=True)

backend/src/main.py

@@ -50,11 +50,11 @@ def files(path):
 @app.route("/api/subgraph/enrichment", methods=["POST"])
 def proteins_enrichment():
     driver = database.get_driver()
-    proteins = request.form.get("proteins").split(",")
+    genes = request.form.get("genes").split(",")
     species_id = int(request.form.get("species_id"))
 
     # in-house functional enrichment
-    list_enrichment = enrichment.functional_enrichment(driver, proteins, species_id)
+    list_enrichment = enrichment.functional_enrichment(driver, genes, species_id)
 
     # STRING API functional enrichment
     """df_enrichment = stringdb.functional_enrichment(proteins, species_id)
@@ -106,7 +106,9 @@ def proteins_subgraph_api():
 
     stopwatch.round("Neo4j")
 
-    nodes = pd.DataFrame(proteins).rename(columns={"ENSEMBL": "external_id"}).drop_duplicates(subset="external_id")
+    nodes = (
+        pd.DataFrame(proteins).rename(columns={"ENSEMBL_PROTEIN": "external_id"}).drop_duplicates(subset="external_id")
+    )
 
     edges = pd.DataFrame({"source": source, "target": target, "score": score})
     edges = edges.drop_duplicates(subset=["source", "target"])

backend/src/pathway_data/data/Overlap/HumanDATA/functional_terms_overlap_time_cost.txt

@@ -1 +1 @@
-time cost: 1.7737935715251498 hours
+time cost: 2.39641605105665 hours

backend/src/pathway_data/data/Overlap/MusMusculusDATA/functional_terms_overlap_time_cost.txt

@@ -1 +1 @@
-time cost: 1.7013362871938282 hours
+time cost: 2.5310714825656677 hours

backend/src/pathway_data/data/kegg_compounds.human.tsv

@@ -7,6 +7,7 @@ C00036	Oxaloacetate
 C00068	Thiamin diphosphate
 C00074	Phosphoenolpyruvate
 C00084	Acetaldehyde
+C00085	D-Fructose 6-phosphate
 C00103	D-Glucose 1-phosphate
 C00111	Glycerone phosphate
 C00118	D-Glyceraldehyde 3-phosphate
@@ -15,15 +16,14 @@ C00197	3-Phospho-D-glycerate
 C00221	beta-D-Glucose
 C00236	3-Phospho-D-glyceroyl phosphate
 C00267	alpha-D-Glucose
+C00354	D-Fructose 1,6-bisphosphate
 C00469	Ethanol
 C00631	2-Phospho-D-glycerate
 C00668	alpha-D-Glucose 6-phosphate
 C01159	2,3-Bisphospho-D-glycerate
 C01172	beta-D-Glucose 6-phosphate
 C01451	Salicin
 C05125	2-(alpha-Hydroxyethyl)thiamine diphosphate
-C05345	beta-D-Fructose 6-phosphate
-C05378	beta-D-Fructose 1,6-bisphosphate
 C06186	Arbutin
 C06187	Arbutin 6-phosphate
 C06188	Salicin 6-phosphate
@@ -61,6 +61,7 @@ C01182	D-Ribulose 1,5-bisphosphate
 C01218	6-Phospho-2-dehydro-D-gluconate
 C01236	D-Glucono-1,5-lactone 6-phosphate
 C01801	Deoxyribose
+C02076	Sedoheptulose
 C03752	2-Amino-2-deoxy-D-gluconate
 C04442	2-Dehydro-3-deoxy-6-phospho-D-gluconate
 C05382	Sedoheptulose 7-phosphate
@@ -118,6 +119,7 @@ C14899	3-Dehydro-L-gulonate 6-phosphate
 C15930	L-Galactonate
 C20680	2-Dehydro-3-deoxy-L-galactonate
 C22337	D-Ribulose 1-phosphate
+C22712	4-Deoxy-L-erythro-hex-4-enopyranuronate
 C00095	D-Fructose
 C00096	GDP-mannose
 C00159	D-Mannose
@@ -167,7 +169,6 @@ C18096	D-Allulose 6-phosphate
 C20781	2,4-Diketo-3-deoxy-L-fuconate
 C20836	beta-L-Fucopyranose
 C00052	UDP-alpha-D-galactose
-C00085	D-Fructose 6-phosphate
 C00089	Sucrose
 C00124	D-Galactose
 C00137	myo-Inositol
@@ -285,7 +286,6 @@ C01623	UDP-apiose
 C01674	Chitobiose
 C01788	CDP-abequose
 C02199	UDP-L-rhamnose
-C02336	beta-D-Fructose
 C02352	1,4-beta-D-Xylan
 C02474	Arabinan
 C02713	N-Acetylmuramate
@@ -1798,7 +1798,6 @@ C00230	3,4-Dihydroxybenzoate
 C00251	Chorismate
 C00254	Prephenate
 C00296	Quinate
-C00354	D-Fructose 1,6-bisphosphate
 C00493	Shikimate
 C00587	3-Hydroxybenzoate
 C00826	L-Arogenate
@@ -3175,6 +3174,7 @@ C15891	Endomorphin-2
 C15995	Bombesin
 C16511	L-Homocysteic acid
 C16512	Palmitoylethanolamide
+C18178	Resolvin D1
 C11378	Ubiquinone-10
 C16844	Hydroxyl radical
 C21478	Erastin

backend/src/pathway_data/data/kegg_compounds.mouse.tsv

@@ -7,6 +7,7 @@ C00036	Oxaloacetate
 C00068	Thiamin diphosphate
 C00074	Phosphoenolpyruvate
 C00084	Acetaldehyde
+C00085	D-Fructose 6-phosphate
 C00103	D-Glucose 1-phosphate
 C00111	Glycerone phosphate
 C00118	D-Glyceraldehyde 3-phosphate
@@ -15,15 +16,14 @@ C00197	3-Phospho-D-glycerate
 C00221	beta-D-Glucose
 C00236	3-Phospho-D-glyceroyl phosphate
 C00267	alpha-D-Glucose
+C00354	D-Fructose 1,6-bisphosphate
 C00469	Ethanol
 C00631	2-Phospho-D-glycerate
 C00668	alpha-D-Glucose 6-phosphate
 C01159	2,3-Bisphospho-D-glycerate
 C01172	beta-D-Glucose 6-phosphate
 C01451	Salicin
 C05125	2-(alpha-Hydroxyethyl)thiamine diphosphate
-C05345	beta-D-Fructose 6-phosphate
-C05378	beta-D-Fructose 1,6-bisphosphate
 C06186	Arbutin
 C06187	Arbutin 6-phosphate
 C06188	Salicin 6-phosphate
@@ -61,6 +61,7 @@ C01182	D-Ribulose 1,5-bisphosphate
 C01218	6-Phospho-2-dehydro-D-gluconate
 C01236	D-Glucono-1,5-lactone 6-phosphate
 C01801	Deoxyribose
+C02076	Sedoheptulose
 C03752	2-Amino-2-deoxy-D-gluconate
 C04442	2-Dehydro-3-deoxy-6-phospho-D-gluconate
 C05382	Sedoheptulose 7-phosphate
@@ -118,6 +119,7 @@ C14899	3-Dehydro-L-gulonate 6-phosphate
 C15930	L-Galactonate
 C20680	2-Dehydro-3-deoxy-L-galactonate
 C22337	D-Ribulose 1-phosphate
+C22712	4-Deoxy-L-erythro-hex-4-enopyranuronate
 C00095	D-Fructose
 C00096	GDP-mannose
 C00159	D-Mannose
@@ -167,7 +169,6 @@ C18096	D-Allulose 6-phosphate
 C20781	2,4-Diketo-3-deoxy-L-fuconate
 C20836	beta-L-Fucopyranose
 C00052	UDP-alpha-D-galactose
-C00085	D-Fructose 6-phosphate
 C00089	Sucrose
 C00124	D-Galactose
 C00137	myo-Inositol
@@ -285,7 +286,6 @@ C01623	UDP-apiose
 C01674	Chitobiose
 C01788	CDP-abequose
 C02199	UDP-L-rhamnose
-C02336	beta-D-Fructose
 C02352	1,4-beta-D-Xylan
 C02474	Arabinan
 C02713	N-Acetylmuramate
@@ -1798,7 +1798,6 @@ C00230	3,4-Dihydroxybenzoate
 C00251	Chorismate
 C00254	Prephenate
 C00296	Quinate
-C00354	D-Fructose 1,6-bisphosphate
 C00493	Shikimate
 C00587	3-Hydroxybenzoate
 C00826	L-Arogenate
@@ -3175,6 +3174,7 @@ C15891	Endomorphin-2
 C15995	Bombesin
 C16511	L-Homocysteic acid
 C16512	Palmitoylethanolamide
+C18178	Resolvin D1
 C11378	Ubiquinone-10
 C16844	Hydroxyl radical
 C21478	Erastin