minor improvements

src/frontend_celery/start_keycloak.sh

@@ -59,8 +59,8 @@ keycloak_path=$tools/keycloak
 
 if [ "${WEBAPP_ENV}" == "dev" ]
 then
-    export NO_PROXY=srv018.img.med.uni-tuebingen.de
-    $keycloak_path/bin/kc.sh start-dev --hostname srv018.img.med.uni-tuebingen.de --http-port 5050 #--features=admin-fine-grained-authz # --log-level debug
+    export NO_PROXY=srv020.img.med.uni-tuebingen.de
+    $keycloak_path/bin/kc.sh start-dev --hostname srv020.img.med.uni-tuebingen.de --http-port 5050 #--features=admin-fine-grained-authz # --log-level debug
 fi
 
 if [ "${WEBAPP_ENV}" == "prod" ]

src/frontend_celery/webapp/io/download_routes.py

@@ -285,18 +285,21 @@ def calculate_class(scheme_type, selected_classes = ''):
     if scheme_type == 'task-force':
         final_class = decide_for_class_task_force(selected_classes)
 
-    if scheme_type == 'acmg-enigma-brca1':
+    if 'acmg' in scheme_type:
         selected_classes = [re.sub(r'[0-9]+', '', x) for x in selected_classes] # remove numbers from critera if there are any
         class_counts = get_class_counts(selected_classes) # count how often we have each strength
-        #print(class_counts)
-        possible_classes = get_possible_classes_enigma_brca1(class_counts) # get a set of possible classes depending on selected criteria
-        final_class = decide_for_class_acmg(possible_classes) # decide for class
 
-    if scheme_type == 'acmg-enigma-brca2':
-        selected_classes = [re.sub(r'[0-9]+', '', x) for x in selected_classes] # remove numbers from critera if there are any
-        class_counts = get_class_counts(selected_classes) # count how often we have each strength
-        #print(class_counts)
-        possible_classes = get_possible_classes_enigma_brca2(class_counts) # get a set of possible classes depending on selected criteria
+        if 'brca1' in scheme_type:
+            possible_classes = get_possible_classes_enigma_brca1(class_counts) # get a set of possible classes depending on selected criteria
+        elif 'brca2' in scheme_type:
+            possible_classes = get_possible_classes_enigma_brca2(class_counts) # get a set of possible classes depending on selected criteria
+        elif 'palb2' in scheme_type:
+            possible_classes = get_possible_classes_enigma_palb2(class_counts) # get a set of possible classes depending on selected criteria
+        elif 'tp53' in scheme_type:
+            possible_classes = get_possible_classes_enigma_tp53(class_counts) # get a set of possible classes depending on selected criteria
+        else:
+            raise RuntimeError('The class could not be calculated with given parameters. Did you specify a supported scheme? (either "acmg" or VUS "task-force" based)')
+
         final_class = decide_for_class_acmg(possible_classes) # decide for class
 
     if final_class is None:
@@ -308,6 +311,108 @@ def calculate_class(scheme_type, selected_classes = ''):
 
 
 
+def get_possible_classes_enigma_tp53(class_counts):
+
+    possible_classes = set()
+
+    # numbering comments are nubmers from the official ACMG paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4544753/ (TABLE 5)
+    # pathogenic
+    if class_counts['pvs'] == 1: # 1
+        if class_counts['ps'] == 1 or class_counts['pm'] >= 2 or (class_counts['pm'] == 1 and class_counts['pp'] == 1) or class_counts['pp'] >= 2:
+            possible_classes.add(5)
+    if class_counts['ps'] >= 2: # 2 
+        possible_classes.add(5)
+    if class_counts['ps'] == 1: # 3
+        if class_counts['pm'] >= 3 or (class_counts['pm'] == 2 and class_counts['pp'] >= 2) or (class_counts['pm'] == 1 and class_counts['pp'] >= 4):
+            possible_classes.add(5)
+
+    # likely pathogenic
+    if class_counts['ps'] == 1:
+        if class_counts['pm'] >= 1 or class_counts['pp'] >= 2: # 3
+            possible_classes.add(4)
+    if class_counts['pm'] >= 3: # 4
+        possible_classes.add(4)
+    if class_counts['pm'] == 2 and class_counts['pp'] >= 2: # 5
+        possible_classes.add(4)
+    if class_counts['pm'] == 1 and class_counts['pp'] >= 4: # 6
+        possible_classes.add(4)
+    if class_counts['pvs'] == 1:
+        if class_counts['pm'] == 1 or class_counts['pp'] == 1:
+            possible_classes.add(4)
+
+    # benign
+    if class_counts['ba'] == 1: # 1
+        possible_classes.add(1)
+    if class_counts['bs'] >= 2: # 2
+        possible_classes.add(1)
+
+    # likely benign
+    if class_counts['bs'] == 1 and class_counts['bp'] == 1: # 1
+        possible_classes.add(2)
+    if class_counts['bp'] >= 2: # 2
+        possible_classes.add(2)
+
+    #print(class_counts)
+    #print(possible_classes)
+
+    return possible_classes
+
+
+
+
+def get_possible_classes_enigma_palb2(class_counts):
+
+    possible_classes = set()
+
+    # numbering comments are nubmers from the official ACMG paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4544753/ (TABLE 5)
+    # pathogenic
+    if class_counts['pvs'] == 1: # 1
+        if class_counts['ps'] == 1 or class_counts['pm'] >= 2 or (class_counts['pm'] == 1 and class_counts['pp'] == 1) or class_counts['pp'] >= 2:
+            possible_classes.add(5)
+    if class_counts['ps'] >= 2: # 2 
+        possible_classes.add(5)
+    if class_counts['ps'] == 1: # 3
+        if class_counts['pm'] >= 3 or (class_counts['pm'] == 2 and class_counts['pp'] >= 2) or (class_counts['pm'] == 1 and class_counts['pp'] >= 4):
+            possible_classes.add(5)
+
+    # likely pathogenic
+    if class_counts['ps'] == 1:
+        if class_counts['pm'] == 1 or class_counts['pp'] >= 2 or class_counts['pm'] == 2: # 3
+            possible_classes.add(4)
+    if class_counts['pm'] >= 3: # 4
+        possible_classes.add(4)
+    if class_counts['pm'] == 2 and class_counts['pp'] >= 2: # 5
+        possible_classes.add(4)
+    if class_counts['pm'] == 1 and class_counts['pp'] >= 4: # 6
+        possible_classes.add(4)
+    if class_counts['pvs'] == 1:
+        if class_counts['pm'] == 1 or class_counts['pp'] == 1:
+            possible_classes.add(4)
+
+    # benign
+    if class_counts['ba'] == 1: # 1
+        possible_classes.add(1)
+    if class_counts['bs'] >= 2: # 2
+        possible_classes.add(1)
+
+    # likely benign
+    if class_counts['bs'] == 1 and class_counts['bp'] == 1: # 1
+        possible_classes.add(2)
+    if class_counts['bp'] >= 2: # 2
+        possible_classes.add(2)
+    if class_counts['bs'] == 1: # 2
+        possible_classes.add(2)
+
+    #print(class_counts)
+    #print(possible_classes)
+
+    return possible_classes
+
+
+
+
+
+
 def get_possible_classes_enigma_brca2(class_counts):
 
     possible_classes = set()

src/frontend_celery/webapp/static/js/classify.js

@@ -724,7 +724,7 @@ function create_criteria_buttons() {
         var default_strength = current_criterium['default_strength']
 
         var criterium_type = criterium_id[0] // a task force criterium -> the type is determined by the first digit
-        if (scheme_type === 'acmg' || scheme_type === 'acmg-enigma-brca1'|| scheme_type === 'acmg-enigma-brca2') {
+        if (scheme_type.includes('acmg')) {
             criterium_type = criterium_id.replace(/\d+/g, '') // an acmg criterium. The type is determined by the first two or three letters
         }
 
@@ -769,7 +769,7 @@ function create_criteria_buttons() {
 // sort helper
 function compare_criteria() {
     return function(a, b) {
-        if (scheme_type === 'acmg' || scheme_type === 'acmg-enigma-brca1' || scheme_type === 'acmg-enigma-brca2') {
+        if (scheme_type.includes('acmg')) {
             const criterium_order = {'PVS': 1, 'PS': 2, 'PM': 3, 'PP': 4, 'BP': 5, 'BS': 6, 'BA': 7}
             const a_letters = a.slice(0, -1)
             const a_crit_num = parseInt(a.slice(-1))

src/frontend_celery/webapp/utils/create_classification_scheme.py

@@ -4,7 +4,7 @@
 from common.db_IO import Connection
 import common.functions as functions
 import json
-
+import argparse
 
 
 def insert_criterium_scheme(conn: Connection, data):
@@ -82,61 +82,9 @@ def get_criterium(all_criteria, criterium_name):
             return criterium
     return None
 
-if __name__ == "__main__":
-
-    conn = Connection(roles = ['super_user'])
-
-    data = json.loads(open("/mnt/storage2/users/ahdoebm1/HerediVar/resources/classification_schemes/ClinGen_BRCA1_v1.0.0.json").read())
-
-    """
-    data = {
-        'classification_scheme_id': "10", # leave blank to specify new scheme or provide id to specify an update
-        'name': "testscheme",
-        'display_name': "yoyotest",
-        'type': "acmg",
-        'reference': "#",
-        'criteria': [ # compute classification_scheme_id
-            {
-                "name": "PSVS1", # has to be unique because of the mutually exclusive criteria list
-                "description": "THIS IS A TEST",
-                "is_selectable": "1",
-                "relevant_info": "",
-                "strengths": [ # compute classification_criterium_id
-                    {
-                        'name': "pvs",
-                        'description': "pathogenic very strong",
-                        'is_default': "1"
-                    },
-                    {
-                        'name': "ps",
-                        'description': "pathogenic strong",
-                        'is_default': "0"
-                    }
-                ],
-                "mutually_exclusive_criteria": [ # list of criterium names
-                    "PS1"
-                ]
-            },
-
-            {
-                "name": "PS1", # has to be unique because of the mutually exclusive criteria list
-                "description": "ps1 test yoo",
-                "is_selectable": "1",
-                "relevant_info": "",
-                "strengths": [ # compute classification_criterium_id
-                    {
-                        'name': "ps",
-                        'description': "pathogenic strong",
-                        'is_default': "1"
-                    }
-                ],
-                "mutually_exclusive_criteria": [ # list of criterium names
-                    
-                ]
-            },
-        ]
-    }
-    """
+
+def insert_scheme(conn, data_path):
+    data = json.loads(open(data_path).read())
 
     classification_scheme_id = insert_criterium_scheme(conn, data)
     insert_criteria(conn, data, classification_scheme_id)
@@ -145,18 +93,35 @@ def get_criterium(all_criteria, criterium_name):
 
 
 
+parser = argparse.ArgumentParser(description="")
+parser.add_argument("-p", "--paths",  nargs="+", help="one or more paths to scheme .json files to be saved to the database")
 
 
+args = parser.parse_args()
 
+conn = Connection(roles = ['super_user'])
+data_paths = args.paths
 
+print(data_paths)
 
+for data_path in data_paths:
+    if not path.exists(data_path):
+        print("SKIPPING: path does not exist: " + data_path)
+        continue
+    insert_scheme(conn, data_path)
 
 
+#/mnt/storage2/users/ahdoebm1/HerediVar/resources/classification_schemes/ClinGen_BRCA1_v1.0.0.json
+#/mnt/storage2/users/ahdoebm1/HerediVar/resources/classification_schemes/ClinGen_BRCA2_v1.0.0.json
 
 
 
-
-
-
+#if __name__ == "__main__":
+#
+#    conn = Connection(roles = ['super_user'])
+#
+#    data_path = "/mnt/storage2/users/ahdoebm1/HerediVar/resources/classification_schemes/ClinGen_BRCA1_v1.0.0.json"
+#
+#    insert_scheme(conn, data_path)