improved classify page and cspec brca assays annotation

resources/backups/database_dumper/dump_database.sh

@@ -90,9 +90,9 @@ then
     echo $DATE > $SCRIPTPATH/most_recent_dump.txt
 fi
 
-if [ "${WEBAPP_ENV}" == "prod" ]
+if [ "${WEBAPP_ENV}" == "prod" ] || [ "${WEBAPP_ENV}" == "demo" ]
 then
-    dump_path=$SCRIPTPATH/prod
+    dump_path=$SCRIPTPATH/$WEBAPP_ENV
     mkdir -p $dump_path
     dump_name=production-dump-$DATE.sql
 

src/annotation_service/annotation_jobs/automatic_classification_job.py

@@ -316,7 +316,7 @@ def get_autoclass_json(self, variant_id, conn: Connection) -> str:
                 minigene = assay.get_metadata_value("minigene", "False") == "True"
                 patient_rna = assay.get_metadata_value("patient_rna", "False") == "True"
                 allelic = assay.get_metadata_value("allele_specific", "False")
-                quantification = functions.percent_to_decimal(assay.metadata.get("minimal_percentage", None))
+                quantification = functions.percent_to_decimal(assay.get_metadata_value("minimal_percentage", None))
                 all_splicing_assays.append({"minigene": minigene,
                                             "patient_rna": patient_rna,
                                             "allelic": allelic,

src/frontend_celery/webapp/static/css/colors.css

@@ -171,7 +171,13 @@ input[type=checkbox]:checked + label.btn-ba {
     background-color: #000d58;
 }
 
-
+/*
+input {
+    appearance: unset;
+    -webkit-appearance: unset;
+    -moz-appearance: unset;
+}
+*/
 
 .btn-check:disabled + label.acmg-button {
     color: rgb(170, 170, 170);

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

@@ -328,6 +328,7 @@ $(document).ready(function() {
     });
 
     add_default_for_important_information()
+    hide_important_information_heading()
 });
 
 
@@ -342,8 +343,10 @@ function add_default_for_important_information() {
             $(this).append(default_empty)
         }
     })
+
 }
 
+
 // update global scheme field variable
 function update_scheme_field_variable() {
     scheme = $('#scheme').val()
@@ -427,10 +430,12 @@ function set_user_selection_counts(scheme) {
             var selected_criteria = scheme_with_info['criteria'] ?? [] // propagate the above
             for (var i in selected_criteria) {
                 var criterium = selected_criteria[i]
-                var criterium_id = criterium['name']
-                var count_label = document.getElementById('users_selected_' + criterium_id)
-                count_label.innerText = parseInt(count_label.innerText) + 1
-                count_label.hidden = false;
+                if (criterium["state"] == "selected") {
+                    var criterium_id = criterium['name']
+                    var count_label = document.getElementById('users_selected_' + criterium_id)
+                    count_label.innerText = parseInt(count_label.innerText) + 1
+                    count_label.hidden = false;
+                }
             }
         }
     }
@@ -459,8 +464,28 @@ function preselect_criteria_from_database(scheme) {
     if (typeof current_scheme_with_info !== "undefined") { // only preselect if there is data for it
         selected_criteria = current_scheme_with_info['scheme']['criteria']
         preselect_criteria_from_list(selected_criteria)
+        remove_criterium_button_backgrounds() 
     }
+}
 
+function remove_criterium_button_backgrounds() {
+    $(".acmg-button").each(function() {
+        var criterium_label = this
+        var all_btn_classes = []
+        for (var i = 0; i < criterium_label.classList.length; i++) {
+            var current_class = criterium_label.classList[i]
+            if (current_class.indexOf("btn-") >= 0) {
+                all_btn_classes.push(current_class)
+                //criterium_label.classList.remove(current_class)
+                //criterium_label.classList.toggle(current_class)
+            }
+        }
+        all_btn_classes.pop()
+
+        all_btn_classes.forEach(css_class => {
+            criterium_label.classList.remove(css_class)
+        });
+    })
 }
 
 function preselect_criteria_from_list(selected_criteria, is_intermediate = false) {
@@ -478,6 +503,8 @@ function preselect_criteria_from_list(selected_criteria, is_intermediate = false
             set_criterium(criterium_id, state, is_intermediate)
         }
     }
+
+
 }
 
 
@@ -629,6 +656,12 @@ function hide_all_information() {
     })
 }
 
+function hide_important_information_heading() {
+    if ($("#important_information_container").find("visually_hidden").length > 0) {
+        document.getElementById('important_information_heading').classList.remove('visually_hidden')
+    }
+}
+
 function revert_strength_selects() {
     var all_buttons = document.querySelectorAll('.btn-check')
     for (var i = 0; i < all_buttons.length; i++) {
@@ -1204,6 +1237,7 @@ function copy_evidence(obj) {
 
     select_criterium_check.value = state
     set_criterium(criterium_id, state, is_intermediate = true)
+    update_classification_preview()
 }
 
 function add_user_acmg_classification_details(criterium_id) {
@@ -1568,14 +1602,17 @@ function set_criterium(criterium_id, state, is_intermediate = false) {
 
     state_check.value = state
 
-    console.log("set_criterium: " + criterium_id + " to state: " + state)
+    console.log("set_criterium: " + criterium_id + " to state: " + state + " with strength: " + strength_check.value)
 
     update_criterium_button_label(criterium_id)
+    //remove_criterium_button_background(criterium_id)
     update_criterium_button_background(criterium_id)
 
     if (!(['unchecked', 'unselected'].includes(previous_state) && ['unchecked', 'unselected'].includes(state))) {
         update_mutual_criteria(criterium_id)
     }
+
+
 }
 
 

src/frontend_celery/webapp/static/js/variant_addition.js

@@ -279,8 +279,8 @@ function show_heredicare_upload_status(color_class, summary, inner_text) {
     const pill_holder_id = "heredicare_status_pill_holder"
     const pill_id = "heredicare_status_pill"
     var prepend_html = null
-    
-    if (summary["needs_upload"] && ["error", "api_error", "success", "requested", "multiple stati"].includes(summary["status"])) {
+
+    if (summary["needs_upload"] && ["error", "api_error", "success", "requested", "multiple stati", "unknown"].includes(summary["status"])) {
         prepend_html = create_exclamation_mark()
         add_tooltip(prepend_html, "The consensus classification needs to be uploaded to HerediCaRe!")
     }

src/frontend_celery/webapp/templates/index.html

@@ -95,9 +95,19 @@ <h4>Changelog</h4>
 
     <div class="underline">v 1.14.5 ()</div>
     <div>
+        General changes:
+        <ul>
+            <li>Removed "Important Information" heading on classify page if there is no important information to show</li>
+            <li>CSpecBRCA splicing assay quantification is now the sum of percent abberant transcript. It was the minimal value previously.</li>
+            <li>CSpecBRCA splicing assay quantification is now explicitly set to 0 if the assay is minigene or patient RNA and the result is "no abberation" which is not ignored</li>
+            <li>Consensus classify count labels now only count criteria which were selected and ignore unselected criteria</li>
+        </ul>
         Bugfixes:
         <ul>
             <li>Fixed a bug where assay annotations would not be considered for automatic classification</li>
+            <li>Fixed a bug which was causing criteria buttons to show the default color after page reload even though the strength was non-default. This problem only existed in Firefox.</li>
+            <li>When copying evidence on the consensus classify page, the classifcation preview would not update</li>
+            <li>Needs HerediCaRe upload for consensus classifications was not showing when there was no HerediCaRe submission</li>
         </ul>
     </div>
 

src/frontend_celery/webapp/templates/variant/classify.html

@@ -112,8 +112,8 @@ <h4 class="sst">Description:</h4>
                             <div id="additional_content" class="sst"></div>
                             <h4 class="bst">Evidence:</h4>
                             <textarea type="text" id="criteria_evidence" class="form-control sst" placeholder="insert evidence..."></textarea>
-                            <h4 class="bst">Important information</h4>
-                            <div>
+                            <h4 id="important_information_heading" class="bst visually_hidden">Important information</h4>
+                            <div id="important_information_container">
                                 <div class="sst important_information" id="splicing_info">
                                     <h5>Splicing</h5>
                                     {% set current_annotations = variant.annotations.get_group('Splicing') %}

tools/db_converter_CSpec_splicing_assays.py

@@ -54,6 +54,7 @@
     percent_aberrant_transcript = parts[13]
     allele_specific = parts[14]
     comment = parts[15]
+    result = parts[9]
 
 
     transcript = gene2transcript[gene]
@@ -74,17 +75,22 @@
         for percentage in re.findall(r'[\d]+[.,\d]+|[\d]*[.][\d]+|[\d]+', percentage):
             percentage = float(percentage)
             all_percentages_curated.append(percentage)
-    minimal_percentage = ""
+    quantification = ""
     if len(all_percentages_curated) > 0:
-        minimal_percentage = str(min(all_percentages_curated))
+        quantification = str(sum(all_percentages_curated))
+    else: # add quantification 0% if not stated
+        if minigene == "Y" or patient_rna == "Y":
+            if result == "no aberration" and comment != "Result ignored (design limitations to detect aberration)":
+                quantification = "0"
 
 
     splicing_assay = [functions.encode_vcf(patient_rna),
                       functions.encode_vcf(minigene), 
-                      functions.encode_vcf(minimal_percentage),
+                      functions.encode_vcf(quantification),
                       functions.encode_vcf(allele_specific), 
                       functions.encode_vcf(comment),
-                      functions.encode_vcf("https://pubmed.ncbi.nlm.nih.gov/" + pmid)]
+                      functions.encode_vcf("https://pubmed.ncbi.nlm.nih.gov/" + pmid),
+                      functions.encode_vcf(result)]
     splicing_assay = "|".join(splicing_assay)
 
     csv_line_parts = [transcript,