Add ClinVar cache pipeline for variant health data

scripts/python/cache/clinvar_cache.py

@@ -0,0 +1,140 @@
+"""Cache data on variants related to human health, from NCBI ClinVar
+
+Example:
+python clinvar_cache.py
+"""
+
+import csv
+import json
+import gzip
+
+clinical_concerns = ['Likely_pathogenic', 'Pathogenic/Likely_pathogenic', 'Pathogenic']
+robust_review_statuses = [
+    'criteria_provided,_multiple_submitters,_no_conflicts',
+    'reviewed_by_expert_panel',
+    'practice_guideline'
+]
+
+disease_ids_and_names = []
+variant_types = []
+molecular_consequences = []
+
+def get_is_relevant(fields):
+    is_clinical_concern = False
+    is_robustly_reviewed = False
+    for field in fields:
+        [name, value] = field.split('=')
+
+        if name == 'CLNSIG' and value in clinical_concerns:
+            is_clinical_concern = True
+
+        if name == 'CLNREVSTAT' and value in robust_review_statuses:
+            is_robustly_reviewed = True
+
+    return is_clinical_concern and is_robustly_reviewed
+
+def trim_info_fields(fields):
+    slim_fields = []
+    names_to_keep = ['CLNREVSTAT', 'CLNSIG', 'CLNVC', 'MC', 'ORIGIN', 'RS']
+    disease_indexes = []
+    disease_names = []
+    disease_ids = []
+    for field in fields:
+        [name, value] = field.split('=')
+
+        if name == 'CLNDISDB': # "Clinical disease database"
+            entries = value.split('|')
+            for entry in entries:
+                full_values = entry.split(',')
+                has_mondo = False
+                for fv in full_values:
+                    split_fv = fv.split(':')
+                    db_name = split_fv[0]
+                    db_value = split_fv[-1]
+                    if db_name == 'MONDO':
+                        disease_ids.append(db_value)
+                        has_mondo = True
+                if not has_mondo:
+                    disease_ids.append('-1')
+
+        elif name == 'CLNDN': # "Clinical disease name"
+            disease_names = value.split('|')
+
+        elif name == 'CLNVC':
+            if value not in variant_types:
+                variant_types.append(value)
+            variant_type = variant_types.index(value)
+            slim_fields.append(str(variant_type))
+
+        elif name == 'MC':
+            entries = value.split(',')
+            slim_mc = []
+            for entry in entries:
+                if entry not in molecular_consequences:
+                    molecular_consequences.append(entry)
+                molecular_consequence = molecular_consequences.index(entry)
+                slim_mc.append(str(molecular_consequence))
+            slim_fields.append(','.join(slim_mc))
+
+        elif name in names_to_keep:
+            if name == 'CLNSIG':
+                value = clinical_concerns.index(value)
+            elif name == 'CLNREVSTAT':
+                value = robust_review_statuses.index(value)
+            slim_fields.append(str(value))
+
+    for (i, disease_id) in enumerate(disease_ids):
+        if disease_id == '-1':
+            continue
+        disease_name = disease_names[i]
+        disease_id_and_name = disease_id + '|' + disease_name
+        if disease_id_and_name not in disease_ids_and_names:
+            disease_ids_and_names.append(disease_id_and_name)
+        disease_index = disease_ids_and_names.index(disease_id_and_name)
+        disease_indexes.append(str(disease_index))
+
+    disease_indexes_string = ','.join(disease_indexes)
+    slim_fields.insert(0, disease_indexes_string)
+
+    slim_info = '\t'.join(slim_fields)
+    return slim_info
+
+output_rows = []
+
+# https://ftp.ncbi.nlm.nih.gov/pub/clinvar/vcf_GRCh38/clinvar_20241215.vcf.gz
+# Source: https://ftp.ncbi.nlm.nih.gov/pub/clinvar/vcf_GRCh38/
+with open('clinvar_20241215.vcf') as file:
+    reader = csv.reader(file, delimiter="\t")
+    for row in reader:
+        if row[0][0] == '#':
+            continue
+        # print('row', row)
+        info = row[7]
+        fields = info.split(';')
+        is_relevant = get_is_relevant(fields)
+        if not is_relevant:
+            continue
+        slim_info = trim_info_fields(fields)
+        del row[5:7]
+        row[5] = slim_info
+
+        output_rows.append('\t'.join(row))
+
+content = '\n'.join(output_rows)
+
+disease_map = json.dumps(disease_ids_and_names)
+column_names = ['#CHROM', 'POS', 'ID', 'REF', 'ALT', 'DISEASE_IDS', 'CLNREVSTAT', 'CLNSIG', 'CLNVC', 'MC', 'ORIGIN', 'RS']
+headers = '\n'.join([
+    '# disease_mondo_ids_and_names = ' + disease_map,
+    '# variant_types = ' + str(variant_types),
+    '# molecular_consequences = ' + str(molecular_consequences),
+    '\t'.join(column_names)
+])
+content = headers + '\n' + content
+
+
+output_path = 'clinvar_priority_20241215.tsv'
+with open(output_path, "w") as f:
+    f.write(content)
+with gzip.open(f"{output_path}.gz", "wt") as f:
+    f.write(content)

test/offline/gene-structure.test.js

@@ -22,7 +22,7 @@ describe('Ideogram gene structure functionality', function() {
         const apoeLabel = document.querySelector('#_c18_a3 path');
         apoeLabel.dispatchEvent(new Event('mouseover'));
         const subparts = document.querySelectorAll('rect.subpart');
-        assert.equal(subparts.length, 7); // spliced, without introns
+        assert.equal(subparts.length, 9); // spliced, without introns
         done();
       }, 500);
     }
@@ -162,7 +162,7 @@ describe('Ideogram gene structure functionality', function() {
         const sKeydown = new KeyboardEvent('keydown', {key: 's'});
         document.dispatchEvent(sKeydown);
         let subparts = document.querySelectorAll('rect.subpart');
-        assert.equal(subparts.length, 10); // includes introns
+        assert.equal(subparts.length, 12); // includes introns
 
         document.dispatchEvent(sKeydown);
         setTimeout(async function() {