--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/kma_result_to_mlst.py	Thu Oct 31 14:12:43 2019 -0400
@@ -0,0 +1,97 @@
+#!/usr/bin/env python
+
+from __future__ import print_function
+
+import argparse
+import csv
+import json
+import os
+import sys
+
+from pprint import pprint
+
+def parse_res_file(res_file_path):
+    LOCUS_ALLELE_DELIMITER = '_'
+    
+    res_fieldnames = [
+        'template',
+        'score',
+        'expected',
+        'template_length',
+        'template_identity',
+        'template_coverage',
+        'query_identity',
+        'query_coverage',
+        'depth',
+        'q_value',
+        'p_value',
+    ]
+    
+    with open(res_file_path, 'r') as f:
+        loci = {}
+        reader = csv.DictReader(f, fieldnames=res_fieldnames, dialect="excel-tab")
+        next(reader) #skip header
+        for row in reader:
+            locus, allele = map(str.strip, row['template'].split(LOCUS_ALLELE_DELIMITER))
+            if locus in loci:
+                loci[locus][allele] = {
+                    'locus_id': locus,
+                    'allele_id': allele,
+                    'score': int(row['score'].strip()),
+                    'expected': int(row['expected'].strip()),
+                    'template_length': int(row['template_length'].strip()),
+                    'template_identity': float(row['template_identity'].strip()),
+                    'template_coverage': float(row['template_coverage'].strip()),
+                    'query_identity': float(row['query_identity'].strip()),
+                    'query_coverage': float(row['query_coverage'].strip()),
+                    'depth': float(row['depth'].strip()),
+                    'q_value': float(row['q_value'].strip()),
+                    'p_value': float(row['p_value'].strip()),
+                }
+            else:
+                loci[locus] = {}
+                loci[locus][allele] = {
+                    'locus_id': locus,
+                    'allele_id': allele,
+                    'score': int(row['score'].strip()),
+                    'expected': int(row['expected'].strip()),
+                    'template_length': int(row['template_length'].strip()),
+                    'template_identity': float(row['template_identity'].strip()),
+                    'template_coverage': float(row['template_coverage'].strip()),
+                    'query_identity': float(row['query_identity'].strip()),
+                    'query_coverage': float(row['query_coverage'].strip()),
+                    'depth': float(row['depth'].strip()),
+                    'q_value': float(row['q_value'].strip()),
+                    'p_value': float(row['p_value'].strip()),
+                }
+
+        return loci
+
+def main(args):
+
+    loci = parse_res_file(args.res)
+    print("\t".join([
+        "locus_id",
+        "allele_id",
+        "template_identity",
+        "template_coverage",
+        "depth",
+        ]))
+
+    for locus, alleles in loci.items():
+        best_allele = sorted(alleles.values(),
+                             key=lambda x: x['score'], reverse=True)[0]['allele_id']
+
+        print("\t".join([
+            alleles[best_allele]['locus_id'],
+            alleles[best_allele]['allele_id'],
+            str(alleles[best_allele]['template_identity']),
+            str(alleles[best_allele]['template_coverage']),
+            str(alleles[best_allele]['depth']),
+        ]))
+        
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--res", dest="res", help="KMA result overview file")
+    args = parser.parse_args()
+    main(args)