Merge pull request #5 from eastgenomics/URA-91_NA_fix

Ura 91 v1.0.2 na fix

dxapp.json

@@ -1,10 +1,10 @@
 {
-  "name": "eggd_somalier_relate2multiqc_v1.0.1",
-  "title": "eggd_somalier_relate2multiqc_v1.0.1",
+  "name": "eggd_somalier_relate2multiqc_v1.0.2",
+  "title": "eggd_somalier_relate2multiqc_v1.0.2",
   "summary": "Reformats somalier output somalier.samples.tsv to append predicted sex to file and it is in a suitable format for multiqc",
-  "dxapi": "1.0.1",
+  "dxapi": "1.0.2",
   "properties": {
-    "githubRelease": "v1.0.1"
+    "githubRelease": "v1.0.2"
   },
   "inputSpec": [
     {

resources/home/dnanexus/reformat.py

@@ -195,18 +195,20 @@ def matching_sexes(data):
                                     lambda x: mappings.get(str(x))
                                     )
 
-    # Need to create a column called match that has true/false boolean 
+    # Need to create a column called match that has true/false boolean
     # for every row, stating whether they match between reported and
-    # predicted sex. If reported is unknown/none, then match is NA
+    # predicted sex. If reported is unknown/none, then matching sex is NA
 
     data["Match_Sexes"] = "NA"
 
-    # If reported sex is not unknown or none, then see if reported and 
+    # If reported sex is not unknown or none, then see if reported and
     # predicted sex is a match (false/true boolean)
+    # If predicted sex is unknown, matching sex will be reported as NA
     for idx, row in data.iterrows():
-        if not (row['original_pedigree_sex'] == "unknown" or row['original_pedigree_sex'] == "none"):
+        if not (row['original_pedigree_sex'] == "unknown" or row['original_pedigree_sex'] == "none"
+        or row['Predicted_Sex'] == "unknown"):
             data.at[idx, 'Match_Sexes'] = row['original_pedigree_sex'] == row['Predicted_Sex']
-            # need to make the false/true boolean to string to make it 
+            # need to make the false/true boolean to string to make it
             # lower case for multiqc
             data.at[idx, 'Match_Sexes'] = str(data.at[idx, 'Match_Sexes']).lower()