Merge pull request #309 from pbashyal-nmdp/308_fix_map_drb345_to_drbx

Fix DRBX mapping for`map_drb345_to_drbx`
nmdp-bioinformatics · Mar 4, 2024 · 7082a6f · 7082a6f
2 parents 2fbe8fa + a2797c5
commit 7082a6f
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Showing 3 changed files with 62 additions and 27 deletions.
diff --git a/extras/reduce_conf.json b/extras/reduce_conf.json
@@ -14,6 +14,12 @@
     "r_drb1_typ2",
     "r_dpb1_typ1",
     "r_dpb1_typ2",
+    "r_drb3_typ1",
+    "r_drb3_typ2",
+    "r_drb4_typ1",
+    "r_drb4_typ2",
+    "r_drb5_typ1",
+    "r_drb5_typ2",
     "d_a_typ1",
     "d_a_typ2",
     "d_b_typ1",
@@ -23,7 +29,13 @@
     "d_drb1_typ1",
     "d_drb1_typ2",
     "d_dpb1_typ1",
-    "d_dpb1_typ2"
+    "d_dpb1_typ2",
+    "d_drb3_typ1",
+    "d_drb3_typ2",
+    "d_drb4_typ1",
+    "d_drb4_typ2",
+    "d_drb5_typ1",
+    "d_drb5_typ2"
   ],
   "locus_column_mapping": {
     "recipient": {
@@ -39,13 +51,25 @@
         "r_c_typ1",
         "r_c_typ2"
       ],
+      "dqb1": [
+        "r_dpb1_typ1",
+        "r_dpb1_typ2"
+      ],
       "drb1": [
         "r_drb1_typ1",
         "r_drb1_typ2"
       ],
-      "dqb1": [
-        "r_dpb1_typ1",
-        "r_dpb1_typ2"
+      "drb3": [
+        "r_drb3_typ1",
+        "r_drb3_typ2"
+      ],
+      "drb4": [
+        "r_drb4_typ1",
+        "r_drb4_typ2"
+      ],
+      "drb5": [
+        "r_drb5_typ1",
+        "r_drb5_typ2"
       ]
     },
     "donor": {
@@ -61,20 +85,30 @@
         "d_c_typ1",
         "d_c_typ2"
       ],
+      "dqb1": [
+        "d_dpb1_typ1",
+        "d_dpb1_typ2"
+      ],
       "drb1": [
         "d_drb1_typ1",
         "d_drb1_typ2"
       ],
-      "dqb1": [
-        "d_dpb1_typ1",
-        "d_dpb1_typ2"
+      "drb3": [
+        "d_drb3_typ1",
+        "d_drb3_typ2"
+      ],
+      "drb4": [
+        "d_drb4_typ1",
+        "d_drb4_typ2"
+      ],
+      "drb5": [
+        "d_drb5_typ1",
+        "d_drb5_typ2"
       ]
     }
   },
-
   "redux_type": "lgx",
   "redux_cache_size": 1000,
-
   "reduce_serology": false,
   "reduce_v2": true,
   "convert_v2_to_v3": false,
@@ -84,17 +118,12 @@
   "reduce_XX": false,
   "reduce_MAC": true,
   "map_drb345_to_drbx": false,
-
   "locus_in_allele_name": true,
   "keep_locus_in_allele_name": true,
-
   "new_column_for_redux": true,
   "reduced_column_prefix": "reduced_",
-
   "generate_glstring": true,
-
   "output_file_format": "csv",
   "apply_compression": "gzip",
-
   "verbose_log": true
 }
diff --git a/extras/sample.csv b/extras/sample.csv
@@ -1,4 +1,4 @@
-rid,did,r_a_typ1,r_a_typ2,r_b_typ1,r_b_typ2,r_c_typ1,r_c_typ2,r_drb1_typ1,r_drb1_typ2,r_dpb1_typ1,r_dpb1_typ2,d_a_typ1,d_a_typ2,d_b_typ1,d_b_typ2,d_c_typ1,d_c_typ2,d_drb1_typ1,d_drb1_typ2,d_dpb1_typ1,d_dpb1_typ2
-2110,123,A*01:AB,A*29:79,B*18:67,B*51:275,C*05:01:19,C*02:85:02,DRB1*03:03,DRB1*14:144,DPB1*193:01:01,DPB1*582:01:01,A*01:AB,A*29:79,B*18:67,B*51:275,C*05:01:19,C*02:85:02,DRB1*03:03,DRB1*14:144,DPB1*193:01:01,DPB1*582:01:01
-2111,456,A*01:01:42,A*30:12:02,B*44:02:32,B*35:42,C*03:148,C*04:322,DRB1*13:01:16,DRB1*15:80N,DPB1*914:01:01,DPB1*278:01:01,A*01:01:42,A*30:12:02,B*44:02:32,B*35:42,C*03:148,C*04:322,DRB1*13:01:16,DRB1*15:80N,DPB1*914:01:01,DPB1*278:01:01
-2113,789,A*02:247,A*03:227,B*15:570,B*07:02:01:17,C*16:01:10,C*06:102,DRB1*13:156,DRB1*14:167:01,DPB1*405:01:01,DPB1*479:01:01,A*02:247,A*03:227,B*15:570,B*07:02:01:17,C*16:01:10,C*06:102,DRB1*13:156,DRB1*14:167:01,DPB1*405:01:01,DPB1*479:01:01
+rid,did,r_a_typ1,r_a_typ2,r_b_typ1,r_b_typ2,r_c_typ1,r_c_typ2,r_drb1_typ1,r_drb1_typ2,r_dpb1_typ1,r_dpb1_typ2,d_a_typ1,d_a_typ2,d_b_typ1,d_b_typ2,d_c_typ1,d_c_typ2,d_drb1_typ1,d_drb1_typ2,d_dpb1_typ1,d_dpb1_typ2,r_drb3_typ1,r_drb3_typ2,r_drb4_typ1,r_drb4_typ2,r_drb5_typ1,r_drb5_typ2,d_drb3_typ1,d_drb3_typ2,d_drb4_typ1,d_drb4_typ2,d_drb5_typ1,d_drb5_typ2
+2110,123,A*01:AB,A*29:79,B*18:67,B*51:275,C*05:01:19,C*02:85:02,DRB1*03:03,DRB1*14:144,DPB1*193:01:01,DPB1*582:01:01,A*01:AB,A*29:79,B*18:67,B*51:275,C*05:01:19,C*02:85:02,DRB1*03:03,DRB1*14:144,DPB1*193:01:01,DPB1*582:01:01,DRB3*02:189,DRB3*03:09,NNNN,NNNN,NNNN,NNNN,NNNN,NNNN,NNNN,NNNN,DRB5*01:93,DRB5*02:02:01
+2111,456,A*01:01:42,A*30:12:02,B*44:02:32,B*35:42,C*03:148,C*04:322,DRB1*13:01:16,DRB1*15:80N,DPB1*914:01:01,DPB1*278:01:01,A*01:01:42,A*30:12:02,B*44:02:32,B*35:42,C*03:148,C*04:322,DRB1*13:01:16,DRB1*15:80N,DPB1*914:01:01,DPB1*278:01:01,NNNN,NNNN,DRB4*01:53,DRB4*01:31,NNNN,NNNN,NNNN,NNNN,NNNN,NNNN,DRB5*01:102,DRB5*01:103
+2113,789,A*02:247,A*03:227,B*15:570,B*07:02:01:17,C*16:01:10,C*06:102,DRB1*13:156,DRB1*14:167:01,DPB1*405:01:01,DPB1*479:01:01,A*02:247,A*03:227,B*15:570,B*07:02:01:17,C*16:01:10,C*06:102,DRB1*13:156,DRB1*14:167:01,DPB1*405:01:01,DPB1*479:01:01,NNNN,NNNN,DRB4*01:79,DRB4*01:119,NNNN,NNNN,DRB3*02:189,DRB3*03:09,NNNN,NNNN,NNNN,NNNN
diff --git a/scripts/pyard-reduce-csv b/scripts/pyard-reduce-csv
@@ -209,15 +209,21 @@ def reduce_locus_columns(df, ard_config, locus_column_mapping, verbose):
     # New columns DRBX_1 and DRBX_2 are created
     if ard_config.get("map_drb345_to_drbx"):
         drbx_loci = ["DRB3", "DRB4", "DRB5"]
-        drbx_columns = [
-            col_name for col_name in df.columns if col_name.split("_")[1] in drbx_loci
-        ]
-        if len(drbx_columns) == len(drbx_loci) * 2:  # For Type1/Type2
-            locus_in_allele_name = ard_config["keep_locus_in_allele_name"]
-            df_drbx = df[drbx_columns].apply(
-                create_drbx, axis=1, args=(locus_in_allele_name,)
-            )
-            df["DRBX_1"], df["DRBX_2"] = zip(*df_drbx)
+        for subject in ard_config["locus_column_mapping"].keys():
+            subject_loci = ard_config["locus_column_mapping"][subject]
+            subject_drbs = []
+            for locus in ard_config["locus_column_mapping"][subject].keys():
+                if locus.upper() in drbx_loci:
+                    subject_drbs.extend(subject_loci[locus])
+
+            # If all the DRBs are there
+            # ['DRB3_1', 'DRB3_2', 'DRB4_1', 'DRB4_2', 'DRB5_1', 'DRB5_2']
+            if len(subject_drbs) == 6:
+                locus_in_allele_name = ard_config["keep_locus_in_allele_name"]
+                df_drbx = df[subject_drbs].apply(
+                    create_drbx, axis=1, args=(locus_in_allele_name,)
+                )
+                df[f"{subject}_DRBX_1"], df[f"{subject}_DRBX_2"] = zip(*df_drbx)
 
     if ard_config.get("generate_glstring"):
         for subject in locus_column_mapping: