diff --git a/run/extraModel/generate_bivar_data.py b/run/extraModel/generate_bivar_data.py
index 87268a6..ee10cb3 100755
--- a/run/extraModel/generate_bivar_data.py
+++ b/run/extraModel/generate_bivar_data.py
@@ -4,12 +4,11 @@
 from glob import glob
 from tqdm import tqdm, trange
 import logging
-from multiprocessing import Pool
 from os.path import exists
 import shutil
 
 def process_sample(data_folder, sample_id,
-                   default_pred, labeling=False, n_thread = 10):
+                   default_pred, labeling=False):
 
     # recessive_folder = f'{data_folder}/recessive_matrix'
     # if not os.path.exists(recessive_folder):
@@ -62,14 +61,11 @@ def process_sample(data_folder, sample_id,
                 'gene': gene,
                'varIDs': list(gene_dict[gene])} for gene in gene_dict
                ]
-    print(f"Now starting to generate recessive feature matrix for {len(gene_dict)} genes, {feature_df.shape[0]} variants using {n_thread} threads.")
-    p = Pool(processes=n_thread)
+    print(f"Now starting to generate recessive feature matrix for {len(gene_dict)} genes, {feature_df.shape[0]} variants.")
     
-    with tqdm(total=len(params)) as pbar:
-        for result in p.imap_unordered(process_gene, params):
-            pbar.update()
-    p.close()
-    p.join()
+    for param in tqdm(params):
+        process_gene(param)
+
     print("Recessive features for each gene finished, now putting together...")
 
     bivar_feature_mats = []
diff --git a/run/extraModel/main.py b/run/extraModel/main.py
index 258aa73..c77c36d 100755
--- a/run/extraModel/main.py
+++ b/run/extraModel/main.py
@@ -16,15 +16,11 @@
 parser.add_argument('-id', metavar='I', type=str,
                     help = 'sample ID')
 
-parser.add_argument('-n_cpu',  type=int, default=10,
-                    help = 'folders containing all extended final matrices')
-
 args = parser.parse_args()
 
 #st_time = time()
 #prj_name = args.project
 sample_id = args.id
-n_cpu = args.n_cpu
 
 out_folder = '/out/conf_4Model'
 
@@ -60,7 +56,7 @@ def assign_ranking(df):
     return pred_df
     
 
-def AIM(data_folder, sample_id, n_thread):
+def AIM(data_folder, sample_id):
     feature_fn = f'/out/final_matrix/{sample_id}.csv'
 
     if not os.path.exists(feature_fn):
@@ -88,7 +84,7 @@ def AIM(data_folder, sample_id, n_thread):
     generate_bivar_data.process_sample( data_folder = out_folder,
                                         sample_id = sample_id,
                                         default_pred = default_pred,                                           
-                                        labeling=False, n_thread = n_thread)
+                                        labeling=False)
 
     recessive_feature_file = f"{out_folder}/recessive_matrix/{sample_id}.csv"
     if os.path.exists(recessive_feature_file):
@@ -117,4 +113,4 @@ def AIM(data_folder, sample_id, n_thread):
     return
 
 #for sample_id in tqdm(sample_folders):
-AIM(out_folder, sample_id, n_thread = n_cpu)
+AIM(out_folder, sample_id)