diff --git a/jass_preprocessing/__main__.py b/jass_preprocessing/__main__.py
index bee0a4fea0ec077888f6c029ef543d251dd50b0d..ed42e4bd26e41b984a4bdbd1e0fcf6dc97cdf508 100644
--- a/jass_preprocessing/__main__.py
+++ b/jass_preprocessing/__main__.py
@@ -28,18 +28,21 @@ def launch_preprocessing(args):
     Preprocessing GWAS dataset
     """
     gwas_map = pd.read_csv(args.gwas_info, sep="\t", index_col=0)
+    print(gwas_map.head())
 
-    for gwas_filename in gwas_map[['filename']]:
+    for gwas_filename in gwas_map.index:
+        print(gwas_filename)
+        print(gwas_map.columns)
         tag = "{0}_{1}".format(gwas_map.loc[gwas_filename, 'consortia'],
                                gwas_map.loc[gwas_filename, 'outcome'])
 
         print('processing GWAS: {}'.format(tag))
         start = time.time()
-        GWAS_link = jp.map_gwas.walkfs(args.gwas_folder, gwas_filename)[2]
+        GWAS_link = jp.map_gwas.walkfs(args.input_folder, gwas_filename)[2]
+
         mapgw = jp.map_gwas.map_columns_position(GWAS_link, args.gwas_info)
 
         gw_df = jp.map_gwas.read_gwas(GWAS_link, mapgw)
-
         ref = pd.read_csv(args.ref_path, header=None, sep= "\t",
                           names =['chr', "pos", "snp_id", "ref", "alt", "MAF"],
                            index_col="snp_id")
diff --git a/jass_preprocessing/map_gwas.py b/jass_preprocessing/map_gwas.py
index 2b0816f39f27a12c3214d0313c69cef626e3fcda..f3e8313c377be8da888d58552d121e5545980ef2 100644
--- a/jass_preprocessing/map_gwas.py
+++ b/jass_preprocessing/map_gwas.py
@@ -112,7 +112,7 @@ def map_columns_position(gwas_internal_link,  GWAS_labels):
     mapgw = pd.Series(label_position, index=reference_label)
     mapgw = mapgw.loc[~mapgw.isna()].astype(int)
     mapgw.sort_values(inplace=True)
-    print(mapgw)
+
     f.close()
     return mapgw
 
@@ -128,6 +128,8 @@ def read_gwas( gwas_internal_link, column_map):
     Return:
         a pandas dataframe with missing value all equal to np.nan
     """
+    print("Reading file:")
+    print(gwas_internal_link)
 
     fullGWAS = pd.read_csv(gwas_internal_link, delim_whitespace=True,
                                usecols = column_map.values, #column_dict['label_position'].keys(),
@@ -140,6 +142,7 @@ def read_gwas( gwas_internal_link, column_map):
                                                  'NA', 'NULL', 'NaN',
                                                  'nan', 'na', '.'])
 
+
     fullGWAS = fullGWAS[~fullGWAS.index.duplicated(keep='first')]
     #fullGWAS = convert_missing_values(fullGWAS)