diff --git a/src/find_interaction_cluster/nt_and_community.py b/src/find_interaction_cluster/nt_and_community.py
index a2faad830499dc70645614d2673712ab90f0376f..45babcb9e6f4a6a01711a99d97e901d185dc23ac 100644
--- a/src/find_interaction_cluster/nt_and_community.py
+++ b/src/find_interaction_cluster/nt_and_community.py
@@ -512,9 +512,9 @@ def expand_results_perm(df: pd.DataFrame, rdf: pd.DataFrame, cpnt: str,
 
 def create_and_save_ctrl_dataframe(df: pd.DataFrame, feature: str,
                                    region: str, cpnt_type: str, cpnt: str,
-                                   outfile: Path, test_type: str,
+                                   outfile_ctrl: Path, test_type: str,
                                    df_ctrl: pd.DataFrame, dic_com: Dict,
-                                   iteration: int, outfile_ctrl: Path) -> None:
+                                   iteration: int) -> None:
     """
     Create a dataframe with a control community, save it as a table and \
     as a barplot figure.
@@ -526,19 +526,19 @@ def create_and_save_ctrl_dataframe(df: pd.DataFrame, feature: str,
     :param cpnt_type: The type of component to analyse; It \
     can be 'nt', 'dnt' or 'aa'.
     :param cpnt: The component (nt, aa, dnt) of interest
-    :param outfile: File used to store diagnotics
+    :param outfile_ctrl: file used to stored the table and the figure \
+    containing the test communities and the control community
     :param test_type: The type of test to make (permutation or lmm)
     :param df_ctrl: A dataframe containing the frequency of each nucleotide \
     in each exons/gene in fasterdb.
     :param dic_com: A dictionary linking each community to the exons \
     it contains.
     :param iteration: The number of sub samples to create
-    :param outfile_ctrl: file used to stored the table and the figure \
-    containing the test communities and the control community
     """
     if test_type == "lmm":
         ndf, rdf = lmm_with_ctrl(df, feature, region, cpnt,
-                                 outfile.parents[1] / outfile.name, cpnt_type)
+                                 outfile_ctrl.parents[1] / outfile_ctrl.name,
+                                 cpnt_type)
         df_bar = expand_results_lmm(ndf, rdf, cpnt, feature)
     else:
         rdf = perm_with_ctrl(df, feature, cpnt, df_ctrl, dic_com, iteration)
@@ -646,8 +646,8 @@ def get_stat_cpnt_communities(df: pd.DataFrame, project: str, weight: int,
     res = {"project": project, "cpnt": cpnt,
            'pval': lmm_maker(df, outfile, cpnt)}
     create_and_save_ctrl_dataframe(df, feature, region, cpnt_type,
-                                   cpnt, outfile, test_type, df_ctrl, dic_com,
-                                   iteration, outfile_ctrl)
+                                   cpnt, outfile_ctrl, test_type, df_ctrl,
+                                   dic_com, iteration)
 
     return pd.Series(res)