diff --git a/src/find_interaction_cluster/__main__.py b/src/find_interaction_cluster/__main__.py
index 19361fad8859cd421a81b1ed8d46562dabaed614..a834dc78013dd26c0a02e27fc22ba5b556800570 100644
--- a/src/find_interaction_cluster/__main__.py
+++ b/src/find_interaction_cluster/__main__.py
@@ -27,6 +27,7 @@ from .colocalisation_n_ppi_analysis import coloc_ppi_stat_main
 def launcher(weight: int = 1,
              global_weight: int = 0,
              same_gene: bool = True,
+             inflation: float = 1.5,
              ps: int = ConfigGraph.cpu,
              html_fig: bool = False, feature: str = 'exon', region: str = '',
              component_type: str = 'nt',
@@ -45,6 +46,7 @@ def launcher(weight: int = 1,
     :param project: The name of the project of interest (default GSM1517081)
     :param same_gene: Say if we consider as co-localised, exons within the \
     same gene (True) or not (False) (default True)
+    :param inflation: The inflation parameter
     :param  html_fig: True to display the html figure (default False).
     :param feature: The feature we want to analyse (default 'exon')
     :param region: The region of a gene to analyse (used only if feature \
@@ -71,17 +73,18 @@ def launcher(weight: int = 1,
     multiple_community_launcher(weight, global_weight, project, same_gene,
                                 html_fig, feature, logging_level)
     # multiple_stat_launcher(ps, weight, global_weight, project, same_gene,
-    #                        feature, logging_level)
+    #                        inflation, feature, logging_level)
     multiple_nt_lm_launcher(ps, weight, global_weight, project,
-                            same_gene, feature, region, component_type,
-                            test_type, iteration, display_size,
+                            same_gene, inflation, feature, region,
+                            component_type, test_type, iteration, display_size,
                             logging_level=logging_level)
     if feature == "gene":
         # ppi_stat_launcher(weight, global_weight, project, same_gene,
+        #                   inflation,
         #                   ConfigGraph.ppi_threshold, iteration,
         #                   logging_level)
         coloc_ppi_stat_main(weight, global_weight, project, same_gene,
-                            iteration, logging_level)
+                            inflation, iteration, logging_level)
 
 
 
diff --git a/src/find_interaction_cluster/colocalisation_n_ppi_analysis.py b/src/find_interaction_cluster/colocalisation_n_ppi_analysis.py
index 6e7efb6518672e2677f13baf055091c288792567..cd33bb836743019a844cc1b0f5c93d709fe6af72 100644
--- a/src/find_interaction_cluster/colocalisation_n_ppi_analysis.py
+++ b/src/find_interaction_cluster/colocalisation_n_ppi_analysis.py
@@ -302,7 +302,8 @@ def create_figure(df_full: pd.DataFrame, outfile: Path) -> None:
 
 
 def coloc_ppi_stat_main(weight: int, global_weight: int,
-                        project: str, same_gene: bool, iteration: int = 1000,
+                        project: str, same_gene: bool, inflation: float,
+                        iteration: int = 1000,
                         logging_level: str = "DISABLE"):
     """
     Launch the statistical tests allowing to determine if interaction between \
@@ -327,14 +328,14 @@ def coloc_ppi_stat_main(weight: int, global_weight: int,
     logging.debug("Calculating stats...")
     community_file = ConfigGraph.get_community_file(project, weight,
                                                     global_weight,
-                                                    same_gene, "gene",
-                                                    f".txt")
+                                                    same_gene, inflation,
+                                                    "gene", f".txt")
 
     df_com = pd.read_csv(community_file, sep="\t")
     df_com = df_com[df_com['nodes'] >= 10].copy()
     full_df = create_scored_dataframe(df_com, ConfigPPI.fasterdb_ppi)
     outfile = ConfigGraph.get_community_file(project, weight, global_weight,
-                                             same_gene, "gene",
+                                             same_gene, inflation, "gene",
                                              f"_interation_gene-protein.pdf",
                                              "community_gene_vs_protein")
     create_figure(full_df, outfile)
diff --git a/src/find_interaction_cluster/community_calibration.py b/src/find_interaction_cluster/community_calibration.py
index 79697e09bb612271d88b0921bf10b5cb48a89cbe..3363835827d77b5b111916a2193a33f44564e113 100644
--- a/src/find_interaction_cluster/community_calibration.py
+++ b/src/find_interaction_cluster/community_calibration.py
@@ -108,10 +108,10 @@ def community_finder(weight: int, global_weight: int, inflation: float,
                                              level=feature)
     outfileg, result_file = write_interaction_file(interaction, project,
                                                    weight, global_weight,
-                                                   same_gene, feature=feature,
+                                                   same_gene,
+                                                   inflation,
+                                                   feature=feature,
                                                    use_weight=use_weight)
-    if result_file.is_file():
-        result_file.unlink()
     graph = create_graph(interaction)
     df, dic_community = find_communities(graph, project, outfileg, result_file,
                                          feature, inflation=inflation,
diff --git a/src/find_interaction_cluster/community_finder.py b/src/find_interaction_cluster/community_finder.py
index 9e5841b908829eeb30f93c75d8dd80202cb23eeb..46e076549c83b91ea602c3bc46ece7ddbb2c9259 100644
--- a/src/find_interaction_cluster/community_finder.py
+++ b/src/find_interaction_cluster/community_finder.py
@@ -276,7 +276,8 @@ def get_figure_title(project, weight, global_weight, same_gene, feature):
 
 def write_interaction_file(arr_interaction: np.array, project: str,
                            weight: int, global_weight: int, same_gene: bool,
-                           use_weight: bool = False, feature: str = 'exon'):
+                           inflation: float, use_weight: bool = False,
+                           feature: str = 'exon'):
     """
 
     :param arr_interaction:  Each couples of co-localized feature within a \
@@ -291,14 +292,15 @@ def write_interaction_file(arr_interaction: np.array, project: str,
     same gene (True) or not (False) (default False)
     :param use_weight: Say if we want to write the weight into the result file.
     :param feature: Says if we want to work at gene or at exons level
+    :param inflation: The inflation parameter
     :return:
     """
     logging.debug('Writing interaction files ...')
     outfile = ConfigGraph.get_community_file(project, weight, global_weight,
-                                             same_gene, feature,
+                                             same_gene, inflation, feature,
                                              f"_interation.txt")
     result = ConfigGraph.get_community_file(project, weight, global_weight,
-                                            same_gene, feature,
+                                            same_gene, inflation, feature,
                                             f"_communities.txt")
     with outfile.open('w') as f:
         for exon1, exon2, cweight in arr_interaction:
@@ -310,7 +312,8 @@ def write_interaction_file(arr_interaction: np.array, project: str,
 
 def community_finder(weight: int, global_weight: int, project: str = "",
                      same_gene=True, html_fig: bool = False,
-                     feature: str = "exon", logging_level: str = "DISABLE"):
+                     feature: str = "exon", inflation: float = 1.5,
+                     logging_level: str = "DISABLE"):
     """
     Find communities inside co-localisation between exons found in \
     a ChIA-PET project.
@@ -325,6 +328,7 @@ def community_finder(weight: int, global_weight: int, project: str = "",
     same gene (True) or not (False) (default False)
     :param logging_level: The level of data to display (default 'DISABLE')
     :param html_fig: True to create an html figure, false else
+    :param inflation: The inflation parameter
     :param feature: The feature we want to analyse (default 'exon')
     """
     ConfigGraph.output_folder.mkdir(exist_ok=True, parents=True)
@@ -335,13 +339,14 @@ def community_finder(weight: int, global_weight: int, project: str = "",
                                              level=feature)
     outfile, result_file = write_interaction_file(interaction, project,
                                                   weight, global_weight,
-                                                  same_gene, feature=feature)
+                                                  same_gene, feature=feature,
+                                                  inflation=inflation)
     graph = create_graph(interaction)
     df, dic_community = find_communities(graph, project, outfile, result_file,
                                          feature)
     logging.debug('Writing results ...')
     outfiles = [ConfigGraph.get_community_file(
-        project, weight, global_weight, same_gene, feature, ext)
+        project, weight, global_weight, same_gene, inflation, feature, ext)
         for ext in [f'.txt', f'.cyjs', f'.html']]
     df.to_csv(outfiles[0], sep="\t", index=False)
     logging.debug("Saving the graph ...")
diff --git a/src/find_interaction_cluster/config.py b/src/find_interaction_cluster/config.py
index 4263fc5f85bd279dbd06dc52d1925f41d63b706d..3e6c717cc65766ba2d4b90461d4ca98a104ed40b 100644
--- a/src/find_interaction_cluster/config.py
+++ b/src/find_interaction_cluster/config.py
@@ -13,31 +13,32 @@ from typing import List, Dict
 import pandas as pd
 
 
-def get_weight_folder(weight: int, global_weight: int):
+def get_weight_folder(weight: int, global_weight: int, inflation: float):
     """
     Get the weight folder.
 
     :param weight: The weight of interaction to consider
     :param global_weight: The global weight to consider. if \
     the global weight is equal to 0 then then density figure are calculated \
-    by project, else all projet are merge together and the interaction \
+    by project, else all project are merge together and the interaction \
     seen in `global_weight` project are taken into account
+    :param inflation: The inflation parameter
     :return: The folder that will contains the interaction with a weight \
     greater or equal to `weigh` in ChIA-PET projects
     """
     if global_weight == 0:
         weight_folder = ConfigGraph.community_folder / \
-                        f"project_weight-{weight}"
+                        f"project_weight-{weight}-{inflation}"
     else:
         weight_folder = ConfigGraph.community_folder / \
                         f"weight-{weight}_" \
-                        f"global_weight-{global_weight}"
+                        f"global_weight-{global_weight}-{inflation}"
     weight_folder.mkdir(parents=True, exist_ok=True)
     return weight_folder
 
 
 def get_community_file(project: str, weight: int, global_weight: int,
-                       same_gene: bool, feature: str = 'exon',
+                       same_gene: bool, inflation: float, feature: str = 'exon',
                        ext: str = ".txt", sub_fold: str = ''):
     """
     Get the output file of interest.
@@ -50,12 +51,13 @@ def get_community_file(project: str, weight: int, global_weight: int,
     seen in `global_weight` project are taken into account
     :param same_gene: Say if we consider as co-localised exon within the \
     same gene
-    :param the kind of feature analyzed
+    :param inflation: The inflation parameter
+    :param feature: the kind of feature analyzed
     :param ext: The file extension
-    :param subfolder: if filled, then the data are recovered from a subfolder
+    :param sub_fold: if filled, then the data are recovered from a subfolder
     :return: The filename of interest
     """
-    folder = get_weight_folder(weight, global_weight)
+    folder = get_weight_folder(weight, global_weight, inflation)
     if sub_fold != '':
         folder = folder / sub_fold
     folder.mkdir(exist_ok=True, parents=True)
diff --git a/src/find_interaction_cluster/create_ppi_files.py b/src/find_interaction_cluster/create_ppi_files.py
index 1d401736c97007912f8ec3b84253e5c7613b6fb7..fa159e8984a8688bfdbc8aca4ae79d1621d49127 100644
--- a/src/find_interaction_cluster/create_ppi_files.py
+++ b/src/find_interaction_cluster/create_ppi_files.py
@@ -8,13 +8,10 @@ Description: create a file of gene interaction at gene and protein levels.
 
 from .config import ConfigGraph
 from .ppi_scripts.config_ppi import ConfigPPI
-from typing import List
 from ..logging_conf import logging_def
 import numpy as np
 import logging
 from .community_finder import get_projects
-from itertools import product
-import multiprocessing as mp
 from pathlib import Path
 from typing import Dict, Union
 import pandas as pd
@@ -68,7 +65,7 @@ def ppi_array(fasterdb_ppi: Path, threshold: int) -> np.array:
 
 def write_interaction_ppi(arr_interaction: np.array, project: str,
                           weight: int, global_weight: int, same_gene: bool,
-                          use_weight: bool = False):
+                          inflation: float, use_weight: bool = False):
     """
 
     :param arr_interaction:  Each couples of co-localized feature within a \
@@ -81,15 +78,16 @@ def write_interaction_ppi(arr_interaction: np.array, project: str,
     seen in `global_weight` project are taken into account
     :param same_gene: Say if we consider as co-localised, exons within the \
     same gene (True) or not (False) (default False)
+    :param inflation: The inflation parameter
     :param use_weight: Say if we want to write the weight into the result file.
     """
     logging.debug('Writing interaction files ...')
     outfile = ConfigGraph.get_community_file(project, weight, global_weight,
-                                             same_gene, "gene",
+                                             same_gene, inflation, "gene",
                                              f"_interation_PPI_tmp.txt",
                                              "community_gene_vs_protein")
     result = ConfigGraph.get_community_file(project, weight, global_weight,
-                                            same_gene, "gene",
+                                            same_gene, inflation, "gene",
                                             f"_communities_PPI_tmp.txt",
                                             "community_gene_vs_protein")
     with outfile.open('w') as f:
@@ -102,7 +100,7 @@ def write_interaction_ppi(arr_interaction: np.array, project: str,
 
 def ppi_community_finder(fasterdb_ppi: Path, project: str,
                          weight: int, global_weight: int,
-                         same_gene: bool = True,
+                         same_gene: bool = True, inflation: float=1.5,
                          threshold: int = 700):
     """
     Find communities inside protein-protein interaction file
@@ -116,18 +114,19 @@ def ppi_community_finder(fasterdb_ppi: Path, project: str,
     seen in `global_weight` project are taken into account
     :param same_gene: Say if we consider as co-localised, exons within the \
     same gene (True) or not (False) (default False)
+    :param inflation: The inflation parameter
     :param threshold: The minimum threshold needed to consider the interaction
     """
     interaction = ppi_array(fasterdb_ppi, threshold)
     outfile, result_file = write_interaction_ppi(interaction, project,
                                                  weight, global_weight,
-                                                 same_gene)
+                                                 same_gene, inflation)
     graph = create_graph(interaction)
     df, dic_community = find_communities(graph, project, outfile, result_file,
                                          "gene")
     logging.debug('Writing results ...')
     outfiles = [ConfigGraph.get_community_file(
-        project, weight, global_weight, same_gene, "gene", ext,
+        project, weight, global_weight, same_gene, inflation, "gene", ext,
         "community_gene_vs_protein")
         for ext in [f'_graph_community_PPI.txt', f'_graph_community_PPI.cyjs']]
     df.to_csv(outfiles[0], sep="\t", index=False)
@@ -229,7 +228,7 @@ def filter_most_overllaping_ppi(df: pd.DataFrame, size_threshold: int
 def create_community_ppi_table(community_file: Path, fasterdb_ppi: Path,
                                project: str,
                                weight: int, global_weight: int,
-                               same_gene: bool = True,
+                               same_gene: bool = True, inflation: float = 1.5,
                                threshold: int = 700):
     """
 
@@ -245,17 +244,19 @@ def create_community_ppi_table(community_file: Path, fasterdb_ppi: Path,
     seen in `global_weight` project are taken into account
     :param same_gene: Say if we consider as co-localised exon within the \
     same gene
+    :param inflation: The inflation parameter
     :param threshold: The minimum threshold needed to consider the interaction
     :return:
     """
     outfile = ConfigGraph.get_community_file(project, weight, global_weight,
-                                             same_gene, "gene",
+                                             same_gene, inflation, "gene",
                                              '_graph_community_PPI.txt',
                                              "community_gene_vs_protein")
     if not outfile.is_file():
         logging.debug("Creating the community file for PPI")
         df_comm_ppi = ppi_community_finder(fasterdb_ppi, project, weight,
-                                           global_weight, same_gene, threshold)
+                                           global_weight, same_gene, inflation,
+                                           threshold)
     else:
         df_comm_ppi = pd.read_csv(outfile, sep="\t")
     logging.debug("Turning ppi community file into a dic")
@@ -275,7 +276,7 @@ def create_community_ppi_table(community_file: Path, fasterdb_ppi: Path,
 def ppi_stats_analysis(community_file: Path, fasterdb_ppi: Path,
                        project: str,
                        weight: int, global_weight: int,
-                       same_gene: bool = True,
+                       same_gene: bool = True, inflation: float = 1.5,
                        threshold: int = 700, iteration: int = 1000):
     """
     :param community_file: A file containing community of gene interacting \
@@ -290,23 +291,25 @@ def ppi_stats_analysis(community_file: Path, fasterdb_ppi: Path,
     seen in `global_weight` project are taken into account
     :param same_gene: Say if we consider as co-localised exon within the \
     same gene
+    :param inflation: The inflation parameter
     :param threshold: The minimum threshold needed to consider the interaction
     :param iteration: The number of iteration to make
     :return:
     """
     outfile = ConfigGraph.get_community_file(project, weight,
-                                             global_weight, same_gene, "gene",
+                                             global_weight, same_gene,
+                                             inflation, "gene",
                                              f"ppi_gene_complete_table.txt",
                                              "community_gene_vs_protein")
     ppi_outfile = ConfigGraph.get_community_file(project, weight,
                                                  global_weight,
-                                                 same_gene, "gene",
+                                                 same_gene, inflation, "gene",
                                                  '_graph_community_PPI.txt',
                                                  "community_gene_vs_protein")
     if not outfile.is_file():
         df = create_community_ppi_table(community_file, fasterdb_ppi,
                                         project, weight, global_weight,
-                                        same_gene, threshold)
+                                        same_gene, inflation, threshold)
         df.to_csv(outfile, sep="\t", index=False)
     else:
         df = pd.read_csv(outfile, sep="\t")
@@ -318,7 +321,7 @@ def ppi_stats_analysis(community_file: Path, fasterdb_ppi: Path,
     df, dic_values = update_overlap_df(df_overlap, dic_dna_gene, ppi_gene,
                                        iteration)
     outstat = ConfigGraph.get_community_file(project, weight, global_weight,
-                                             same_gene, "gene",
+                                             same_gene, inflation, "gene",
                                              f"ppi_gene_table_{iteration}_"
                                              f"stat.txt",
                                              "community_gene_vs_protein")
@@ -327,7 +330,7 @@ def ppi_stats_analysis(community_file: Path, fasterdb_ppi: Path,
                                           iteration, dic_values,
                                           use_seed=False)
     outstat = ConfigGraph.get_community_file(project, weight, global_weight,
-                                             same_gene, "gene",
+                                             same_gene, inflation, "gene",
                                              f"ppi_gene_table_{iteration}_"
                                              f"stat_recap.txt",
                                              "community_gene_vs_protein")
@@ -337,7 +340,8 @@ def ppi_stats_analysis(community_file: Path, fasterdb_ppi: Path,
 def ppi_stat_launcher(weight: int,
                       global_weight: int,
                       project: str,
-                      same_gene: bool, threshold: int = 700,
+                      same_gene: bool, inflation: float,
+                      threshold: int = 700,
                       iteration: int = 1000,
                       logging_level: str = "DISABLE"):
     """
@@ -351,6 +355,7 @@ def ppi_stat_launcher(weight: int,
     :param project: The project name, used only if global_weight = 0
     :param same_gene: Say if we consider as co-localised exon within the \
     same gene
+    :param inflation: The inflation parameter
     :param threshold: The minimum threshold needed to consider the interaction
     :param iteration: The number of iteration to make
     :param logging_level: Level of information to display
@@ -363,10 +368,11 @@ def ppi_stat_launcher(weight: int,
     logging.debug("Calculating stats...")
     community_file = ConfigGraph.get_community_file(project, weight,
                                                     global_weight,
-                                                    same_gene, "gene",
-                                                    f".txt")
+                                                    same_gene, inflation,
+                                                    "gene", f".txt")
     ppi_stats_analysis(community_file, ConfigPPI.fasterdb_ppi, project,
-                       weight, global_weight, same_gene, threshold, iteration)
+                       weight, global_weight, same_gene, inflation, threshold,
+                       iteration)
 
 
 if __name__ == "__main__":
diff --git a/src/find_interaction_cluster/nt_and_community.py b/src/find_interaction_cluster/nt_and_community.py
index c38f4f878d8fb7db8d6502908d0935771e3d196e..d1d591ed527c40e3dac73f386d52e1c17a2a3141 100644
--- a/src/find_interaction_cluster/nt_and_community.py
+++ b/src/find_interaction_cluster/nt_and_community.py
@@ -249,9 +249,9 @@ def prepare_dataframe(df: pd.DataFrame, test_type: str, nt: str,
 
 
 def create_outfiles(project: str, weight: int, global_weight: int,
-                    same_gene: bool, feature: str, cpnt_type: str,
-                    cpnt: str, test_type: str, community_file: str
-                    ) -> Tuple[Path, Path]:
+                    same_gene: bool, inflation: float, feature: str,
+                    cpnt_type: str, cpnt: str, test_type: str,
+                    community_file: str) -> Tuple[Path, Path]:
     """
     Create a file used to store diagnostics and a file used to store the \
     table containing the test communities and the control community
@@ -268,6 +268,7 @@ def create_outfiles(project: str, weight: int, global_weight: int,
     can be 'nt', 'dnt' or 'aa'.
     :param cpnt: The component (nt, aa, dnt) of interest
     :param feature: The kind of feature analysed
+    :param inflation: The inflation parameter
     :param test_type: The type of test to make (permutation or lm)
     :param community_file: A file containing custom communities. If \
     it equals to '' then weight, global weight and same genes parameter are \
@@ -286,11 +287,13 @@ def create_outfiles(project: str, weight: int, global_weight: int,
             f"{cpnt}-{cpnt_type}_VS_CTRL_stat_{test_type}.pdf"
         return outfile, outfile_ctrl
     outfile = ConfigGraph.\
-        get_community_file(project, weight, global_weight, same_gene, feature,
+        get_community_file(project, weight, global_weight, same_gene,
+                           inflation, feature,
                            f"{cpnt}-{cpnt_type}_stat_{test_type}.txt",
                            outfolder)
     outfile_ctrl = ConfigGraph.\
-        get_community_file(project, weight, global_weight, same_gene, feature,
+        get_community_file(project, weight, global_weight, same_gene,
+                           inflation, feature,
                            f"{cpnt}-{cpnt_type}_VS_CTRL_stat_{test_type}.pdf",
                            outfolder)
     return outfile, outfile_ctrl
@@ -298,6 +301,7 @@ def create_outfiles(project: str, weight: int, global_weight: int,
 
 def get_stat_cpnt_communities(df: pd.DataFrame, project: str, weight: int,
                               global_weight: int, same_gene: bool,
+                              inflation: float,
                               cpnt_type: str, cpnt: str,
                               dic_com: Dict, feature: str = "exon",
                               test_type: str = "",
@@ -318,6 +322,7 @@ def get_stat_cpnt_communities(df: pd.DataFrame, project: str, weight: int,
     seen in `global_weight` project are taken into account
     :param same_gene: Say if we consider as co-localised, exons within the \
     same gene (True) or not (False) (default False)
+    :param inflation: The inflation parameter
     :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
@@ -335,7 +340,8 @@ def get_stat_cpnt_communities(df: pd.DataFrame, project: str, weight: int,
     logging.debug(f"{test_type} for {project}, w:{weight}, "
                   f"g:{global_weight} cpnt: {cpnt}({cpnt_type})")
     outfile, outfile_ctrl = create_outfiles(project, weight, global_weight,
-                                            same_gene, feature, cpnt_type,
+                                            same_gene, inflation, feature,
+                                            cpnt_type,
                                             cpnt, test_type, community_file)
     res = {"project": project, "cpnt": cpnt,
            'pval': lm_maker(df, outfile, cpnt)}
@@ -346,7 +352,7 @@ def get_stat_cpnt_communities(df: pd.DataFrame, project: str, weight: int,
 
 
 def create_dataframe(project: str, weight: int, global_weight: int,
-                     same_gene: bool, feature: str = 'exon',
+                     same_gene: bool, inflation: float, feature: str = 'exon',
                      region: str = "", component_type: str = 'nt',
                      community_file: str = "",
                      from_communities: bool = True,
@@ -360,6 +366,7 @@ def create_dataframe(project: str, weight: int, global_weight: int,
     seen in `global_weight` project are taken into account
     :param same_gene: Say if we consider as co-localised, exons within the \
     same gene (True) or not (False)
+    :param inflation: The inflation parameter
     :param feature: The kind of feature to analyse
     :param from_communities: True if we only select gene/exons
     :param region: the region of interest to extract from gene
@@ -377,8 +384,8 @@ def create_dataframe(project: str, weight: int, global_weight: int,
         if community_file == "":
             result = ConfigGraph.get_community_file(project, weight,
                                                     global_weight,
-                                                    same_gene, feature,
-                                                    ".txt")
+                                                    same_gene, inflation,
+                                                    feature, ".txt")
         else:
             result = Path(community_file)
             if not result.is_file():
@@ -399,7 +406,8 @@ def create_dataframe(project: str, weight: int, global_weight: int,
     return df
 
 
-def create_dataframes(project, weight, global_weight, same_gene, feature,
+def create_dataframes(project, weight, global_weight, same_gene, inflation,
+                      feature,
                       region, test_type, component_type: str,
                       community_file: str
                       ) -> Tuple[pd.DataFrame, Dict]:
@@ -411,6 +419,7 @@ def create_dataframes(project, weight, global_weight, same_gene, feature,
     :param project: The project name, used only if global_weight = 0
     :param same_gene: Say if we consider as co-localised exon within the \
     same gene
+    :param inflation: The inflation parameter
     :param feature: The kind of analysed feature
     :param region: the region of interest to extract from gene
     :param test_type: The type of test to make (permutation or lm)
@@ -420,10 +429,10 @@ def create_dataframes(project, weight, global_weight, same_gene, feature,
     it equals to '' then weight, global weight and same genes parameter are \
     used to find the community files computed with ChIA-PET data.
     """
-    df = create_dataframe(project, weight, global_weight, same_gene,
+    df = create_dataframe(project, weight, global_weight, same_gene, inflation,
                           feature, region, component_type, community_file)
     df_ctrl = create_dataframe(project, weight, global_weight, same_gene,
-                               feature, region, component_type,
+                               inflation, feature, region, component_type,
                                from_communities=False)
     df_ctrl = df_ctrl.loc[-df_ctrl[f"id_{feature}"].isin(df[f"id_{feature}"]),
                           :].copy()
@@ -438,6 +447,7 @@ def multiple_nt_lm_launcher(ps: int,
                             global_weight: int,
                             project: str,
                             same_gene: bool,
+                            inflation: float,
                             feature: str = 'exon',
                             region: str = '',
                             component_type: str = "nt",
@@ -457,6 +467,7 @@ def multiple_nt_lm_launcher(ps: int,
     :param project: The project name, used only if global_weight = 0
     :param same_gene: Say if we consider as co-localised exon within the \
     same gene
+    :param inflation: The inflation parameter
     :param feature: The kind of analysed feature
     :param component_type: The type of component to analyse; It \
     can be 'nt', 'dnt' or 'aa'.
@@ -487,16 +498,16 @@ def multiple_nt_lm_launcher(ps: int,
     pool = mp.Pool(processes=min(ps, len(condition)))
     logging.debug("Creating tables")
     df, dic_com = create_dataframes(project, weight, global_weight,
-                                    same_gene, feature, region,
+                                    same_gene, inflation, feature, region,
                                     test_type, component_type, community_file)
     for project, weight, cpnt in condition:
         nfile_table = ConfigGraph.get_community_file(
-            project, weight, global_weight, same_gene, feature,
+            project, weight, global_weight, same_gene, inflation, feature,
             f"_{component_type}_table.txt", "community_enrichment")
         df.to_csv(nfile_table, sep="\t", index=False)
-        args = [df, project, weight, global_weight, same_gene, component_type,
-                cpnt, dic_com, feature, test_type, iteration, display_size,
-                community_file]
+        args = [df, project, weight, global_weight, same_gene, inflation,
+                component_type, cpnt, dic_com, feature, test_type, iteration,
+                display_size, community_file]
         processes.append(pool.apply_async(get_stat_cpnt_communities, args))
     results = [p.get(timeout=None) for p in processes]
     pool.close()
@@ -505,7 +516,7 @@ def multiple_nt_lm_launcher(ps: int,
     fdf["padj"] = multipletests(fdf['pval'].values, method='fdr_bh')[1]
     outfile = ConfigGraph.get_community_file(project, weight,
                                              global_weight,
-                                             same_gene, feature,
+                                             same_gene, inflation, feature,
                                              f"lmm-{component_type}_stat.txt",
                                              "community_enrichment")
     nfolder = outfile.parent / f"{component_type}_analysis"
@@ -523,6 +534,7 @@ def launcher_community_file(ps: int = 1,
                             global_weight: int = -1,
                             project: str = "GSM1018963_GSM1018964",
                             same_gene: bool = True,
+                            inflation: float = 1.5,
                             feature: str = 'exon',
                             region: str = '',
                             component_type: str = "nt",
@@ -556,9 +568,9 @@ def launcher_community_file(ps: int = 1,
     :param logging_level: Level of information to display (default DISABLE)
     """
     multiple_nt_lm_launcher(ps, weight, global_weight, project,
-                            same_gene, feature, region, component_type,
-                            test_type, iteration, display_size, community_file,
-                            logging_level)
+                            same_gene, inflation, feature, region,
+                            component_type, test_type, iteration, display_size,
+                            community_file, logging_level)
 
 
 if __name__ == "__main__":
diff --git a/src/find_interaction_cluster/sf_and_communities.py b/src/find_interaction_cluster/sf_and_communities.py
index 41728da8cfec21ee69cbe30eb1261f14dfc1a87a..0449bbf88e70be9456a96cb6870f597460e562d4 100644
--- a/src/find_interaction_cluster/sf_and_communities.py
+++ b/src/find_interaction_cluster/sf_and_communities.py
@@ -180,7 +180,7 @@ def glmm_maker(expanded_df: pd.DataFrame, outfile: Path) -> float:
     ... "community_size": [5, 7],
     ... "%reg in community": [40, 42.85], 'pval': [1, 0.5], 'padj': [1, 1]})
     >>> e_df = expand_dataframe(d)
-    >>> outfile = ConfigGraph.get_community_file("Test", 1, 1, True,
+    >>> outfile = ConfigGraph.get_community_file("Test", 1, 1, True, 1.5,
     ... "_stat.txt", "sf_community_enrichment")
     >>> glmm_maker(e_df, outfile)
     1.0
@@ -210,7 +210,8 @@ def glmm_maker(expanded_df: pd.DataFrame, outfile: Path) -> float:
 
 def glmm_statistics(df: pd.DataFrame, sf_name: str, reg: str,
                     project: str, weight: int, global_weight: int,
-                    same_gene: bool, feature: str = "exon") -> pd.Series:
+                    same_gene: bool, inflation: float,
+                    feature: str = "exon") -> pd.Series:
     """
     Create the glmm statistics for a given splicing factor with \
     given communities.
@@ -227,13 +228,14 @@ def glmm_statistics(df: pd.DataFrame, sf_name: str, reg: str,
     :param same_gene: Say if we consider as co-localised, exons within the \
     same gene (True) or not (False) (default False)
     :param feature: The kind of feature analysed
+    :param inflation: the inflation parameter
     :return: The glmm pvalue among with other informations
     """
     ndf = df.loc[-df['community'].isin(["All-community", "FASTERDB"]),
           :].copy()
     expanded_df = expand_dataframe(ndf)
     outfile = ConfigGraph.get_community_file(project, weight, global_weight,
-                                             same_gene, feature,
+                                             same_gene, inflation, feature,
                                              f"{sf_name}_{reg}_stat.txt",
                                              "sf_community_enrichment")
     noutfold = outfile.parent / "expanded_df"
@@ -274,6 +276,7 @@ def adapt_regulated_list(cnx: sqlite3.Connection,
 def get_stat4communities(sf_name: str, reg: str,
                          project: str, weight: int,
                          global_weight: int, same_gene: bool,
+                         inflation: float,
                          feature: str = 'exon',
                          ) -> Tuple[pd.DataFrame, pd.Series]:
     """
@@ -290,13 +293,14 @@ def get_stat4communities(sf_name: str, reg: str,
     seen in `global_weight` project are taken into account
     :param same_gene: Say if we consider as co-localised, exons within the \
     same gene (True) or not (False) (default False)
+    :param inflation: The inflation parameter
     :param feature: The kind of analysed feature
     """
     logging.debug(f"Working on {sf_name}-{reg}, for {project}, w:{weight}, "
                   f"g:{global_weight}")
     cnx = sqlite3.connect(ConfigGraph.db_file)
     result = ConfigGraph.get_community_file(project, weight, global_weight,
-                                            same_gene, feature,
+                                            same_gene, inflation, feature,
                                             ".txt")
     communities = get_communities_basefile(result, 0)
     regulated_dic, number = get_every_events_4_a_sl(cnx, sf_name, reg)
@@ -328,7 +332,7 @@ def get_stat4communities(sf_name: str, reg: str,
     d['project'] = [project] * len(d["community"])
     df = pd.DataFrame(d)
     s = glmm_statistics(df, sf_name, reg, project, weight, global_weight,
-                        same_gene, feature)
+                        same_gene, inflation, feature)
     return df, s
 
 
@@ -365,7 +369,8 @@ def multiple_stat_launcher(ps: int,
                            weight: int,
                            global_weight: int,
                            project: str,
-                           same_gene: bool, feature: str = 'exon',
+                           same_gene: bool, inflation: float,
+                           feature: str = 'exon',
                            logging_level: str = "DISABLE"):
     """
     Launch the statistical analysis for every
@@ -379,6 +384,7 @@ def multiple_stat_launcher(ps: int,
     :param same_gene: Say if we consider as co-localised exon within the \
     same gene
     :param feature: The feature we want to analyse
+    :param inflation: the inflation parameter
     :param logging_level: Level of information to display
     """
     ConfigGraph.community_folder.mkdir(exist_ok=True, parents=True)
@@ -394,7 +400,7 @@ def multiple_stat_launcher(ps: int,
     for project, weight, sf_name, reg in condition:
         ckey = get_key(project, weight)
         args = [sf_name, reg, project, weight, global_weight, same_gene,
-                feature]
+                inflation, feature]
         if ckey in processes:
             processes[ckey].append(pool.apply_async(get_stat4communities, args))
         else:
@@ -409,7 +415,7 @@ def multiple_stat_launcher(ps: int,
         df = pd.concat(list_df, axis=0, ignore_index=True)
         outfile = ConfigGraph.get_community_file(project, weight,
                                                  global_weight,
-                                                 same_gene, feature,
+                                                 same_gene, inflation, feature,
                                                  "_stat.txt",
                                                  "sf_community_enrichment")
         df.to_csv(outfile, sep="\t", index=False)
@@ -418,7 +424,7 @@ def multiple_stat_launcher(ps: int,
                                        method='fdr_bh')[1]
         outfile = ConfigGraph.get_community_file(project, weight,
                                                  global_weight,
-                                                 same_gene, feature,
+                                                 same_gene, inflation, feature,
                                                  "_glmm_stat.txt",
                                                  "sf_community_enrichment")
         glm_df.to_csv(outfile, sep="\t", index=False)