diff --git a/src/find_interaction_cluster/clip_figures/clip_launcher_4_many_communities.py b/src/find_interaction_cluster/clip_figures/clip_launcher_4_many_communities.py
new file mode 100644
index 0000000000000000000000000000000000000000..f9e6f2ea305c375c321b7f0034382d305374e904
--- /dev/null
+++ b/src/find_interaction_cluster/clip_figures/clip_launcher_4_many_communities.py
@@ -0,0 +1,189 @@
+#!/usr/bin/env python3
+
+# -*- coding: UTF-8 -*-
+
+"""
+Description: Launch Clip analysis for many communities
+"""
+
+
+import logging
+from typing import Tuple, Dict
+from pathlib import Path
+from .config import ConfigClip
+from .clip_analyser import create_table, \
+ add_regulation_column, create_community_fig, find_or_create_community, \
+ ConfigGraph, logging_def
+import multiprocessing as mp
+from itertools import product
+import lazyparser as lp
+import numpy as np
+import subprocess as sp
+
+
+def select_community_file(project: str, weight: int, global_weight: int,
+ same_gene: bool, inflation: float, cell_line: str,
+ feature: str, clip_file: Path,
+ community_file: str = "") -> Tuple[Path, Path]:
+ """
+ Return the community file and output folder that will be used.
+
+ :param project: The name of the project of interest
+ :param weight: The minimum 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 \
+ 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 cell_line: Interactions are only selected from projects made on \
+ a specific cell line (ALL to disable this filter). (default ALL)
+ :param feature: The feature we want to analyse (default 'exon')
+ :param clip_file: A bed file containing clip
+ :param community_file: A file containing custom communities. If \
+ it equals to '' then weight, global weight and same genes parameter are \
+ used to find the community files computed with ChIA-PET data.
+ :return: The community file used and the output folder used.
+
+ """
+ if community_file == "":
+ com_file = find_or_create_community(project, weight, global_weight,
+ same_gene, inflation, cell_line,
+ feature)
+ else:
+ com_file = Path(community_file)
+ if not com_file.is_file():
+ raise FileNotFoundError(f"File {com_file} was not found !")
+ outname = clip_file.name.split('.')[0]
+ output = ConfigClip.output_folder / \
+ f"multiTAD_CLIP_community_figures-{feature}-{cell_line}" / outname
+ return com_file, output
+
+
+def create_figure(p: Dict , clip_file: Path,
+ feature_bed: Path,
+ community_file: Tuple[str, str],
+ test_type: str = "permutation",
+ iteration: int = 10000, display_size: bool = False,
+ sl_reg: bool = False) -> Path:
+ """
+ Create the final figure
+ :param p: A dictionary containing parameter used to compute \
+ HipMCL communities
+ :param clip_file: A bed file containing clip
+ :param feature_bed: A bed files containing exons or genes depending on \
+ feature parameter.
+ :param test_type: The king of test to perform for frequency analysis. \
+ (default 'lm') (choose from 'lm', 'permutation')
+ :param iteration: The number of iteration to make
+ :param community_file: A Tuple containing a file containing custom \
+ communities. If it equals to '' then weight, global weight and \
+ same genes parameter are used to find the community files computed \
+ with ChIA-PET data. The second item of the tuple is it's name.
+ :param display_size: True to display the size of the community. \
+ False to display nothing. (default False)
+ :param sl_reg: True to display the FaRLine regulation of the \
+ same factor, False to not display it.
+ :return: Folder containing he figures
+ """
+ logging.info(f"Working on {clip_file} - {community_file[0]} - "
+ f"{community_file[1]}")
+ com_file, output = select_community_file(p["project"], p["weight"],
+ p["global_weight"],
+ p["same_gene"], p["inflation"],
+ p["cell_line"],
+ p["feature"], clip_file,
+ community_file[0])
+ output.mkdir(exist_ok=True, parents=True)
+ outfile = output / f"{community_file[1]}.tmp.pdf"
+ final_table = create_table(p["feature"], clip_file, feature_bed, com_file)
+ if sl_reg:
+ final_table = add_regulation_column(final_table,
+ clip_file.name.split("_")[0],
+ p["feature"])
+ create_community_fig(final_table, p["feature"], "peak_density", outfile,
+ test_type, iteration=iteration,
+ display_size=display_size)
+ return outfile.parent
+
+
+def merge_figures(folder: Path) -> None:
+ """
+ Merge the figures together using imageMagick
+
+ :param folder: A folder containing pdf files
+ """
+ fig_name = folder.name
+ cmd = f"montage -geometry +1+1 -tile 1X6 " \
+ f"-compress jpeg -density 100 " \
+ f"{folder}/*.tmp.pdf {folder}/{fig_name}.pdf"
+ sp.check_call(cmd, shell=True)
+
+
+@lp.parse(test_type=["permutation", "lm"], feature=["gene", "exon"])
+def clip_folder_analysis(clip_folder: str, weight: int,
+ global_weight: int, same_gene: bool = True,
+ project: str = "GSM1018963_GSM1018964",
+ inflation: float = 1.5,
+ cell_line: str = "ALL",
+ feature: str = "exon",
+ test_type: str = "permutation",
+ iteration: int = 10000, display_size: bool=False,
+ sl_reg: bool = False) -> None:
+ """
+ Create the final figure
+ :param project: The name of the project of interest
+ :param weight: The minimum 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 \
+ 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 cell_line: Interactions are only selected from projects made on \
+ a specific cell line (ALL to disable this filter). (default ALL)
+ :param feature: The feature we want to analyse (default 'exon')
+ :param clip_folder: A folder containing clip file
+ :param test_type: The king of test to perform for frequency analysis. \
+ (default 'lm') (choose from 'lm', 'permutation')
+ :param iteration: The number of iteration to make
+ :param display_size: True to display the size of the community. \
+ False to display nothing. (default False)
+ :param sl_reg: True to display the FaRLine regulation of the \
+ same factor, False to not display it.
+ :param ps: The number of processes to create (default 1)
+ """
+ logging_def(ConfigGraph.community_folder, __file__, "INFO")
+ clip_folder = Path(clip_folder)
+ feature_bed = ConfigClip.bed_gene if feature == "gene" \
+ else ConfigClip.bed_exon
+ files = list(clip_folder.glob("*.bed")) + \
+ list(clip_folder.glob("*.bed.gz"))
+ files = [files[0]]
+
+ processes = []
+ p = {"project": project, "weight": weight, "global_weight": global_weight,
+ "same_gene": same_gene, "inflation": inflation,
+ "cell_line": cell_line, "feature": feature}
+
+ prod = list(product(files, zip(ConfigClip.communities,
+ ConfigClip.communities_name)))
+ pool = mp.Pool(processes=min(len(prod), ConfigGraph.cpu))
+ for mfile, community_file in prod:
+ if community_file[0] == "":
+ tmp = \
+ f"HIPMCL_g{global_weight}_w{weight}_{inflation}"
+ community_file = (community_file[0], tmp)
+ args = [p, mfile, feature_bed, community_file, test_type, iteration,
+ display_size, sl_reg]
+ processes.append(pool.apply_async(create_figure, args))
+ list_path = [str(p.get(timeout=None)) for p in processes]
+ list_path = np.unique(list_path)
+ for my_folder in list_path:
+ merge_figures(Path(my_folder))
+
+
+if __name__ == "__main__":
+ clip_folder_analysis()
\ No newline at end of file