Venn2Plot

VeennDiagramm_bed_files.py

@@ -3,91 +3,54 @@
 # Lab : DIADE - IRD
 # University : Montpellier - France
 
+####-------- Intersection of bed files --------####
+# Autor: Fadwa EL KHADDAR
+# Lab : DIADE - IRD
+# University : Montpellier - France
+
 import os
 import subprocess
 import pandas as pd
 import matplotlib
 import matplotlib.pyplot as plt
-from matplotlib_venn import venn3_unweighted
+from matplotlib_venn import venn2_unweighted
 import argparse
 import tkinter as tk
 from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
 matplotlib.use('TkAgg')
 
 # Arguments
-parser = argparse.ArgumentParser(description="Venn Diagramm of gff and bed files")
+parser = argparse.ArgumentParser(description="Venn Diagram of gff and bed files")
 parser.add_argument('-bed1', type=str, help="Path to the first bed file")
 parser.add_argument('-bed2', type=str, help="Path to the second bed file")
-parser.add_argument('-bed3', type=str, help="Path to the third bed file")
 args = parser.parse_args()
 
 bed1 = args.bed1
 bed2 = args.bed2
-bed3 = args.bed3
 
 # Extract file names
-
 filename1 = os.path.splitext(os.path.basename(bed1))[0]
 filename2 = os.path.splitext(os.path.basename(bed2))[0]
-filename3 = os.path.splitext(os.path.basename(bed3))[0]
-
-# Intersection of bedfile , You have to load bedtools
 
-command2 = subprocess.Popen(f"multiIntersectBed -i  {bed1} {bed2} {bed3} ", shell=True, stdout=subprocess.PIPE)
+# Intersection of bed files using bedtools
+command2 = subprocess.Popen(f"bedtools intersect -u -a {bed1} -b {bed2}", shell=True, stdout=subprocess.PIPE)
 output, error = command2.communicate()
 results = output.decode('utf-8').strip()
 
-# Creation of Dataframe
-
-columns = ["Chro", "Start", "End", "nb_overlap_file", "label_overlap_file","None1", "None2", "None3"]
-rows= [line.split('\t') for line in results.split('\n') if line]
-
-raw_dataframe=pd.DataFrame(rows, columns=columns)
-df= raw_dataframe.loc[:, ["Chro", "Start", "End", "nb_overlap_file", "label_overlap_file"]]
-
-# Conversion of values
-df['nb_overlap_file'] = df['nb_overlap_file'].astype(int)
-df['label_overlap_file'] = df['label_overlap_file'].astype(str)
-
-
-# Different filters
-
-filtre1 = df[df['nb_overlap_file'] == 3]
-count1 = filtre1.shape[0]
-
+# Create DataFrame
+columns = ["Chro", "Start", "End"]
+rows = [line.split('\t') for line in results.split('\n') if line]
+df = pd.DataFrame(rows, columns=columns)
 
-filtre2 = df.loc[(df['nb_overlap_file'] == 2) & (df['label_overlap_file'] == '1,3')]
-count2 = filtre2.shape[0]
+# Venn Diagram Construction
+count1 = df.shape[0]
+count2 = len(pd.read_csv(bed1, sep='\t'))
+count3 = len(pd.read_csv(bed2, sep='\t'))
 
-
-filtre3 = df.loc[(df['nb_overlap_file'] == 2) & (df['label_overlap_file'] == '1,2')]
-count3 = filtre3.shape[0]
-
-
-filtre4 = df.loc[(df['nb_overlap_file'] == 2) & (df['label_overlap_file'] == '2,3')]
-count4 = filtre4.shape[0]
-
-
-filtre5 = df[(df['nb_overlap_file'] == 1) & (df['label_overlap_file'] == '1')]
-count5=filtre5.shape[0]
-
-
-filtre6 = df[(df['nb_overlap_file'] == 1) & (df['label_overlap_file'] == '2')]
-count6 = filtre6.shape[0]
-
-
-filtre7 = df[(df['nb_overlap_file'] == 1) & (df['label_overlap_file'] == '3')]
-count7 = filtre7.shape[0]
-
-
-# Venn Diagramm Construction
-
-subset=[count5,count6,count3,count7,count2,count4,count1]
-venn3_unweighted(subset, set_labels=(filename1, filename2,filename3))
-fig, ax = plt.subplots()
-venn3_unweighted(subset, set_labels=(filename1, filename2, filename3), ax=ax)
+subset = (count2, count3, count1)
+venn2_unweighted(subset, set_labels=(filename1, filename2))
 fig, ax = plt.subplots()
-venn3_unweighted(subset, set_labels=(filename1, filename2, filename3), ax=ax)
+venn2_unweighted(subset, set_labels=(filename1, filename2), ax=ax)
 
 root = tk.Tk()
 root.title("Venn Diagram")
@@ -95,4 +58,4 @@ root.title("Venn Diagram")
 canvas = FigureCanvasTkAgg(fig, master=root)
 canvas.draw()
 canvas.get_tk_widget().pack(side=tk.TOP, fill=tk.BOTH, expand=1)
-root.mainloop()
\ No newline at end of file
+root.mainloop()