quick graphical analysis of the yeast's GATC

src/GATC_analysis.py

+import numpy as np
+import pandas as pd
+import matplotlib.pyplot as plt
+from Bio import SeqIO
+import math
+
+df = pd.read_csv("/home/nathan/projects/vscode_nextflow/nextflow-nathan/results/GATC/sites_yeast.bed", 
+                 header = None, 
+                 sep = '\t')
+
+regions_chro = list()
+chromosomes = list()
+i = 0
+sites_region = list()
+j = 0
+chrom_regions = list()
+chrom_length = list()
+chrom = str()
+chromosome_sites = list()
+sites = list()
+id_list = list()
+
+for rec in SeqIO.parse("/home/nathan/projects/vscode_nextflow/nextflow-nathan/data/genome/GCF_000146045.2_R64_genomic.fna",
+                       "fasta"):
+    seq = rec.seq
+    chrom_length.append(len(seq))
+    
+    name = rec.description
+    id_list.append(name[43 : -19])
+
+for row in df.itertuples():
+    if len(chrom) <= 0:
+        chrom = row[1]
+        
+    if row[1] != chrom:
+        chromosome_sites.append(sites)
+        sites = list()
+        chrom = row[1]
+    
+    sites.append(row[3])        
+
+chromosome_sites.append(sites)
+
+for sites in chromosome_sites:
+    
+    region = np.linspace(1, max(sites) + 100, round((max(sites) + 100) / 10000))
+    chrom_regions.append(region)
+    
+    for site in sites:
+        
+        if site > region[i]:
+            i += 1
+            sites_region.append(j)
+            j = 0
+        j += 1
+    i = 0
+    sites_region.append(j)
+    chromosomes.append(sites_region)
+    sites_region = list()
+    
+
+fig, axes = plt.subplots(math.ceil(len(chromosomes) / 5), 5 )
+
+i = 0
+j = 0
+
+for chrom, regions, name in zip(chromosomes, chrom_regions, id_list):
+    
+    if j >= 5:
+        j = 0
+        i += 1
+        
+    axes[i, j].set_title(name)
+    axes[i, j].set_ylabel("site number / bin")
+    axes[i, j].plot(regions, chrom)
+    j += 1
+    
+plt.tight_layout(pad = 4.5)
+plt.show()
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