--- a/cluster_table2krona_format.py	Fri May 14 11:08:46 2021 +0000
+++ b/cluster_table2krona_format.py	Tue May 18 11:03:57 2021 +0000
@@ -3,6 +3,7 @@
 import re
 from collections import defaultdict
 import argparse
+import csv
 
 parser = argparse.ArgumentParser()
 parser.add_argument("-i" ,"--input", type=argparse.FileType('r'), help="path to file CLUSTER_table.csv")
@@ -12,26 +13,35 @@
 args = parser.parse_args()
 
 column = 6 if args.use_manual else 4
-
+if args.use_manual:
+    annotation="Final_annotation"
+else:
+    annotation="Automatic_annotation"
 
 header = False
 clust_info = {}
 counts = defaultdict(lambda: 0)
 top_clusters = 0
 with open(args.input.name, 'r') as f:
-    for l in f:
-        parts = l.split()
-        if re.match('.*Cluster.+Supercluster.+Size.+Size_adjusted.+Automatic_annotation.+TAREAN_annotation.+Final_annotation', l):
-            print("header detected")
+    csv_reader = csv.reader(f, delimiter = "\t")
+    for parts in csv_reader:
+        if len(parts) == 0:
+            continue
+        if parts[0] == "Cluster" and parts[1]== "Supercluster":
             header = True
+            header_columns = parts
+            column = header_columns.index(annotation)
             continue
         if header:
             classification = "Top_clusters\t" + "\t".join(parts[column].split("/")[1:]).replace('"','')
             counts[classification] += int(parts[3])
             top_clusters += int(parts[3])
+        elif len(parts) >= 2:
+            try:
+                clust_info[parts[0].replace('"', '')] = int(parts[1])
+            except ValueError:
+                pass
 
-        elif len(parts) >= 2:
-            clust_info[parts[0].replace('"', '')] = int(parts[1])
 
 counts['Singlets'] = clust_info['Number_of_singlets']
 counts['Small_cluster'] = int(clust_info['Number_of_reads_in_clusters']) - top_clusters

--- a/summarize_cluster_table.xml	Fri May 14 11:08:46 2021 +0000
+++ b/summarize_cluster_table.xml	Tue May 18 11:03:57 2021 +0000
@@ -1,5 +1,5 @@
-<tool id="summarize_annotation" name="Make summary of CLUSTER_TABLE" version="1.0.0">
-  <description> Simple utility to summarize final annotation from RepeatExplorer CLUSTER_TABLE</description>
+<tool id="summarize_annotation" name="Repeat proportions from CLUSTER_TABLE" version="1.0.0">
+  <description> Simple utility to summarize final annotations from RepeatExplorer CLUSTER_TABLE</description>
   <requirements>
     <requirement type="package">r-optparse</requirement>
   </requirements>
@@ -16,12 +16,12 @@
     </inputs>
 
     <outputs>
-         	<data format="tabular" name="output" label="Summary of repeat proportion from ${cluster_table.hid}"/>
+         	<data format="tabular" name="output" label="Summary of repeat proportions from ${cluster_table.hid}"/>
     </outputs>
     <help>
-      **Summarization of annotation from CLUSTER_TABLE**
+      **The tool calculates genome proportions of identified repeats based on cluster annotations in CLUSTER_TABLE.csv**
           
-      Input file CLUSTER_TABLE.csv  must contains filled "Final_annotation" column. Contamination and organelle clusters are discarded from quantification, cluster table must also contain header - see example.
+	  The column "Final_annotation" must be filled in the input file CLUSTER_TABLE.csv. Contamination and organelle clusters are discarded from quantification. Table header with information about numbers of analyzed reads should remain unchanged - see example below.
 
       Example of CLUSTER_TABLE.csv: ::