diff --git a/bin/2.2_motif_estimation/merge_similar_clusters.R b/bin/2.2_motif_estimation/merge_similar_clusters.R
index 0104d05..d9b2373 100644
--- a/bin/2.2_motif_estimation/merge_similar_clusters.R
+++ b/bin/2.2_motif_estimation/merge_similar_clusters.R
@@ -1,77 +1,79 @@
-#!/usr/bin/env Rscript
-if (!require(optparse)) install.packages("optparse"); library(optparse)
-
-option_list <- list(
-  make_option(opt_str = c("-i", "--input"), default = NULL, help = "Input TSV-file. Output from merged tomtom results", metavar = "character"),
-  make_option(opt_str = c("-l", "--list"), default = NULL, help = "Numerically sorted whitespace separated list of absolute fasta-file paths", metavar = "character"),
-  make_option(opt_str = c("-w", "--min"), default = NULL, help = "Minimum weight of edge allowed in graph clusters.", metavar = "character")
-)
-
-opt_parser <- OptionParser(option_list = option_list,
-                           description = "Adding Cluster ID to Query_ID Column")
-
-opt <- parse_args(opt_parser)
-
-#' Merging FASTA-files, which motifs are similar.
-#'
-#' @parameter tsv_in <string> Path to TSV file generated by Tomtom.
-#'                            The input for Tomtom is a from all clusters merged meme-file.
-#' @parameter file_list <string> Numerically sorted whitespace separated list of absolute fasta-file paths
-#' @parameter min_weight <INT> Minimum weight of edge allowed in graph clusters.
-#'
-#' @author René Wiegandt
-#' @contact rene.wiegandt(at)mpi-bn.mpg.de
-merge_similar <- function(tsv_in, file_list, min_weight){
-
-  files <- unlist(as.list(strsplit(file_list, ",")))
-
-  # split the string on the character "." in the first to columns and safe the last value each, to get the number of the cluster.
-  tsv <- data.table::fread(tsv_in, header = TRUE, sep = "\t",colClasses = 'character')
-  query_cluster <- unlist(lapply(strsplit(tsv[["Query_ID"]],"\\."), function(l){
-    tail(l,n=1)
-  }))
-  target_cluster <- unlist(lapply(strsplit(tsv[["Target_ID"]],"\\."), function(l){
-    tail(l,n=1)
-  }))
-
-  # create data.table with only the cluster-numbers
-  sim_not_unique <- data.table::data.table(query_cluster,target_cluster)
-  # convert from character to numeric values
-  sim_not_unique[, query_cluster := as.numeric(query_cluster)]
-  sim_not_unique[, target_cluster := as.numeric(target_cluster)]
-
-  # remove rows if column 1 is idential to column 2
-  edgelist <- sim_not_unique[query_cluster != target_cluster]
-
-  # create graph from data.frame
-  g <- igraph::graph_from_edgelist(as.matrix(edgelist))
-  # converting graph to adjacency matrix
-  adj_matrix <- igraph::get.adjacency(g, names = T)
-  # generating weighted graph from adjacency matrix
-  g_adj <- igraph::graph_from_adjacency_matrix(adj_matrix, weighted = T)
-
-  # get subgraphs from graph with edges of weight > min_weight
-  s1 <- igraph::subgraph.edges(g_adj, igraph::E(g_adj)[igraph::E(g_adj)$weight>min_weight], del=F)
-  png('motif_clusters.png')
-  plot(s1)
-  dev.off()
-  clust <- igraph::clusters(s1)
-  if (clust$no < 1){
-    b <- lapply(files, function(f){
-      system(paste("cat",f,">",basename(f)))
-    })
-  }
-  # merge FASTA-files depending on the clustered graphs
-  a <- lapply(seq(from = 1, to = clust$no, by = 1), function(i){
-    cl <- as.vector(which(clust$membership %in% c(i)))
-    fasta_list <- paste(files[cl], collapse = " ")
-    name <- paste0("Cluster_",i,".fasta")
-    system(paste("cat",fasta_list,">",name))
-  })
-}
-
-
-# run function merge_similar with given parameteres if not in interactive context (e.g. run from shell)
-if (!interactive()) {
-  merge_similar(opt$input, opt$list, opt$min)
-}
+#!/usr/bin/env Rscript
+if (!require(optparse)) install.packages("optparse"); library(optparse)
+
+option_list <- list(
+  make_option(opt_str = c("-i", "--input"), default = NULL, help = "Input TSV-file. Output from merged tomtom results", metavar = "character"),
+  make_option(opt_str = c("-l", "--list"), default = NULL, help = "Numerically sorted whitespace separated list of absolute fasta-file paths", metavar = "character"),
+  make_option(opt_str = c("-w", "--min"), default = NULL, help = "Minimum weight of edge allowed in graph clusters.", metavar = "character")
+)
+
+opt_parser <- OptionParser(option_list = option_list,
+                           description = "Adding Cluster ID to Query_ID Column",
+                           epilogue = "Author: Rene Wiegandt <Rene.Wiegandt@mpi-bn.mpg.de>")
+
+opt <- parse_args(opt_parser)
+
+#' Merging FASTA-files, which motifs are similar.
+#'
+#' @parameter tsv_in <string> Path to TSV file generated by Tomtom.
+#'                            The input for Tomtom is a from all clusters merged meme-file.
+#' @parameter file_list <string> Numerically sorted comma separated list of absolute fasta-file paths
+#' @parameter min_weight <INT> Minimum weight of edge allowed in graph clusters.
+#'
+#' @author René Wiegandt
+#' @contact rene.wiegandt(at)mpi-bn.mpg.de
+merge_similar <- function(tsv_in, file_list, min_weight){
+
+  files <- unlist(strsplit(file_list, ","))
+
+  # split the string on the character "." in the first to columns and safe the last value each, to get the number of the cluster.
+  tsv <- data.table::fread(tsv_in, header = TRUE, sep = "\t",colClasses = 'character')
+  query_cluster <- vapply(strsplit(tsv[["Query_ID"]],"\\."), function(l){
+    tail(l, n = 1)
+  },"")
+  target_cluster <- vapply(strsplit(tsv[["Target_ID"]],"\\."), function(l){
+    tail(l, n = 1)
+  },"")
+
+  # create data.table with only the cluster-numbers
+  sim_not_unique <- data.table::data.table(as.numeric(query_cluster),as.numeric(target_cluster))
+
+  # remove rows if column 1 is identical to column 2
+  edgelist <- sim_not_unique[query_cluster != target_cluster]
+
+  # create graph from data.frame
+  g <- igraph::graph_from_edgelist(as.matrix(edgelist))
+  # converting graph to adjacency matrix
+  adj_matrix <- igraph::get.adjacency(g, names = T)
+  # generating weighted graph from adjacency matrix
+  g_adj <- igraph::graph_from_adjacency_matrix(adj_matrix, weighted = T)
+
+  # get subgraphs from graph with edges of weight > min_weight
+  s1 <- igraph::subgraph.edges(g_adj, igraph::E(g_adj)[igraph::E(g_adj)$weight > min_weight], del = F)
+  png('motif_clusters.png')
+  plot(s1)
+  dev.off()
+  clust <- igraph::clusters(s1)
+  if (clust$no < 1) {
+    b <- lapply(files, function(f){
+      system(paste("cat",f,">",basename(f)))
+    })
+  }
+  # merge FASTA-files depending on the clustered graphs
+  a <- lapply(seq(from = 1, to = clust$no, by = 1), function(i){
+    #get vector with cluster ids, which are clustered together in "motif cluster" i
+    cl <- as.vector(which(clust$membership %in% c(i)))
+    #create string, which represents a list, containing all FASTA-files to be merged
+    fasta_list <- paste(files[cl], collapse = " ")
+    #create name for merged FASTA-file
+    name <- paste0("Cluster_",i,".fasta")
+    #merge fasta files
+    system(paste("cat",fasta_list,">",name))
+  })
+}
+
+
+# run function merge_similar with given parameteres if not in interactive context (e.g. run from shell)
+if (!interactive()) {
+  merge_similar(opt$input, opt$list, opt$min)
+}