diff --git a/bin/1.2_filter_motifs/compareBed_runinfo.R b/bin/1.2_filter_motifs/compareBed_runinfo.R
index 4a7af6f..4c5686d 100644
--- a/bin/1.2_filter_motifs/compareBed_runinfo.R
+++ b/bin/1.2_filter_motifs/compareBed_runinfo.R
@@ -8,7 +8,13 @@
 #             adds a column with a flag "contains_maxpos"
 #             and creates a file with information of the bedtool comparison
 
-# TODO: check number of columns, implement make.unique in a better way 
+# parameters: Parameters are not named. Respect the parameter order.
+#             min:            minimum footprint size threshold 
+#             max:            maximum footprint size threshold
+#             input_raw:      unfiltered BED-file
+#             input_filtered: filtered BED-file (after bedtools subtract)
+#             output:         output path/file
+#             output_stats:   output file with general info of the comparison
 
 # parsing parameters
 library(data.table)
@@ -18,8 +24,10 @@ max = as.numeric(args[2])
 input_raw = args[3]
 input_filtered = args[4]
 output = args[5]
+output_stats = args[6]
+
+data_filtered = fread(input_filtered, sep='\t')
 
-data_filtered = fread(input_filtered)
 # check if data has less than 9 columns
 if (ncol(data_filtered) < 9) {
 	stop("footprint file has less than 9 columns. exiting.")
@@ -51,7 +59,7 @@ data_filtered[[8]] = data_filtered[[8]] - data_filtered[[2]]
 fwrite(data_filtered, output, col.names=FALSE, quote = FALSE, sep = '\t')
 
 # data is the initial data before any comparisons have been done (-d parameter of compareBed.sh)
-data = fread(input_raw)
+data = fread(input_raw, sep='\t')
 
 # some statistics about the bedtool comparisons are stored in FilterMotifs.stats
 sum_data = sum(data[[3]]-data[[2]])
@@ -62,4 +70,4 @@ length_data = formatC(mean(data[[3]]-data[[2]]), digits = 4)
 length_filtered = formatC(mean(data_filtered[[7]]), digits = 4)
 stats = data.frame(sum_nt_input = sum_data, sum_nt_filtered = sum_filtered, quotient_of_nt = difference_nt, loss_of_nt = loss_nt, mean_length_input = length_data, mean_length_filtered = length_filtered, flag_1_ratio = length(which(data_filtered$containsMaxpos == 1))/dim(data_filtered)[1])
 stats = t(stats)
-write.table(stats, "./FilterMotifs.stats", col.names = FALSE, quote = FALSE, sep = '\t')
+write.table(stats, output_stats, col.names = FALSE, quote = FALSE, sep = '\t')