diff --git a/README.md b/README.md
index d080783..3c6e740 100644
--- a/README.md
+++ b/README.md
@@ -54,14 +54,14 @@ Required arguments:
 	--genome_fasta		 Path to genome in FASTA-format
 	--motif_db		 Path to motif-database in MEME-format
 	--config		 Path to UROPA configuration file
- 	--organism 		 Input organism [hg38 | hg19 | mm9 | mm10]
+	--organism 		 Input organism [hg38 | hg19 | mm9 | mm10]
 	--out			 Output Directory (Default: './out/')
 
 Optional arguments:
 
 	--help [0|1]		1 to show this help message. (Default: 0)
 	--gtf_path		Path to gtf-file. If path is set the process which creates a gtf-file is skipped.
-	--tfbs_path 		Path to directory with output from tfbsscan. If given tfbsscan will be skipped.
+	--tfbs_path 		Path to directory with tfbsscan output. If given tfbsscan will be skipped.
 
 	Footprint extraction:
 	--window_length INT	This parameter sets the length of a sliding window. (Default: 200)
@@ -78,7 +78,7 @@ Optional arguments:
 	Sequence preparation/ reduction:
 	--kmer INT		K-mer length (Default: 10)
 	--aprox_motif_len INT	Motif length (Default: 10)
-	--motif_occurence FLOAT	Percentage of motifs over all sequences. Use 1 (Default) to assume every sequence contains a motif.
+	--motif_occurrence FLOAT	Percentage of motifs over all sequences. Use 1 (Default) to assume every sequence contains a motif.
 	--min_seq_length Interations	Remove all sequences below this value. (Default: 10)
 	Clustering:
 	--global INT		Global (=1) or local (=0) alignment. (Default: 0)
@@ -96,14 +96,17 @@ Optional arguments:
 	--tomtom_treshold FLOAT	Threshold for similarity score. (Default: 0.01)
 	--best_motif INT	Get the best X motifs per cluster. (Default: 3)
 	--gap_penalty INT	Set penalty for gaps in GLAM2 (Default: 1000)
+	--seed Set seed for GLAM2 (Default: 123456789)
 	Moitf clustering:
-	--cluster_motif	Boolean	If 1 pipeline clusters motifs. If its 0 it does not. (Default: 0)
+	--cluster_motif	Boolean	If 1 pipeline clusters motifs. If its 0 it does not. (Defaul: 0)
 	--edge_weight INT	Minimum weight of edges in motif-cluster-graph (Default: 5)
 	--motif_similarity_thresh FLOAT	Threshold for motif similarity score (Default: 0.00001)
 
 	Creating GTF:
 	--tissues List/String 	List of one or more keywords for tissue-/category-activity, categories must be specified as in JSON
 				config
+	Evaluation:
+	--max_uropa_runs INT	 Maximum number UROPA runs running parallelized (Default: 10)
 All arguments can be set in the configuration files
  ```
 
diff --git a/bin/1.2_filter_motifs/compareBed.sh b/bin/1.2_filter_motifs/compareBed.sh
index aa97c95..3d25631 100644
--- a/bin/1.2_filter_motifs/compareBed.sh
+++ b/bin/1.2_filter_motifs/compareBed.sh
@@ -5,10 +5,10 @@
 
 # desciption: This scripts uses bedtools to find new, non overlapping regions
 #             between input data in BED-format and a group of known motifs in
-#             BED-format. 
+#             BED-format.
 
 #             For parameter description, run the script without parameters or -h.
-#             The output is a file with the filtered footprints and the log file compareBed.stats
+#             The output is a file with the filtered footprints and the log file compareBed.log
 
 # One R scripts is used, compareBed_runinfo.R, stored in the same directory.
 # Parameter values (file/directory paths) must not contain the | symbol, because it is chosen as "sed"-field separator.
@@ -124,7 +124,7 @@ then
 	echo "              -o   --output       output path/file ; default dir current directory and filename is newMotifs.bed and newMotifs.bed.fasta"
 	echo "              -h --help           shows this help message"
 	echo ""
-	echo " Note: file paths must not contain the '|' pipe symbol" 
+	echo " Note: file paths must not contain the '|' pipe symbol"
 	exit 0
 fi
 
@@ -188,7 +188,7 @@ cat $data | sed 's/[ \t]*$//' > "$workdir"/filtered.bed
 # motiffiles either from a directory OR comma separated list
 if [ -d "$motifs" ]
 then
-	# creates an array of all files with bed in its name in the directory $motifs  
+	# creates an array of all files with bed in its name in the directory $motifs
 	declare -a motiffiles=(`ls $motifs | grep -i '.bed$' | sed "s|^|$motifs\/|g" | tr '\n' ' ' | sed "s|//|/|g"`)
 
 # the else case means, that the motiffiles were passed comma separated with no whitespace.
@@ -264,9 +264,9 @@ fi
 
 # remove short/long motivs, make unique ids (relevant for some splitted tfbs from subtract) and handle maxScorePosition
 # also creates a small output file with information about the comparison
-Rscript $path/compareBed_runinfo.R $min $max $data "$workdir"/filtered.bed "$workdir"/filtered_flagged.bed "$workdir"/compareBed.stats
+Rscript $path/compareBed_runinfo.R $min $max $data "$workdir"/filtered.bed "$workdir"/filtered_flagged.bed "$workdir"/compareBed.log
 # check if Rscript executed without errors
-if [ $? -gt 0 ] 
+if [ $? -gt 0 ]
 then
 	exit 1
 fi
@@ -279,15 +279,15 @@ then
 	# add initial number of footprints to the log file
 	fp_initial=`cat $data | wc -l`
 	fp_initial=`expr $fp_initial - 1`
-	echo $fp_initial | sed 's/^/initial number of footprints: /g' >> "$workdir"/compareBed.stats
+	echo $fp_initial | sed 's/^/initial number of footprints: /g' >> "$workdir"/compareBed.log
 else
 	# output will be overwritten if it exists
 	rm -f $output
 	# add initial number of footprints to the log file
-	cat $data | wc -l | sed 's/^/initial number of footprints: /g' >> "$workdir"/compareBed.stats
+	cat $data | wc -l | sed 's/^/initial number of footprints: /g' >> "$workdir"/compareBed.log
 fi
 # add number of footprints after filtering to the log file
-cat "$workdir"/filtered_flagged.bed | wc -l | sed 's/^/number of footprints after subtract: /g' >> "$workdir"/compareBed.stats
+cat "$workdir"/filtered_flagged.bed | wc -l | sed 's/^/number of footprints after subtract: /g' >> "$workdir"/compareBed.log
 
 # add fasta sequences to bed and create fasta file
 out_fasta=`echo $output | sed "s|.bed$|.fasta|g"`
diff --git a/bin/2.2_motif_estimation/get_motif_seq.R b/bin/2.2_motif_estimation/get_motif_seq_id.R
similarity index 94%
rename from bin/2.2_motif_estimation/get_motif_seq.R
rename to bin/2.2_motif_estimation/get_motif_seq_id.R
index bbcaff6..ca07eb6 100644
--- a/bin/2.2_motif_estimation/get_motif_seq.R
+++ b/bin/2.2_motif_estimation/get_motif_seq_id.R
@@ -68,7 +68,7 @@ create_seq_json <- function(input, output, num, tmp_path, cluster_id) {
 
   # Create json file
   ## naming
-  names(datalist) <- paste0(c("Motif_", "Motif_", "Motif_"),seq(1,as.numeric(num),1) , " Cluster_", cluster_id)
+  names(datalist) <- paste0("Motif_", seq(1,as.numeric(num),1), " Cluster_", cluster_id)
   ## creating json object
   json <- RJSONIO::toJSON(datalist, pretty = T , .withNames = T)
   ## writing file
diff --git a/bin/2.2_motif_estimation/merge_similar_clusters.R b/bin/2.2_motif_estimation/merge_similar_clusters.R
index d9b2373..4cf8c47 100644
--- a/bin/2.2_motif_estimation/merge_similar_clusters.R
+++ b/bin/2.2_motif_estimation/merge_similar_clusters.R
@@ -1,5 +1,6 @@
 #!/usr/bin/env Rscript
 if (!require(optparse)) install.packages("optparse"); library(optparse)
+if (!require(igraph)) install.packages("igraph"); library(igraph)
 
 option_list <- list(
   make_option(opt_str = c("-i", "--input"), default = NULL, help = "Input TSV-file. Output from merged tomtom results", metavar = "character"),
@@ -40,37 +41,39 @@ merge_similar <- function(tsv_in, file_list, min_weight){
 
   # remove rows if column 1 is identical to column 2
   edgelist <- sim_not_unique[query_cluster != target_cluster]
-
+  unique_edgelist <- unique(edgelist)
+  
   # 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)
+  g <- graph_from_edgelist(as.matrix(unique(edgelist)), directed = F)
+  g_tidy <- delete.vertices(simplify(g), degree(g) == 0)
+  g_tidy <- set_vertex_attr(g_tidy,"name",V(g_tidy), value = (sort(unique(c(unique_edgelist$V1,unique_edgelist$V2)))) - 1)
 
-  # get subgraphs from graph with edges of weight > min_weight
-  s1 <- igraph::subgraph.edges(g_adj, igraph::E(g_adj)[igraph::E(g_adj)$weight > min_weight], del = F)
+  # plotting
   png('motif_clusters.png')
-  plot(s1)
+  plot(g_tidy)
   dev.off()
-  clust <- igraph::clusters(s1)
+  clust <- clusters(g)
   if (clust$no < 1) {
     b <- lapply(files, function(f){
       system(paste("cat",f,">",basename(f)))
     })
   }
+  clust_out <- file("cluster.txt")
   # merge FASTA-files depending on the clustered graphs
-  a <- lapply(seq(from = 1, to = clust$no, by = 1), function(i){
+  a <- vapply(seq(from = 1, to = clust$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")
+    name <- paste0("Cluster_",i - 1 ,".fasta")
     #merge fasta files
     system(paste("cat",fasta_list,">",name))
-  })
+    paste("Cluster",i - 1,"is generated by merging cluster:",paste(cl - 1,collapse = ","))
+  }, "")
+  writeLines(a[a != ""], con = clust_out)
 }
+  
 
 
 # run function merge_similar with given parameteres if not in interactive context (e.g. run from shell)
diff --git a/bin/2.2_motif_estimation/png_to_pdf.R b/bin/2.2_motif_estimation/png_to_pdf.R
new file mode 100644
index 0000000..7c86920
--- /dev/null
+++ b/bin/2.2_motif_estimation/png_to_pdf.R
@@ -0,0 +1,94 @@
+#!/usr/bin/env Rscript
+if (!require(optparse)) install.packages("optparse"); library(optparse)
+if (!require(png)) install.packages("png"); library(png)
+if (!require(grid)) install.packages("grid"); library(grid)
+if (!require(gridExtra)) install.packages("gridExtra"); library(gridExtra)
+
+
+option_list <- list(
+  make_option(opt_str = c("-i", "--png_new"), default = NULL, help = "List of png paths separated by \',\'", metavar = "character"),
+  make_option(opt_str = c("-p", "--png_old"), default = NULL, help = "List of png paths separated by \',\'", metavar = "character"),
+  make_option(opt_str = c("-f", "--index"), default = NULL, help = "Path to index file", metavar = "character")
+)
+
+opt_parser <- OptionParser(option_list = option_list,
+                           description = "Generating a PDF from multiple png files",
+                           epilogue = "Author: Rene Wiegandt <Rene.Wiegandt@mpi-bn.mpg.de>")
+
+opt <- parse_args(opt_parser)
+
+
+
+#' Generating a PDF from multiple png files.
+#'
+#' @parameter png_new <string> List of png paths separated by ,
+#' @parameter png_old <string> List of png paths separated by ,
+#' @parameter cluster_ids <string> List of IDs separated by ,
+#' @parameter new_id <int> New Cluster ID
+#'
+#' @author Rene Wiegandt
+#' @contact rene.wiegandt(at)mpi-bn.mpg.de
+png_to_pdf <- function(png_top, png_list, cluster_ids, new_id, out = "cluster.pdf"){
+  #png_top <- "G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/03_motif_cluster/04_glam2/Cluster_0/logo1.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/03_motif_cluster/04_glam2/Cluster_0/logo2.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/03_motif_cluster/04_glam2/Cluster_0/logo3.png"
+  #png_list <- "G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/02_glam2/buenrostro50k_chr1_fp_cluster_0/logo1.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/02_glam2/buenrostro50k_chr1_fp_cluster_0/logo2.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/02_glam2/buenrostro50k_chr1_fp_cluster_0/logo3.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/02_glam2/buenrostro50k_chr1_fp_cluster_1/logo1.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/02_glam2/buenrostro50k_chr1_fp_cluster_1/logo2.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/02_glam2/buenrostro50k_chr1_fp_cluster_1/logo3.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/02_glam2/buenrostro50k_chr1_fp_cluster_0/logo1.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/02_glam2/buenrostro50k_chr1_fp_cluster_0/logo2.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/02_glam2/buenrostro50k_chr1_fp_cluster_0/logo3.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/02_glam2/buenrostro50k_chr1_fp_cluster_1/logo1.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/02_glam2/buenrostro50k_chr1_fp_cluster_1/logo2.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/02_glam2/buenrostro50k_chr1_fp_cluster_1/logo3.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/02_glam2/buenrostro50k_chr1_fp_cluster_0/logo1.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/02_glam2/buenrostro50k_chr1_fp_cluster_0/logo2.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/02_glam2/buenrostro50k_chr1_fp_cluster_0/logo3.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/02_glam2/buenrostro50k_chr1_fp_cluster_1/logo1.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/02_glam2/buenrostro50k_chr1_fp_cluster_1/logo2.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/02_glam2/buenrostro50k_chr1_fp_cluster_1/logo3.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/02_glam2/buenrostro50k_chr1_fp_cluster_0/logo1.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/02_glam2/buenrostro50k_chr1_fp_cluster_0/logo2.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/02_glam2/buenrostro50k_chr1_fp_cluster_0/logo3.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/02_glam2/buenrostro50k_chr1_fp_cluster_1/logo1.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/02_glam2/buenrostro50k_chr1_fp_cluster_1/logo2.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/02_glam2/buenrostro50k_chr1_fp_cluster_1/logo3.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/02_glam2/buenrostro50k_chr1_fp_cluster_0/logo1.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/02_glam2/buenrostro50k_chr1_fp_cluster_0/logo2.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/02_glam2/buenrostro50k_chr1_fp_cluster_0/logo3.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/02_glam2/buenrostro50k_chr1_fp_cluster_1/logo1.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/02_glam2/buenrostro50k_chr1_fp_cluster_1/logo2.png,G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/02_glam2/buenrostro50k_chr1_fp_cluster_1/logo3.png"
+  #cluster_ids <- c(1,2,3,4,5,6,7,8,9,10)
+  top_split <- unlist(strsplit(png_top, ","))
+  png_split <- unlist(strsplit(png_list, ","))
+  cluster_list <- unlist(strsplit(cluster_ids, ","))
+  top_grob <- lapply(top_split,function(p){rasterGrob(readPNG(p),interpolate = FALSE)})
+  grobs <- lapply(png_split,function(p){rasterGrob(readPNG(p),interpolate = FALSE)})
+
+  split_grobs <- split(grobs, rep(1:ceiling(length(grobs)/3), each = 3)[1:length(grobs)])
+  
+  rows <- lapply(seq(1,length(split_grobs)), function(sg){
+    arrangeGrob(grobs = split_grobs[[sg]], top = textGrob(paste0("Cluster ",cluster_list[sg]),gp = gpar(fontsize = 20,font = 3)), ncol = 3)
+  })
+  split_rows <- split(rows, rep(1:ceiling(length(rows)/4), each = 4)[1:length(rows)])
+  
+  pdf(out,width = 17, height = 11)
+  grid.arrange(grobs = top_grob, nrow = 3, top = textGrob(paste0("New Cluster ",new_id),gp = gpar(fontsize = 30,font = 3)))
+  lapply(split_rows, function(r){
+    grid.arrange(grobs = r, nrow = 4, top = textGrob("Generated from...",gp = gpar(fontsize = 30,font = 3))) 
+  })
+
+  dev.off()
+
+}
+#### index_file <- "G://Rene.Wiegandt/10_Master/tmp/test_pipeline_11_3_19/2.2_motif_estimation/03_motif_cluster/03_merged_fasta/cluster.txt"
+
+
+#' Parsing index file.
+#'
+#' @parameter index_file Path to index file.
+#'
+#' @author Rene Wiegandt
+#' @contact rene.wiegandt(at)mpi-bn.mpg.de
+get_index <- function(index_file){
+  f <- data.table::fread(index_file, header = F)
+  index <- f[,c(2,8)]
+  index$V8 <- strsplit(index$V8,",")
+  return(index[unlist(lapply(index$V8, function(v){ifelse(length(v) > 1, TRUE, FALSE)}))])
+  
+}
+
+
+png_to_pdf_set_up <- function(png_top, png_list, index_file){
+  
+  index <- get_index(index_file)
+  t <- lapply(seq(nrow(index)), function(i){
+    new_id <- index[i,1]
+    cluster_ids <- index[i,2]
+    out <- paste0("Summary_cluster_", new_id, ".pdf")
+    png_to_pdf(png_top = ,png_list = ,cluster_ids = cluster_ids, new_id = new_id, out = out )
+  })
+  
+}
+
+
+# run function merge_similar with given parameteres if not in interactive context (e.g. run from shell)
+if (!interactive()) {
+  png_to_pdf_set_up(opt$png_new, opt$png_old , opt$index)
+}
+
+
+
diff --git a/bin/3.2_evaluation/venn.R b/bin/3.2_evaluation/venn.R
new file mode 100644
index 0000000..94d8cd2
--- /dev/null
+++ b/bin/3.2_evaluation/venn.R
@@ -0,0 +1,87 @@
+#!/usr/bin/env Rscript
+
+### master JLU 2018 Modul 3.2 Motif Evaluation ###
+# author: afust
+# capabilities:
+# ratio: sequenced used to create motif vs sites found by rescan
+
+# dependencies
+suppressMessages(library(data.table, quietly = TRUE))
+suppressMessages(library(VennDiagram, quietly = TRUE))
+suppressMessages(library(RJSONIO, quietly = TRUE))
+suppressMessages(library(getopt, quietly = TRUE))
+
+# ---------------------------- options ----------------------------------------- #
+# 0 flag
+# 1 mandatory parameter
+# 2 optional parameter
+options(warn = 1)
+options <- matrix(c(
+# tfbs is either the directory including all accessible regions
+# or the directory including precalculated score matrices etc
+"cluster_dir", "i", 1, "character", "directory with rescan results",
+"pattern", "p", 1, "character", "cluster pattern, e.g. 'Cluster_96'",
+"seq_dir", "l", 1, "character", "directory with fp assignment per cluster",
+"clustered_fp", "c", 1, "character", "clustering results",
+"outdir", "o", 1, "character", "output directory",
+"help", "h", 0, "logical", "Provides command line help"
+), byrow = TRUE, ncol = 5)
+opt <- getopt(options)
+
+# ---------------------------- options processing ----------------------------- #
+# check for mandatory parameters and print help if required
+if (!is.null(opt$help) ){
+	cat(getopt(options, usage = TRUE), file = stderr()); q(status = 0)
+}
+
+# load input
+
+# list used files: due to rescan script there is one output per motif for each cluster
+# all should be used in one plot result -> list files with pattern
+rescan_files <- list.files(opt$cluster_dir, pattern = opt$pattern, ignore.case = FALSE)
+# list of fps representing a motif
+fp_list <- fromJSON(opt$seq_dir)
+
+# clustering information needed to extract genomic locations of fps
+# -> reduce to current cluster
+dt.clustering <- fread(opt$clustered_fp, sep="\t", header = TRUE)
+colnames(dt.clustering) <- sub("#chr", "chr", colnames(dt.clustering))
+cl <- as.numeric(strsplit(opt$pattern, "_")[[1]][2])
+dt.clustering <- dt.clustering[dt.clustering$cluster == cl, ]
+
+# pdf including venn diagrams for all motifs
+pdf(paper="a4", file=file.path(opt$outdir, paste0("Cluster_",cl,".pdf")), useDingbats = FALSE)
+plot.new()
+for(f in rescan_files){
+	# load genomic locations found by rescan with motif
+	dt.rescan <- fread(file.path(opt$cluster_dir,f), sep="\t", header = FALSE, select = c(1:4), stringsAsFactors=FALSE)
+	colnames(dt.rescan) <- c("chr", "start", "end", "name")
+
+	# extract fps that build up current motif
+	tmp <- strsplit(as.character(dt.rescan[1,"name"]), "_")[[1]]
+	cluster <- paste(tmp[1],tmp[2],sep="_")
+	id <- paste(paste("Motif", tmp[3], sep="_"), cluster, sep=" ")
+	#cat("\nfor",id, "there are", length(unname(unlist(fp_list[id]))), "sequences assigned")
+	# reduce cluster info to sites used for current motif to find overlaps
+	dt.motif_seq <- dt.clustering[dt.clustering$name %in% unname(unlist(fp_list[id])),c("chr","start", "end")]
+	setkeyv(dt.rescan, c("chr","start","end"))
+	setkeyv(dt.motif_seq, c("chr","start","end"))
+	dt.overlaps <- foverlaps(dt.motif_seq, dt.rescan, mult="first")
+	dt.overlaps <- dt.overlaps[complete.cases(dt.overlaps),]
+	dt.overlaps <- dt.overlaps[!duplicated(dt.overlaps$i.start),]
+	# number of locations found in both: motif setup sequences and rescan
+	hits <- nrow(dt.overlaps)
+	#cat("\nnumbers:\nregions assignet to motif", nrow(dt.motif_seq), "\nregions found by rescan", nrow(dt.rescan), "\noverlaps", hits)
+	# draw venn
+	draw.pairwise.venn(area1 = nrow(dt.motif_seq), area2 = nrow(dt.rescan), cross.area = hits,
+		category = c(paste0("related motif sites of ",cluster), paste0("rescan with ", id)),
+		lty = rep("blank", 2), scaled = TRUE,
+		fill= c("blue", "red"), alpha = c(0.5,0.5),
+		cat.pos = c(0, 0), cat.dist = rep(0.025, 2) )
+	title(id)
+	if(f != tail(rescan_files,1)){
+		grid.newpage()
+	}
+}
+
+invisible(dev.off())
diff --git a/config/cluster.config b/config/cluster.config
index 1ba0b33..9ca8601 100644
--- a/config/cluster.config
+++ b/config/cluster.config
@@ -2,7 +2,7 @@ params{
   //reduce_bed
   kmer=10
   aprox_motif_len=10
-  motif_occurence=1
+  motif_occurrence=1
   min_seq_length=10
 
   //cdhit_wrapper
diff --git a/config/motif_estimation.config b/config/motif_estimation.config
index c829265..e82c4c6 100644
--- a/config/motif_estimation.config
+++ b/config/motif_estimation.config
@@ -1,11 +1,12 @@
 params {
 	//bed_to_clustered_fasta
-	min_seq = 10
+	min_seq = 100
 
 	//glam2
 	motif_min_key = 8
 	motif_max_key = 20
 	iteration = 10000
+	gap_penalty = 1000
 
 	//tomtom
 	tomtom_treshold = 0.01
diff --git a/config/uropa.config b/config/uropa.config
index 3c4a189..0b93f22 100644
--- a/config/uropa.config
+++ b/config/uropa.config
@@ -1,16 +1,8 @@
 {
-"queries":[
-    {"feature":"",
-    "feature.anchor": "",
-    "distance": [ , ],
-    "strand":"",
-    "direction":"",
-    "internals":"",
-    "filter.attribute":"",
-    "attribute.value":"",
-    "show.attributes":"" }
-          ],
-"priority": "",
-"gtf": "placeholder_gtf",
-"bed": "placeholder_bed"
-}
\ No newline at end of file
+	"queries":[
+	{"feature":"gene","distance":[5000,1000], "show.attributes":"gene_id"},
+	{"feature":["ctcf_binding_site","enhancer", "open_chromatin", "promoter", "promoter_flanking_region", "tf_binding_site"], "distance":[1000], "internals":"TRUE"}
+	],
+  "gtf": "placeholder_gtf",
+  "bed": "placeholder_bed"
+}
diff --git a/masterenv.yml b/masterenv.yml
index dc19c1a..8f2ad34 100644
--- a/masterenv.yml
+++ b/masterenv.yml
@@ -24,3 +24,4 @@ dependencies:
   - seaborn
   - crossmap
   - r-bit64
+  - uropa
diff --git a/meme_suite.yml b/meme_suite.yml
new file mode 100644
index 0000000..2ac242e
--- /dev/null
+++ b/meme_suite.yml
@@ -0,0 +1,5 @@
+
+name: meme_suite
+dependencies:
+  - python=2.7
+  - meme
diff --git a/nextflow.config b/nextflow.config
index 653afd6..c935ad0 100644
--- a/nextflow.config
+++ b/nextflow.config
@@ -1,11 +1,11 @@
-wd = ""
+wd = "/mnt/agnerds/Rene.Wiegandt/repo2/masterJLU2018"
 createTimeout = 40
-params.threads=60 //Parameter for for scripts! Not for nextflow processes.
-params.config="${wd}/config/uropa.config"
+params.threads = 10 //Parameter for for scripts! Not for nextflow processes.
+params.config = "${wd}/config/uropa.config"
 
 env {
 	path_bin = "${wd}/bin"
-	path_env = "${wd}/masterenv.yml"
+	meme_env = "${wd}/meme_suite.yml"
 }
 
 includeConfig "${wd}/config/footprint_extraction.config"
diff --git a/pipeline.nf b/pipeline.nf
index 4e3b4fc..afd3399 100644
--- a/pipeline.nf
+++ b/pipeline.nf
@@ -1,5 +1,6 @@
 #!/usr/bin/env nextflow
 
+disable_mo_clu = 1
 
 //setting default values
 	params.bigwig=""
@@ -10,6 +11,7 @@
 	params.tfbs_path=""
 	params.help = 0
 	params.gtf_path=""
+	params.gtf2=""
 	params.out = "./out/"
 
 //footprint_extraction
@@ -24,19 +26,19 @@
 	params.tfbsscan_method = "moods"
 
 //clustering
-  	//reduce_sequence
-  	params.kmer=10
-  	params.aprox_motif_len=10
-  	params.motif_occurence=1
-  	params.min_seq_length=10
-
-  	//cdhit_wrapper
-  	params.global=0
-  	params.identity=0.8
-  	params.sequence_coverage=8
-  	params.memory=800
- 	params.throw_away_seq=9
-  	params.strand=0
+  //reduce_sequence
+	params.kmer=10
+	params.aprox_motif_len=10
+	params.motif_occurrence=1
+	params.min_seq_length=10
+
+	//cdhit_wrapper
+	params.global=0
+	params.identity=0.8
+	params.sequence_coverage=8
+	params.memory=800
+	params.throw_away_seq=9
+	params.strand=0
 
 //motif_estimation
 	//bed_to_clustered_fasta
@@ -47,6 +49,7 @@
 	params.motif_max_key = 20 // Maximum number of key positions (aligned columns)
 	params.iteration = 10000 // Number of Iterations done by glam2. A high iteration number equals a more accurate result but with an higher runtime.
 	params.gap_penalty = 1000
+	params.seed = 123456789
 
 	//tomtom
 	params.tomtom_treshold = 0.01 // threshold for similarity score.
@@ -62,94 +65,103 @@
 	params.organism=""
 	params.tissues=""
 
-if (params.bigwig == "" || params.bed == "" || params.organism == "" || params.genome_fasta == "" || params.motif_db == "" || params.config == "" || "${params.help}" != "0" ){
-log.info """
-Usage: nextflow run pipeline.nf --bigwig [BigWig-file] --bed [BED-file] --genome_fasta [FASTA-file] --motif_db [MEME-file] --config [UROPA-config-file]
-
-Required arguments:
-	--bigwig		 Path to BigWig-file
-	--bed			 Path to BED-file
-	--genome_fasta		 Path to genome in FASTA-format
-	--motif_db		 Path to motif-database in MEME-format
-	--config		 Path to UROPA configuration file
- 	--organism 		 Input organism [hg38 | hg19 | mm9 | mm10]
-	--out			 Output Directory (Default: './out/')
-
-Optional arguments:
-
-	--help [0|1]		1 to show this help message. (Default: 0)
-	--gtf_path		Path to gtf-file. If path is set the process which creates a gtf-file is skipped.
-	--tfbs_path 		Path to directory with output from tfbsscan. If given tfbsscan will be skipped.
-
-	Footprint extraction:
-	--window_length INT	This parameter sets the length of a sliding window. (Default: 200)
-	--step INT		This parameter sets the number of positions to slide the window forward. (Default: 100)
-	--percentage INT	Threshold in percent (Default: 0)
-	--min_gap INT		If footprints are less than X bases apart the footprints will be merged (Default: 6)
-
-	Filter motifs:
-	--min_size_fp INT	Minimum sequence length threshold. Smaller sequences are discarded. (Default: 10)
-	--max_size_fp INT	Maximum sequence length threshold. Discards all sequences longer than this value. (Default: 200)
-	--tfbsscan_method [moods|fimo] Method used by tfbsscan. (Default: moods)
-
-	Cluster:
-	Sequence preparation/ reduction:
-	--kmer INT		K-mer length (Default: 10)
-	--aprox_motif_len INT	Motif length (Default: 10)
-	--motif_occurence FLOAT	Percentage of motifs over all sequences. Use 1 (Default) to assume every sequence contains a motif.
-	--min_seq_length Interations	Remove all sequences below this value. (Default: 10)
-	Clustering:
-	--global INT		Global (=1) or local (=0) alignment. (Default: 0)
-	--identity FLOAT	Identity threshold. (Default: 0.8)
-	--sequence_coverage INT	Minimum aligned nucleotides on both sequences. (Default: 8)
-	--memory INT		Memory limit in MB. 0 for unlimited. (Default: 800)
-	--throw_away_seq INT	Remove all sequences equal or below this length before clustering. (Default: 9)
-	--strand INT		Align +/+ & +/- (= 1). Or align only +/+ (= 0). (Default: 0)
-
-	Motif estimation:
-	--min_seq INT 		Sets the minimum number of sequences required for the FASTA-files given to GLAM2. (Default: 100)
-	--motif_min_key INT	Minimum number of key positions (aligned columns) in the alignment done by GLAM2. (Default: 8)
-	--motif_max_key INT	Maximum number of key positions (aligned columns) in the alignment done by GLAM2. (Default: 20)
-	--iteration INT		Number of iterations done by GLAM2. More Iterations: better results, higher runtime. (Default: 10000)
-	--tomtom_treshold FLOAT	Threshold for similarity score. (Default: 0.01)
-	--best_motif INT	Get the best X motifs per cluster. (Default: 3)
-	--gap_penalty INT	Set penalty for gaps in GLAM2 (Default: 1000)
-	Moitf clustering:
-	--cluster_motif	Boolean	If 1 pipeline clusters motifs. If its 0 it does not. (Defaul: 0)
-	--edge_weight INT	Minimum weight of edges in motif-cluster-graph (Default: 5)
-	--motif_similarity_thresh FLOAT	Threshold for motif similarity score (Default: 0.00001)
-
-	Creating GTF:
-	--tissues List/String 	List of one or more keywords for tissue-/category-activity, categories must be specified as in JSON
-				config
-All arguments can be set in the configuration files
- ```
-"""
-System.exit(2)
+//evaluation
+	params.max_uropa_runs = 10
+
+if (params.bigwig == "" || params.bed == "" || params.organism == "" || params.genome_fasta == "" || params.motif_db == "" || params.config == "" || params.gtf2 == "" || "${params.help}" != "0" ) {
+	log.info """
+	Usage: nextflow run pipeline.nf --bigwig [BigWig-file] --bed [BED-file] --genome_fasta [FASTA-file] --motif_db [MEME-file] --config [UROPA-config-file]
+
+	Required arguments:
+		--bigwig		 Path to BigWig-file
+		--bed			 Path to BED-file
+		--genome_fasta		 Path to genome in FASTA-format
+		--motif_db		 Path to motif-database in MEME-format
+		--config		 Path to UROPA configuration file
+	 	--organism 		 Input organism [hg38 | hg19 | mm9 | mm10]
+		--out			 Output Directory (Default: './out/')
+
+	Optional arguments:
+
+		--help [0|1]		1 to show this help message. (Default: 0)
+		--gtf_path		Path to gtf-file. If path is set the process which creates a gtf-file is skipped.
+		--tfbs_path 		Path to directory with tfbsscan output. If given tfbsscan will be skipped.
+
+		Footprint extraction:
+		--window_length INT	This parameter sets the length of a sliding window. (Default: 200)
+		--step INT		This parameter sets the number of positions to slide the window forward. (Default: 100)
+		--percentage INT	Threshold in percent (Default: 0)
+		--min_gap INT		If footprints are less than X bases apart the footprints will be merged (Default: 6)
+
+		Filter motifs:
+		--min_size_fp INT	Minimum sequence length threshold. Smaller sequences are discarded. (Default: 10)
+		--max_size_fp INT	Maximum sequence length threshold. Discards all sequences longer than this value. (Default: 200)
+		--tfbsscan_method [moods|fimo] Method used by tfbsscan. (Default: moods)
+
+		Cluster:
+		Sequence preparation/ reduction:
+		--kmer INT		K-mer length (Default: 10)
+		--aprox_motif_len INT	Motif length (Default: 10)
+		--motif_occurrence FLOAT	Percentage of motifs over all sequences. Use 1 (Default) to assume every sequence contains a motif.
+		--min_seq_length Interations	Remove all sequences below this value. (Default: 10)
+		Clustering:
+		--global INT		Global (=1) or local (=0) alignment. (Default: 0)
+		--identity FLOAT	Identity threshold. (Default: 0.8)
+		--sequence_coverage INT	Minimum aligned nucleotides on both sequences. (Default: 8)
+		--memory INT		Memory limit in MB. 0 for unlimited. (Default: 800)
+		--throw_away_seq INT	Remove all sequences equal or below this length before clustering. (Default: 9)
+		--strand INT		Align +/+ & +/- (= 1). Or align only +/+ (= 0). (Default: 0)
+
+		Motif estimation:
+		--min_seq INT 		Sets the minimum number of sequences required for the FASTA-files given to GLAM2. (Default: 100)
+		--motif_min_key INT	Minimum number of key positions (aligned columns) in the alignment done by GLAM2. (Default: 8)
+		--motif_max_key INT	Maximum number of key positions (aligned columns) in the alignment done by GLAM2. (Default: 20)
+		--iteration INT		Number of iterations done by GLAM2. More Iterations: better results, higher runtime. (Default: 10000)
+		--tomtom_treshold FLOAT	Threshold for similarity score. (Default: 0.01)
+		--best_motif INT	Get the best X motifs per cluster. (Default: 3)
+		--gap_penalty INT	Set penalty for gaps in GLAM2 (Default: 1000)
+		--seed Set seed for GLAM2 (Default: 123456789)
+		Moitf clustering:
+		--cluster_motif	Boolean	If 1 pipeline clusters motifs. If its 0 it does not. (Defaul: 0)
+		--edge_weight INT	Minimum weight of edges in motif-cluster-graph (Default: 5)
+		--motif_similarity_thresh FLOAT	Threshold for motif similarity score (Default: 0.00001)
+
+		Creating GTF:
+		--tissues List/String 	List of one or more keywords for tissue-/category-activity, categories must be specified as in JSON
+					config
+		Evaluation:
+		--max_uropa_runs INT	 Maximum number UROPA runs running parallelized (Default: 10)
+	All arguments can be set in the configuration files
+	 ```
+	"""
+	System.exit(2)
 } else {
 	Channel.fromPath(params.bigwig).map {it -> [it.simpleName, it]}.set {bigwig_input}
-	Channel.fromPath(params.bed).into {bed_input; bed_for_tfbsscan}
+	Channel.fromPath(params.bed).into {bed_input; bed_for_tfbsscan; bed_for_rescan}
 	Channel.fromPath(params.genome_fasta).into {fa_overlap; fa_scan; fa_overlap_2}
 	Channel.fromPath(params.motif_db).into {db_for_motivscan; db_for_tomtom}
 	Channel.fromPath(params.config).set {config}
+	Channel.fromPath(params.gtf2).set {gtf_to_merge}
 	if (params.tfbs_path != ""){
 		known_tfbs = file(params.tfbs_path).toAbsolutePath()
 	}
 }
 
+
+
 /*
 Checking for parameter input!
 */
 int_params = ["window_length", "step", "min_size_fp", "max_size_fp", "kmer",
-             "aprox_motif_len", "motif_occurence", "min_seq_length", "global",
+             "aprox_motif_len", "motif_occurrence", "min_seq_length", "global",
              "sequence_coverage", "memory", "throw_away_seq", "strand",
              "min_seq", "motif_min_key", "motif_max_key", "iteration",
              "edge_weight", "best_motif", "min_gap", "gap_penalty", "edge_weight",
-						 "threads", ]
+						 "threads", "max_uropa_runs"]
 req_params = ["bigwig", "bed", "genome_fasta", "motif_db", "config"]
 all_params = int_params + req_params + ["organism" , "identity", "tfbsscan_method",
 							"percentage", "tomtom_treshold", "motif_similarity_thresh", "out",
-							"tissues", "gtf_path", "cluster_motif", "tfbs_path", "help"]
+							"tissues", "gtf_path", "cluster_motif", "tfbs_path", "help", "gtf2", "seed"]
 
 valid_organism = ["hg38", "hg19", "mm9", "mm10"]
 valid_tfbsscan_methods = ["moods","fimo"]
@@ -212,7 +224,7 @@ process footprint_extraction {
 
 	tag{name}
 	publishDir "${params.out}/1.1_footprint_extraction/", mode: 'copy', pattern: '*.bed'
-	publishDir "${params.out}/1.1_footprint_extraction/log", mode: 'copy', pattern: '*.log'
+	publishDir "${params.out}/log", mode: 'copy', pattern: '*.log'
 
 	input:
 	set name, file (bigWig), file (bed) from footprint_in
@@ -235,7 +247,8 @@ Find postitions of known tfbs with tfbsscan and discard the overlaps with compar
 */
 process overlap_with_known_TFBS {
 	//conda "${path_env}"
-	publishDir "${params.out}/1.2_filter_motifs", mode :'copy'
+	publishDir "${params.out}/1.2_filter_motifs", mode :'copy', pattern: '*_unknown.bed'
+	publishDir "${params.out}/log", mode: 'copy', pattern: '*.log'
 	tag{name}
 	errorStrategy 'finish'
 
@@ -245,7 +258,7 @@ process overlap_with_known_TFBS {
 	output:
 	set name, file ("${name}_unknown.bed") into bed_for_reducing
 	file ('./known_tfbs/*.bed') optional true
-	file ('*.stats')
+	file ('*.log')
 
 	script:
 	if(params.tfbs_path == ""){
@@ -280,7 +293,7 @@ process reduce_sequence {
 	tag{name}
 
 	publishDir "${params.out}/2.1_clustering/reduced_bed/", mode: 'copy', pattern: '*.bed'
-	publishDir "${params.out}/2.1_clustering/log", mode: 'copy', pattern: '*.log'
+	publishDir "${params.out}/log", mode: 'copy', pattern: '*.log'
 
 	input:
 	set name, file (bed) from bed_for_reducing
@@ -291,7 +304,7 @@ process reduce_sequence {
 
 	script:
 	"""
-	Rscript ${path_bin}/2.1_clustering/reduce_sequence.R -i ${bed} -k ${params.kmer} -m ${params.aprox_motif_len} -o ${name}_reduced.bed -t ${params.threads} -f ${params.motif_occurence} -s ${params.min_seq_length} --summary reduce_sequence.log
+	Rscript ${path_bin}/2.1_clustering/reduce_sequence.R -i ${bed} -k ${params.kmer} -m ${params.aprox_motif_len} -o ${name}_reduced.bed -t ${params.threads} -f ${params.motif_occurrence} -s ${params.min_seq_length} --summary reduce_sequence.log
 	"""
 }
 
@@ -303,13 +316,14 @@ process clustering {
 	//conda "${path_env}"
 
 	publishDir "${params.out}/2.1_clustering/", mode: 'copy', pattern: '*.bed'
-	publishDir "${params.out}/2.1_clustering/log", mode: 'copy', pattern: '*.log'
+	publishDir "${params.out}/log", mode: 'copy', pattern: '*.log'
 
 	input:
 	set name, file (bed) from bed_for_clustering
 
 	output:
 	set name, file ('*.bed') into bed_for_motif_esitmation
+	file ('*.bed') into bed_for_venn
 	file ('*.log')
 
 	script:
@@ -325,21 +339,21 @@ Converting BED-File to one FASTA-File per cluster
 process bed_to_clustered_fasta {
 
 	//conda "${path_env}"
-	publishDir "${params.out}/2.2_motif_estimation/fasta/", mode: 'copy', pattern: '*.FASTA'
-    tag{name}
+	publishDir "${params.out}/2.2_motif_estimation/01_fasta/", mode: 'copy', pattern: '*.FASTA'
+  tag{name}
 
-    input:
-    set name, file (bed) from bed_for_motif_esitmation
+  input:
+  set name, file (bed) from bed_for_motif_esitmation
 
-    output:
-    file ('*.FASTA') into fasta_for_glam2
-    file ('*.FASTA') into fasta_for_motif_cluster
+  output:
+  file ('*.FASTA') into fasta_for_glam2
+  file ('*.FASTA') into fasta_for_motif_cluster
 	file ('*.log') into log22
 
-    script:
-    """
-    Rscript ${path_bin}/2.2_motif_estimation/bed_to_fasta.R -i ${bed} -p ${name} -m ${params.min_seq}
-    """
+  script:
+  """
+  Rscript ${path_bin}/2.2_motif_estimation/bed_to_fasta.R -i ${bed} -p ${name} -m ${params.min_seq}
+  """
 }
 
 
@@ -354,35 +368,36 @@ Generating Motifs through alignment and scoring best local matches.
 */
 process glam2 {
 
-    tag{name}
-	publishDir "${params.out}/2.2_motif_estimation/glam2/", mode: 'copy'
-	//conda "${path_env}"
+  tag{name}
+	publishDir "${params.out}/2.2_motif_estimation/02_glam2/", mode: 'copy'
+	conda "${meme_env}"
 
-    input:
-    set name, file (fasta) from fasta_for_glam2
+  input:
+  set name, file (fasta) from fasta_for_glam2
 
 	output:
-    file("${name}/*.meme") into meme_to_merge
-	set name, file("${name}/*.meme") into meme_for_tomtom
-	set name, file("${name}/*.meme") into meme_to_search_in_merged
-	set name, file("${name}/*.meme") into meme_for_filter
+  file("${name}/*.meme") into meme_to_merge
+	set name, file("${name}/*.meme") into meme_for_tomtom, meme_to_search_in_merged, meme_for_filter
 	set name, file("${name}/*.txt") into glam_for_seq
+	set name, file("${name}/logo[1-9]*.png") into motif_png
 	file ('*')
 
-    script:
-    """
-    glam2 n ${fasta} -O ./${name}/ -E ${params.gap_penalty} -J ${params.gap_penalty} -a ${params.motif_min_key} -b ${params.motif_max_key} -z 5 -n ${params.iteration}
-    """
+  script:
+  """
+  glam2 n ${fasta} -O ./${name}/ -E ${params.gap_penalty} -J ${params.gap_penalty} -a ${params.motif_min_key} -b ${params.motif_max_key} -z 5 -n ${params.iteration} -s ${params.seed}
+  """
 }
 
+//motif_png.toSortedList()).println()
+
 /*
 Combining all MEME-files to one big MEME-file.
 The paths are sorted numerically depending on the cluster ID.
 */
 process merge_meme {
 
-	publishDir "${params.out}/2.2_motif_estimation/cluster_motifs/merged_meme/", mode: 'copy'
-	//conda "${path_env}"
+	publishDir "${params.out}/2.2_motif_estimation/03_motif_cluster/", mode: 'copy'
+	// conda "/home/rwiegan/.conda/envs/meme"
 
 	input:
 	val (memelist) from meme_to_merge.toList()
@@ -392,6 +407,7 @@ process merge_meme {
 
 	when:
 	params.cluster_motif == 1
+	disable_mo_clu == 0
 
 	script:
 	//sorting
@@ -401,6 +417,7 @@ process merge_meme {
 	//create list for bash
 	meme_list = meme_sorted_full.toString().replaceAll(/\,|\[|\]/,"")
 	"""
+	set +u; source activate meme;
 	meme2meme ${meme_list} > merged_meme.meme
 	"""
 }
@@ -411,11 +428,11 @@ to_find_similar_motifs = meme_to_search_in_merged.combine(merged_meme)
 Running Tomtom on merged meme-files.
 Output table has the information which clusters are similar to each other.
 */
-process find_similar_motifs {
+process compare_cluster {
 
 	tag{name}
-	publishDir "${params.out}/2.2_motif_estimation/cluster_motifs/cluster_similarity/", mode: 'copy'
-	//conda "${path_env}"
+	publishDir "${params.out}/2.2_motif_estimation/03_motif_cluster/01_tomtom/", mode: 'copy'
+	conda "${meme_env}"
 
 	input:
 	set name, file (meme) ,file (merged_meme) from to_find_similar_motifs
@@ -438,7 +455,7 @@ Label first column of TSV-file with Cluster ID
 process label_cluster {
 
 	tag{name}
-	//conda "${path_env}"
+	publishDir "${params.out}/2.2_motif_estimation/03_motif_cluster/02_labeled_tsv/", mode: 'copy'
 
 	input:
 	set name, file (tsv) from motif_similarity
@@ -450,17 +467,19 @@ process label_cluster {
 	params.cluster_motif == 1
 
 	script:
+	id = name.split('_')[-1].toInteger() + 1
 	"""
-	Rscript ${path_bin}/2.2_motif_estimation/label_cluster.R -i ${tsv} -o ${name}_labeled.tsv
+	tail -n +2 ${tsv} | awk -F \$'\t' 'BEGIN {OFS = FS}(\$1=\$1".${id}")' > ${name}_labeled.tsv
 	"""
 }
 
+
 /*
 Merging tsv files_for_merge_fasta
 */
 process merge_labeled_tsv {
 
-	publishDir "${params.out}/2.2_motif_estimation/cluster_motifs/", mode: 'copy'
+	publishDir "${params.out}/2.2_motif_estimation/03_motif_cluster/", mode: 'copy'
 
 	input:
 	val (tsvlist) from labeled_tsv.toSortedList { it.toString().tokenize('_')[-2] as Integer }
@@ -474,7 +493,7 @@ process merge_labeled_tsv {
 	script:
 	tsvs = tsvlist.toString().replaceAll(/\,|\[|\]/,"")
 	"""
-	echo -e 'Query_ID\tTarget_ID\tOptimal_offset\tp-value\tE-value\tq-value\tOverlap\tQuery_consensus\tTarget_consensus\tOrientation'> merged_labeled.tsv
+	echo -e 'Query_ID\tTarget_ID\tOptimal_offset\tp-value\tE-value\tq-value\tOverlap\tQuery_consensus\tTarget_consensus\tOrientation' > merged_labeled.tsv
 	for i in $tsvs; do
 		cat \$i >> merged_labeled.tsv
 	done
@@ -490,23 +509,23 @@ Merging FASTA-files of similar clusters
 process merge_fasta {
 
 	//conda "${path_env}"
-	publishDir "${params.out}/2.2_motif_estimation/cluster_motifs/merged_fasta/", mode: 'copy'
+	publishDir "${params.out}/2.2_motif_estimation/03_motif_cluster/03_merged_fasta/", mode: 'copy'
 
 	input:
 	set file (motiv_sim), val (fasta_list) from files_for_merge_fasta
 
 	output:
 	file ('*.fasta') into motif_clustered_fasta_list
-  	file('*.png')
+  file('*')
 
-  	when:
-  	params.cluster_motif == 1
+  when:
+  params.cluster_motif == 1
 
 	script:
-  	fa_sorted = fasta_list.sort(false) { it.getBaseName().tokenize('_')[-1] as Integer }
-  	fastalist = fa_sorted.toString().replaceAll(/\s|\[|\]/,"")
+  fa_sorted = fasta_list.sort(false) { it.getBaseName().tokenize('_')[-1] as Integer }
+  fastalist = fa_sorted.toString().replaceAll(/\s|\[|\]/,"")
 	"""
-	Rscript ${path_bin}/2.2_motif_estimation/merge_similar_clusters.R ${motiv_sim} ${fastalist} ${params.edge_weight}
+	Rscript ${path_bin}/2.2_motif_estimation/merge_similar_clusters.R -i ${motiv_sim} -l ${fastalist} -w ${params.edge_weight}
 	"""
 }
 
@@ -518,26 +537,25 @@ Run GLAM2 on emrged FASTA-files
 */
 process clustered_glam2 {
 
-	publishDir "${params.out}/2.2_motif_estimation/cluster_motifs/glam2/", mode: 'copy'
+	publishDir "${params.out}/2.2_motif_estimation/03_motif_cluster/04_glam2/", mode: 'copy'
 	tag{name}
-	//conda "${path_env}"
+	conda "${meme_env}"
 
 	input:
 	file (fasta) from motif_clustered_fasta_flat
 
 	output:
-	set name, file ("/${name}/*.meme") into clustered_meme_for_tomtom
-  	set name, file ("/${name}/*.meme") into clustered_meme_for_filter
-	set name, file("/${name}/glam2.txt") into clust_glam_for_seq
-  	file('*')
+	set name, file ("./${name}/glam2.meme") into clustered_meme_for_tomtom, clustered_meme_for_filter
+	set name, file("./${name}/glam2.txt") into clust_glam_for_seq
+  file('*')
 
 	when:
 	params.cluster_motif == 1
 
 	script:
-  	name = fasta.getBaseName()
+  name = fasta.getBaseName()
 	"""
-	glam2 n ${fasta} -O ./${name}/ -E ${params.gap_penalty} -J ${params.gap_penalty} -a ${params.motif_min_key} -b ${params.motif_max_key} -z 5 -n ${params.iteration}
+	glam2 n ${fasta} -O ./${name}/ -E ${params.gap_penalty} -J ${params.gap_penalty} -a ${params.motif_min_key} -b ${params.motif_max_key} -z 5 -n ${params.iteration} -s ${params.seed}
 	"""
 }
 
@@ -562,20 +580,19 @@ Tomtom searches motifs in databases.
 */
 process tomtom {
 
-    tag{name}
-	publishDir "${params.out}/2.2_motif_estimation/tomtom/", mode: 'copy'
-	//conda "${path_env}"
+	tag{name}
+	publishDir "${params.out}/2.2_motif_estimation/04_tomtom/", mode: 'copy'
 
-    input:
-    set name, file (meme) from for_tomtom
+  input:
+  set name, file (meme) from for_tomtom
 
-    output:
-    set name, file ('*.tsv') into tsv_for_filter
+  output:
+  set name, file ('*.tsv') into tsv_for_filter
 
-    script:
-    """
-    tomtom ${meme} ${params.motif_db} -thresh ${params.tomtom_treshold} -mi 1 -text | sed '/^#/ d' | sed '/^\$/d' > ${name}_known_motif.tsv
-    """
+  script:
+  """
+  tomtom ${meme} ${params.motif_db} -thresh ${params.tomtom_treshold} -mi 1 -text | sed '/^#/ d' | sed '/^\$/d' > ${name}_known_motif.tsv
+  """
 }
 
 
@@ -597,7 +614,7 @@ log22.combine(count_cluster).combine(count_cluster_before_filter ).set {log22_fi
 //Writes log file for 2.2_motif_estimation
 process write_log_for_motif_estimation {
 
-	publishDir "${params.out}/2.2_motif_estimation/log/", mode: 'copy'
+	publishDir "${params.out}/log/", mode: 'copy'
 
 	input:
 	set file (logfile), after_filter, before_filter from log22_final
@@ -613,20 +630,20 @@ process write_log_for_motif_estimation {
 	"""
 }
 
+
 //If channel 'check' is empty print errormessage
 process check_for_unknown_motifs {
-    echo true
-
-    input:
-    val x from check.ifEmpty('EMPTY')
+  echo true
 
-    when:
-    x == 'EMPTY'
+  input:
+  val x from check.ifEmpty('EMPTY')
 
-    """
-    echo '>>> STOPPED: No unknown Motifs were found.'
-    """
+  when:
+  x == 'EMPTY'
 
+  """
+  echo '>>> STOPPED: No unknown Motifs were found.'
+  """
 }
 
 
@@ -635,13 +652,13 @@ process get_best_motif {
 
 	//conda "${path_env}"
 	tag{name}
-	publishDir "${params.out}/2.2_motif_estimation/best_unknown_motifs/", mode: 'copy'
+	publishDir "${params.out}/2.2_motif_estimation/05_best_unknown_motifs/motifs/", mode: 'copy'
 
 	input:
 	set name, file(meme), file(tsv) from meme_for_scan
 
 	output:
-	set name, file('*_best.meme') into best_motif
+	set name, file('*_best.meme') into best_motif, best_motif_for_venn
 
 	script:
 	cluster_id = name.split('_')[-1]
@@ -654,56 +671,73 @@ process get_best_motif {
 /*
 Get the sequence names used to create best X Motifs as a JSON-file
 */
-process get_best_motif_seq {
+process get_best_motif_seq_id {
 
 	//conda "${path_env}"
 	tag{name}
-	publishDir "${params.out}/2.2_motif_estimation/best_unknown_motifs/motif_sequences/", mode: 'copy'
+	publishDir "${params.out}/2.2_motif_estimation/05_best_unknown_motifs/motif_sequence_ids/", mode: 'copy'
 
 	input:
 	set name, file (txt) from seq_to_json
 
 	output:
-	file("${name}_seq.json")
+	set name, file("${name}_seq.json") into seq_id_for_venn
 
 	script:
 	cluster_id = name.split('_')[-1]
 	"""
-	Rscript ${path_bin}/2.2_motif_estimation/get_motif_seq.R -i ${txt} -o ${name}_seq.json -n ${params.best_motif} -t ./motif_seq_tmp/cluster_${cluster_id} -c ${cluster_id}
+	Rscript ${path_bin}/2.2_motif_estimation/get_motif_seq_id.R -i ${txt} -o ${name}_seq.json -n ${params.best_motif} -t ./motif_seq_tmp/cluster_${cluster_id} -c ${cluster_id}
 	"""
 }
 
 
-best_motif.combine(fa_scan).set {files_for_genome_scan}
+best_motif.combine(fa_scan).combine(bed_for_rescan).set {files_for_re_scan}
 
 /*
-process genome_scan {
+*/
+process re_scan {
 	//conda "${path_env}"
+	tag{name}
+	publishDir "${params.out}/3.2_evaluation/rescan/${name}", mode: 'copy'
 
 	input:
-	set name, file(meme), file(fasta) from files_for_genome_scan
+	set name, file(meme), file(fasta), file (peaks) from files_for_re_scan
 
 	output:
-	file ('.bed') into bed_for_uropa, bed_for_cluster_quality
+	set name, val ('link') into link_re_scan_to_venn
+	file ("*.bed") into re_scan_for_uropa
 
 	script:
 	"""
+	mkdir -p ./tmp/re_scan/${name}
+	python ${path_bin}/1.2_filter_motifs/tfbsscan.py -m ${meme} -g ${fasta} -b ${peaks} -o . --cores 4 --use moods --resolve_overlaps
+	mkdir -p ${workflow.workDir}/tmp/re_scan_final
+	cp ./Cluster*.bed ${workflow.workDir}/tmp/re_scan_final
 	"""
 }
 
 
-process cluster_quality {
+seq_id_for_venn.combine(link_re_scan_to_venn, by: 0).combine(bed_for_venn).set {for_venn}
+
+/*
+*/
+process venn {
+
+	tag{name}
+	publishDir "${params.out}/3.2_evaluation/venn", mode: 'copy'
 
 	input:
-	file (bed) from bed_for_cluster_quality
+	set name, file(seq_ids), link, file (clustered_bed) from for_venn
 
 	output:
-	file ('*.bed') into bed_for_final_filter
+	file ('*.pdf')
 
 	script:
+	cluster_id = name.split('_')[-1]
 	"""
+	Rscript ${path_bin}/3.2_evaluation/venn.R -i ${workflow.workDir}/tmp/re_scan_final/ -p Cluster_${cluster_id}_ -l ${seq_ids} -c ${clustered_bed} -o .
 	"""
-} */
+}
 
 
 process create_GTF {
@@ -723,60 +757,83 @@ process create_GTF {
 	"""
 }
 
-if (params.gtf_path == "") {
-	gtf_for_uropa = gtf
-} else {
-	gtf_for_uropa = Channel.fromPath(params.gtf_path)
-}
 
-/*
-bed_for_final_filter.combine(gtf_for_uropa).set {uropa_in}
+gtf.combine(gtf_to_merge).set {gtf_list}
 
 
-// Create configuration file for UROPA.
-// Takes template and replaces bed- and gtf-placeholders with actual paths.
-process create_uropa_config {
+process merge_gtf {
 
-	publishDir '/mnt/agnerds/Rene.Wiegandt/10_Master/', mode: 'copy'
+	stageInMode 'copy'
+	publishDir "${params.out}/3.1_create_gtf/", mode: 'copy'
 
 	input:
-	set val(bed), val(gtf) from uropa_in.toList()
-	file (conf) from config
+	set file (gtf_reg), file (gtf_genes) from gtf_list
 
 	output:
-	file ('uropa.config') into uropa_config
+	file ('merged.gtf') into merged_gtf
+
+	when:
+	params.gtf_path == ""
 
 	script:
 	"""
-  	sed -- 's/placeholder_gtf/${gtf}/g; s/placeholder_bed/${bed}/g' ${conf} > uropa.config.final
+	cat ${gtf_genes} > merged.gtf
+	cat ${gtf_reg} >> merged.gtf
 	"""
 }
 
+if (params.gtf_path == "") {
+	gtf_for_uropa = merged_gtf
+} else {
+	gtf_for_uropa = Channel.fromPath(params.gtf_path)
+}
+
+re_scan_for_uropa.flatten().combine(gtf_for_uropa).combine(config).set {uropa_in}
 
-process UROPA {
+// Create configuration file for UROPA.
+// Takes template and replaces bed- and gtf-placeholders with actual paths.
+process create_uropa_config {
+
+	tag{bed}
+	echo true
+	publishDir "${params.out}/3.2_evaluation/uropa/config", mode: 'copy'
 
 	input:
-	file (config) from uropa_config
+	set val(bed), val (gtf), file (conf) from uropa_in
 
 	output:
-	set file ("*_allhits.txt"), file ("*_finalhits.txt") into uropa_for_filter
+	set name, file ("${name}_uropa.config") into uropa_config
 
 	script:
+	name = bed.getBaseName()
 	"""
+  	sed -- 's=placeholder_gtf=${gtf}=g; s=placeholder_bed=${bed}=g' ${conf} > ${name}_uropa.config
 	"""
 }
 
 
-process filter {
+process UROPA {
+
+	tag{config}
+	maxForks params.max_uropa_runs
+	publishDir "${params.out}/3.2_evaluation/uropa", mode: 'copy', pattern: "*.txt"
+	publishDir "${params.out}/3.2_evaluation/uropa/summary", mode: 'copy', pattern: "*.pdf"
+	publishDir "${params.out}/log/uropa/${name}", mode: 'copy', pattern: "*.log"
 
 	input:
+	set name, file (config) from uropa_config
 
 	output:
+	set file ("*_allhits.txt"), file ("*_finalhits.txt") into uropa_for_filter
+	file("*.pdf")
+	file("*.log")
 
 	script:
 	"""
+	uropa -i ${config} -l uropa.log -t 4 -p ${name} -s -d
 	"""
-} */
+}
+
 
 workflow.onComplete {
 log.info"""
@@ -789,4 +846,6 @@ workDir     : ${workflow.workDir}
 exit status : ${workflow.exitStatus}
 Error report: ${workflow.errorReport ?: '-'}
 """
+f = file(workflow.workDir + '/tmp/re_scan_final')
+f.deleteDir()
 }