diff --git a/modules/local/fitness/templates/fitness_calculation.R b/modules/local/fitness/templates/fitness_calculation.R
index 0312ef2..6531414 100644
--- a/modules/local/fitness/templates/fitness_calculation.R
+++ b/modules/local/fitness/templates/fitness_calculation.R
@@ -18,13 +18,13 @@ compute_nt_hamming <- function(merged.counts, wt.seq) {
   merged.counts <- cbind("nt_ham" = rep(NA, nrow(merged.counts)), merged.counts)
   for (i in 1:nrow(merged.counts)){
     tmp.wt <- strsplit(as.character(wt.seq), "")[[1]]
-    tmp.mut <- strsplit(as.character(merged.counts\$nt_seq[i]), "")[[1]]
+    tmp.mut <- strsplit(as.character(merged.counts$nt_seq[i]), "")[[1]]
     if(length(which(tmp.mut != tmp.wt)) == 0){
-      merged.counts\$nt_ham[i] <- 0
+      merged.counts$nt_ham[i] <- 0
       rm(tmp.mut, tmp.wt)
       next
     }else{
-      merged.counts\$nt_ham[i] <- length(which(tmp.mut != tmp.wt))
+      merged.counts$nt_ham[i] <- length(which(tmp.mut != tmp.wt))
       rm(tmp.mut, tmp.wt)
       next
     }
@@ -34,7 +34,7 @@ compute_nt_hamming <- function(merged.counts, wt.seq) {
 
 # translate sequences and add aa_seq
 add_aa_seq <- function(merged.counts) {
-  merged.counts <- cbind("aa_seq" = as.character(translate(DNAStringSet(merged.counts\$nt_seq))), merged.counts)
+  merged.counts <- cbind("aa_seq" = as.character(translate(DNAStringSet(merged.counts$nt_seq))), merged.counts)
   merged.counts
 }
 
@@ -43,13 +43,13 @@ compute_aa_hamming <- function(merged.counts, wt.seq.aa) {
   merged.counts <- cbind("aa_ham" = rep(NA, nrow(merged.counts)), merged.counts)
   for (i in 1:nrow(merged.counts)){
     tmp.wt <- strsplit(as.character(wt.seq.aa), "")[[1]]
-    tmp.mut <- strsplit(as.character(merged.counts\$aa_seq[i]), "")[[1]]
+    tmp.mut <- strsplit(as.character(merged.counts$aa_seq[i]), "")[[1]]
     if(length(which(tmp.mut != tmp.wt)) == 0){
-      merged.counts\$aa_ham[i] <- 0
+      merged.counts$aa_ham[i] <- 0
       rm(tmp.mut, tmp.wt)
       next
     }else{
-      merged.counts\$aa_ham[i] <- length(which(tmp.mut != tmp.wt))
+      merged.counts$aa_ham[i] <- length(which(tmp.mut != tmp.wt))
       rm(tmp.mut, tmp.wt)
       next
     }
@@ -63,14 +63,14 @@ name_mutations <- function(merged.counts, wt.seq.aa) {
                          "pos" = rep(NA, nrow(merged.counts)),
                          "mut aa" = rep(NA, nrow(merged.counts)), merged.counts)
   for (i in 1:nrow(merged.counts)){
-    if(merged.counts\$aa_ham[i] == 0){
+    if(merged.counts$aa_ham[i] == 0){
       next
     }else{
       tmp.wt <- strsplit(as.character(wt.seq.aa), "")[[1]]
-      tmp.mut <- strsplit(as.character(merged.counts\$aa_seq[i]), "")[[1]]
-      merged.counts\$pos[i] <- which(tmp.mut != tmp.wt)
-      merged.counts\$`wt aa`[i] <- tmp.wt[merged.counts\$pos[i]]
-      merged.counts\$`mut aa`[i] <- tmp.mut[merged.counts\$pos[i]]
+      tmp.mut <- strsplit(as.character(merged.counts$aa_seq[i]), "")[[1]]
+      merged.counts$pos[i] <- which(tmp.mut != tmp.wt)
+      merged.counts$`wt aa`[i] <- tmp.wt[merged.counts$pos[i]]
+      merged.counts$`mut aa`[i] <- tmp.mut[merged.counts$pos[i]]
       rm(tmp.mut, tmp.wt)
     }
   }
@@ -83,17 +83,17 @@ aggregate_by_aa <- function(merged.counts) {
   merged.counts <- cbind(merged.counts,
                          "wt" = rep(NA, nrow(merged.counts)),
                          "stop" = rep(NA, nrow(merged.counts)))
-  merged.counts\$wt[which(merged.counts\$nt_ham == 0)] <- TRUE
-  merged.counts\$stop[which(merged.counts\$`mut aa` == "*")] <- TRUE
+  merged.counts$wt[which(merged.counts$nt_ham == 0)] <- TRUE
+  merged.counts$stop[which(merged.counts$`mut aa` == "*")] <- TRUE
   
   ## aggregate counts of variants which are identical on the aa (but not nt) level
   ## exception: wildtype ones
   ## thereby shrinking the matrix
-  uniq.aa.vars <- unique(merged.counts\$aa_seq)
-  uniq.aa.vars <- uniq.aa.vars[-which(uniq.aa.vars == merged.counts\$aa_seq[which(merged.counts\$wt == TRUE)])]
+  uniq.aa.vars <- unique(merged.counts$aa_seq)
+  uniq.aa.vars <- uniq.aa.vars[-which(uniq.aa.vars == merged.counts$aa_seq[which(merged.counts$wt == TRUE)])]
   for(i in 1:length(uniq.aa.vars)){
     tmp.aa_seq <- uniq.aa.vars[i]
-    hits <- which(as.character(merged.counts\$aa_seq) == tmp.aa_seq)
+    hits <- which(as.character(merged.counts$aa_seq) == tmp.aa_seq)
     if(length(hits) == 1){
       rm(tmp.aa_seq, hits)
       next
@@ -129,7 +129,7 @@ density_peaks <- function(x, adjust = 1, ...) {
 # 3. Raw fitness calculations ##
 calc_raw_fitness <- function(merged.counts, exp.design) {
   ## how many fitness replicates are there
-  reps <- length(unique(exp.design\$experiment_replicate))
+  reps <- length(unique(exp.design$experiment_replicate))
   for (i in 1:reps){
     merged.counts <- cbind(merged.counts, rep(NA, nrow(merged.counts)))
     colnames(merged.counts)[ncol(merged.counts)] <- paste0("raw_fitness_rep", i)
@@ -146,8 +146,8 @@ calc_raw_fitness <- function(merged.counts, exp.design) {
     tmp.output.counts[which(tmp.output.counts == 0 & tmp.input.counts != 0)] <- 1
 
     ### take logs
-    tmp.wt.log.ratio <- log(tmp.output.counts[which(merged.counts\$wt == TRUE)] / 
-                              tmp.input.counts[which(merged.counts\$wt == TRUE)])
+    tmp.wt.log.ratio <- log(tmp.output.counts[which(merged.counts$wt == TRUE)] / 
+                              tmp.input.counts[which(merged.counts$wt == TRUE)])
     tmp.fitness <- log(tmp.output.counts / 
                          tmp.input.counts) - tmp.wt.log.ratio
 
@@ -174,8 +174,8 @@ rescale_and_summarize <- function(merged.counts, reps) {
     colnames(merged.counts)[ncol(merged.counts)] <- paste0("rescaled_fitness_rep", i)
 
     ### fetch the key counts
-    tmp.wt.fitness <- merged.counts[which(merged.counts\$aa_ham == 0),ncol(merged.counts) - reps]
-    tmp.stop.fitness <- merged.counts[which(merged.counts\$stop == TRUE),ncol(merged.counts) - reps]
+    tmp.wt.fitness <- merged.counts[which(merged.counts$aa_ham == 0),ncol(merged.counts) - reps]
+    tmp.stop.fitness <- merged.counts[which(merged.counts$stop == TRUE),ncol(merged.counts) - reps]
     
     ### rescale
     tmp.wt.fitness.med <- median(tmp.wt.fitness, na.rm = TRUE)
@@ -221,15 +221,15 @@ rescale_and_summarize <- function(merged.counts, reps) {
 
   if(reps == 1){
     
-    merged.counts\$`mean fitness` <- merged.counts[,ncol(merged.counts) - 2]
+    merged.counts$`mean fitness` <- merged.counts[,ncol(merged.counts) - 2]
     
   }else if(reps > 1){
     
-    merged.counts\$`mean fitness` <- apply(merged.counts[,c(ncol(merged.counts) - 1 - reps):c(ncol(merged.counts) - 2)],
+    merged.counts$`mean fitness` <- apply(merged.counts[,c(ncol(merged.counts) - 1 - reps):c(ncol(merged.counts) - 2)],
                                           1,
                                           mean,
                                           na.rm = TRUE)
-    merged.counts\$`fitness sd` <- apply(merged.counts[,c(ncol(merged.counts) - 1 - reps):c(ncol(merged.counts) - 2)],
+    merged.counts$`fitness sd` <- apply(merged.counts[,c(ncol(merged.counts) - 1 - reps):c(ncol(merged.counts) - 2)],
                                         1,
                                         sd,
                                         na.rm = TRUE)
@@ -256,8 +256,8 @@ run_fitness_estimation <- function(counts_path,
   ## 1. Import key files ##
   #########################
   
-  merged.counts <- read.table(counts_path, sep = "\\t", header = TRUE, check.names = FALSE)
-  exp.design   <- read.table(design_path, sep = "\\t", header = TRUE, check.names = FALSE)
+  merged.counts <- read.table(counts_path, sep = "\t", header = TRUE, check.names = FALSE)
+  exp.design   <- read.table(design_path, sep = "\t", header = TRUE, check.names = FALSE)
   wt.seq       <- DNAString(as.character(read.table(wt_seq_path)))
   wt.seq.aa    <- translate(wt.seq)
 
@@ -282,8 +282,8 @@ run_fitness_estimation <- function(counts_path,
   ## 3. Raw fitness calculations ##
   #################################
   fitness_res <- calc_raw_fitness(merged.counts, exp.design)
-  merged.counts <- fitness_res\$merged.counts
-  reps <- fitness_res\$reps
+  merged.counts <- fitness_res$merged.counts
+  reps <- fitness_res$reps
   
   ## 4. Fitness and error refinements ##
   ######################################
@@ -294,7 +294,7 @@ run_fitness_estimation <- function(counts_path,
 
   ## export
   write.table(merged.counts, output_path,
-              col.names = TRUE, row.names = FALSE, quote = FALSE, sep = "\\t", na = "")
+              col.names = TRUE, row.names = FALSE, quote = FALSE, sep = "\t", na = "")
   
   invisible(merged.counts)
 }