diff --git a/R/filter_calls.R b/R/filter_calls.R
index e1a8ab0..acd4535 100644
--- a/R/filter_calls.R
+++ b/R/filter_calls.R
@@ -63,6 +63,7 @@ filter_calls = function(
           melt.data.table(id.vars = melt.id.vars,variable.name = 'variable',value.name = 'value') %>%
           mutate(variable = gsub('fragment','_',variable)) %>% separate(variable,c('variable','Sample_Type'),sep = '___') %>%
           mutate(Tumor_Sample_Barcode = paste0(sample.name,'___',Sample_Type)) %>% select(-Sample_Type) %>% data.table() %>%
+          unique() %>%
           dcast.data.table(as.formula(paste0(paste0(melt.id.vars,collapse = ' + '),' ~ variable')),value.var = 'value') -> maf.file
       }else{
         maf.file <- maf.file %>% mutate(Tumor_Sample_Barcode = paste0(sample.name,'___',sample.type)) %>%
@@ -73,7 +74,7 @@ filter_calls = function(
         transmute(Hugo_Symbol,Tumor_Sample_Barcode,Chromosome = as.character(Chromosome),Start_Position,End_Position,Variant_Classification,
                   HGVSp_Short,Reference_Allele,Tumor_Seq_Allele2,t_var_freq,ExAC_AF) %>% data.table()
       return(maf.file)
-    }))
+    })) %>% unique() %>% data.table()
     # merging and melting -----------------------------------------------------
     hotspot.maf <- fread(paste0(results.dir,'/',x,'/',x,'_all_unique_calls_hotspots.maf')) %>% rowwise() %>%
       transmute(Hugo_Symbol,Chromosome = as.character(Chromosome),Start_Position,End_Position,Variant_Classification,
@@ -137,16 +138,16 @@ filter_calls = function(
     if(all(!c('unfilterednormal','normal_DMP') %in% sample.sheet$Sample_Type)){
       tmp.col.name <- plasma.samples[1]
       lapply(plasma.samples,function(tmp.col.name){
-        fillouts.dt[as.numeric(gsub("\\(|\\)",'',str_extract(get(tmp.col.name),"\\(.*.\\)"))) >= 0.3 | ExAC_AF >= 0.0001,eval(paste0(tmp.col.name,'.called')) := 'Not Called']
+        #fillouts.dt[as.numeric(gsub("\\(|\\)",'',str_extract(get(tmp.col.name),"\\(.*.\\)"))) >= 0.3 | ExAC_AF >= 0.0001,eval(paste0(tmp.col.name,'.called')) := 'Not Called']
         fillouts.dt[get(tmp.col.name)  == '0/0(NaN)',eval(paste0(tmp.col.name,'.called')) := 'Not Covered']
       })
     }else{
       lapply(plasma.samples,function(tmp.col.name){
         lapply(normal.samples,function(tmp.col.name.normal){
           # duplex tvar/nvar > 5
-          fillouts.dt[(as.numeric(gsub("\\(|\\)",'',str_extract(get(tmp.col.name),"\\(.*.\\)")))/as.numeric(gsub("\\(|\\)",'',str_extract(get(tmp.col.name.normal),"\\(.*.\\)"))) < 5) |
+          fillouts.dt[(as.numeric(gsub("\\(|\\)",'',str_extract(get(tmp.col.name),"\\(.*.\\)")))/as.numeric(gsub("\\(|\\)",'',str_extract(get(tmp.col.name.normal),"\\(.*.\\)"))) < 2) |
                         # if duplex have no reads, use simplex tvar
-                        (as.numeric(gsub("\\(|\\)",'',str_extract(get(gsub('duplex','simplex',tmp.col.name)),"\\(.*.\\)")))/as.numeric(gsub("\\(|\\)",'',str_extract(get(tmp.col.name.normal),"\\(.*.\\)"))) < 5 &
+                        (as.numeric(gsub("\\(|\\)",'',str_extract(get(gsub('duplex','simplex',tmp.col.name)),"\\(.*.\\)")))/as.numeric(gsub("\\(|\\)",'',str_extract(get(tmp.col.name.normal),"\\(.*.\\)"))) < 2 &
                            as.numeric(gsub("/.*.$",'',get(tmp.col.name)))  == 0),
                       eval(paste0(tmp.col.name,'.called')) := 'Not Called']
           fillouts.dt[get(tmp.col.name)  == '0/0(NaN)',eval(paste0(tmp.col.name,'.called')) := 'Not Covered']
@@ -156,7 +157,10 @@ filter_calls = function(
     
     # final processing --------------------------------------------------------
     # Save only the useful column
-    fillouts.dt <-  fillouts.dt[DMP == 'Signed out' | fillouts.dt[,apply(.SD,1,function(x){any(x == 'Called')})]]  
+    #print(fillouts.dt)
+    #print("#######")
+    fillouts.dt <-  fillouts.dt[DMP == 'Signed out' | fillouts.dt[,apply(.SD,1,function(x){any(x == 'Called')})]] 
+    #print(fillouts.dt)
     # combining duplex and simplex counts
     lapply(plasma.samples,function(tmp.col.name){
       # hotspot reads
diff --git a/R/plot_all_events.R b/R/plot_all_events.R
index 759fe3c..7ecedcc 100644
--- a/R/plot_all_events.R
+++ b/R/plot_all_events.R
@@ -10,216 +10,261 @@
 # helper methods ----------------------------------------------------------
 
 # collapsing read counts from the same rearrangement events into one total count
-collapse_AF = function(x){
+collapse_AF <- function(x) {
   # x = c("32-117-190(0.7842)|53-0-959(0.0553)","NA|16-0-1035(0.0155)","63-0-954(0.066)|NA" )
   # x = c('3-5-1300')
   # x = c('NA|NA|NA|0-56-4183','NA|NA|NA|3-4-76')
-  print(paste0(x,collapse = "','"))
+  print(paste0(x, collapse = "','"))
   # number of samples
-  samples.num = attr(gregexpr('\\|',x[1])[[1]],"match.length")
+  samples.num <- attr(gregexpr("\\|", x[1])[[1]], "match.length")
   print(samples.num)
   # when not found, return -1
-  if(samples.num != -1){
-    paste0(round(apply(separate(data.frame(AF = x),'AF',paste0('timpoint_',c(1:(length(samples.num)+1))),sep = '\\|'),2,function(one.tp.afs){
-      mean(unlist(lapply(one.tp.afs,function(tmp.af){
-        if(tmp.af == 'NA'){return(0)}
-        else{
-          read.counts = as.numeric(str_split(gsub('\\(.*','',tmp.af),'-')[[1]])
-          return((read.counts[1]+read.counts[2])/read.counts[3])
+  if (samples.num != -1) {
+    paste0(round(apply(separate(data.frame(AF = x), "AF", paste0("timpoint_", c(1:(length(samples.num) + 1))), sep = "\\|"), 2, function(one.tp.afs) {
+      mean(unlist(lapply(one.tp.afs, function(tmp.af) {
+        if (tmp.af == "NA") {
+          return(0)
+        }
+        else {
+          read.counts <- as.numeric(str_split(gsub("\\(.*", "", tmp.af), "-")[[1]])
+          return((read.counts[1] + read.counts[2]) / read.counts[3])
         }
       })))
-    }),digits = 3),collapse = '|')
-  }else{
+    }), digits = 3), collapse = "|")
+  } else {
     print(x)
-    as.character(round(mean(unlist(lapply(x,function(tmp.af){
-      if(tmp.af == 'NA'){return(0)}
-      else{
-        read.counts = as.numeric(str_split(gsub('\\(.*','',tmp.af),'-')[[1]])
-        return((read.counts[1]+read.counts[2])/read.counts[3])
+    as.character(round(mean(unlist(lapply(x, function(tmp.af) {
+      if (tmp.af == "NA") {
+        return(0)
+      }
+      else {
+        read.counts <- as.numeric(str_split(gsub("\\(.*", "", tmp.af), "-")[[1]])
+        return((read.counts[1] + read.counts[2]) / read.counts[3])
       }
-    }))),digits = 3))
+    }))), digits = 3))
   }
 }
 
 # convert naming to timepoint, get rid of uncovered impact and access calls
-process_maf_for_graph = function(tmp.maf){
-  print('convert naming to timepoint, get rid of uncovered impact and access calls')
+process_maf_for_graph <- function(tmp.maf) {
+  print("convert naming to timepoint, get rid of uncovered impact and access calls")
   # tmp.maf = ret.054.calls
   # tumor sample
-  tumor.sample = structure(gsub('-','',str_extract(unique(tmp.maf$Tumor_Sample_Barcode[grep('IM[0-9]$',tmp.maf$Tumor_Sample_Barcode)]),'-T..-')),
-                           names = as.character(unique(tmp.maf$Tumor_Sample_Barcode[grep('IM[0-9]$',tmp.maf$Tumor_Sample_Barcode)])))
+  tumor.sample <- structure(gsub("-", "", str_extract(unique(tmp.maf$Tumor_Sample_Barcode[grep("IM[0-9]$", tmp.maf$Tumor_Sample_Barcode)]), "-T..-")),
+    names = as.character(unique(tmp.maf$Tumor_Sample_Barcode[grep("IM[0-9]$", tmp.maf$Tumor_Sample_Barcode)]))
+  )
   print(tumor.sample)
   # rest of the samples are plasma
-  plasma.sample = setdiff(tmp.maf$Tumor_Sample_Barcode,names(tumor.sample))
+  plasma.sample <- setdiff(tmp.maf$Tumor_Sample_Barcode, names(tumor.sample))
   # filter for plasma sample only
-  tmp.maf = tmp.maf[Tumor_Sample_Barcode %in% plasma.sample]
+  tmp.maf <- tmp.maf[Tumor_Sample_Barcode %in% plasma.sample]
   # change samples into timepoint information
-  plasma.sample = structure(case_when(
+  plasma.sample <- structure(case_when(
     # some of the DA-ret sample need to be renamed
-    grepl('-T0._',plasma.sample) ~ gsub('-|_','',gsub('T','L0',str_extract(plasma.sample,'-T0._'))),
+    grepl("-T0._", plasma.sample) ~ gsub("-|_", "", gsub("T", "L0", str_extract(plasma.sample, "-T0._"))),
     # otherwise extract L00 something
-    TRUE ~ gsub('-','',str_extract(plasma.sample,'-L...-'))
-  ),names = plasma.sample)
+    TRUE ~ gsub("-", "", str_extract(plasma.sample, "-L...-"))
+  ), names = plasma.sample)
   print(plasma.sample)
-  sample.name.conversion = c(tumor.sample,plasma.sample)
+  sample.name.conversion <- c(tumor.sample, plasma.sample)
   print(sample.name.conversion)
   # get all not covered calls
-  not.covered.df = unique(tmp.maf[call_confidence == 'Not Covered',.N,.(Hugo_Symbol,Chromosome,Start_Position,End_Position,Variant_Classification,
-                                                                        HGVSp_Short,Reference_Allele,Tumor_Seq_Allele2)])[N > length(plasma.sample)/2]
-  only.covered.tmp.maf = anti_join(tmp.maf,not.covered.df,by = c('Hugo_Symbol','Chromosome','Start_Position','End_Position','Variant_Classification',
-                                                                 'HGVSp_Short','Reference_Allele','Tumor_Seq_Allele2')) %>% data.table()
+  not.covered.df <- unique(tmp.maf[call_confidence == "Not Covered", .N, .(
+    Hugo_Symbol, Chromosome, Start_Position, End_Position, Variant_Classification,
+    HGVSp_Short, Reference_Allele, Tumor_Seq_Allele2
+  )])[N > length(plasma.sample) / 2]
+  only.covered.tmp.maf <- anti_join(tmp.maf, not.covered.df, by = c(
+    "Hugo_Symbol", "Chromosome", "Start_Position", "End_Position", "Variant_Classification",
+    "HGVSp_Short", "Reference_Allele", "Tumor_Seq_Allele2"
+  )) %>% data.table()
   # only the converted timepoint names
   # only.covered.tmp.maf$Tumor_Sample_Barcode = sample.name.conversion[as.character(only.covered.tmp.maf$Tumor_Sample_Barcode)]
-  if(any(grepl('__',only.covered.tmp.maf$Hugo_Symbol))){
-    fusion.only.covered.tmp.maf = data.table(only.covered.tmp.maf)[grepl('__',Hugo_Symbol)]
+  if (any(grepl("__", only.covered.tmp.maf$Hugo_Symbol))) {
+    fusion.only.covered.tmp.maf <- data.table(only.covered.tmp.maf)[grepl("__", Hugo_Symbol)]
     # process original hugo_symbol column (sort two genes by name)
-    fusion.only.covered.tmp.maf$Hugo_Symbol = unlist(lapply(fusion.only.covered.tmp.maf$Hugo_Symbol,function(x){paste0(sort(str_split(x,'__')[[1]]),collapse = '-')}))
-    fusion.only.covered.tmp.maf$Chromosome = unlist(lapply(fusion.only.covered.tmp.maf$Chromosome,function(x){paste0(sort(str_split(x,'__')[[1]]),collapse = '-')}))
+    fusion.only.covered.tmp.maf$Hugo_Symbol <- unlist(lapply(fusion.only.covered.tmp.maf$Hugo_Symbol, function(x) {
+      paste0(sort(str_split(x, "__")[[1]]), collapse = "-")
+    }))
+    fusion.only.covered.tmp.maf$Chromosome <- unlist(lapply(fusion.only.covered.tmp.maf$Chromosome, function(x) {
+      paste0(sort(str_split(x, "__")[[1]]), collapse = "-")
+    }))
     # collapsing AF for rows of the same events (i.e. reciprocal rearrangement) while perserving the sample level seaparation in AF
-    fusion.only.covered.tmp.maf = fusion.only.covered.tmp.maf[,.(Start_Position = Start_Position[1],End_Position = End_Position[1],HGVSp_Short = HGVSp_Short[1],
-                                                                 Reference_Allele = Reference_Allele[1], Tumor_Seq_Allele2 = Tumor_Seq_Allele2[1],
-                                                                 ExAC_AF = ExAC_AF[1], Hotspot = Hotspot[1], DMP = DMP[1], duplex_support_num = duplex_support_num[1],
-                                                                 call_confidence = ifelse(any(call_confidence == 'Called'),'Called','Not Called'),
-                                                                 call_info = paste0(call_info,collapse = ' | '),CH = 'No',
-                                                                 t_alt_count = sum(t_alt_count,na.rm = T),t_total_count = sum(t_total_count,na.rm = T)),
-                                                              .(Hugo_Symbol,Chromosome,Variant_Classification,Tumor_Sample_Barcode)]
-    only.covered.tmp.maf = only.covered.tmp.maf[-grep('__',Hugo_Symbol)]
-    only.covered.tmp.maf = rbind(only.covered.tmp.maf,fusion.only.covered.tmp.maf)
+    fusion.only.covered.tmp.maf <- fusion.only.covered.tmp.maf[
+      , .(
+        Start_Position = Start_Position[1], End_Position = End_Position[1], HGVSp_Short = HGVSp_Short[1],
+        Reference_Allele = Reference_Allele[1], Tumor_Seq_Allele2 = Tumor_Seq_Allele2[1],
+        ExAC_AF = ExAC_AF[1], Hotspot = Hotspot[1], DMP = DMP[1], duplex_support_num = duplex_support_num[1],
+        call_confidence = ifelse(any(call_confidence == "Called"), "Called", "Not Called"),
+        call_info = paste0(call_info, collapse = " | "), CH = "No",
+        t_alt_count = sum(t_alt_count, na.rm = T), t_total_count = sum(t_total_count, na.rm = T)
+      ),
+      .(Hugo_Symbol, Chromosome, Variant_Classification, Tumor_Sample_Barcode)
+    ]
+    only.covered.tmp.maf <- only.covered.tmp.maf[-grep("__", Hugo_Symbol)]
+    only.covered.tmp.maf <- rbind(only.covered.tmp.maf, fusion.only.covered.tmp.maf)
   }
-  only.covered.tmp.maf$t_alt_count = ifelse(is.na(only.covered.tmp.maf$t_alt_count),0,only.covered.tmp.maf$t_alt_count)
-  only.covered.tmp.maf$t_total_count = ifelse(is.na(only.covered.tmp.maf$t_total_count),0,only.covered.tmp.maf$t_total_count)
+  only.covered.tmp.maf$t_alt_count <- ifelse(is.na(only.covered.tmp.maf$t_alt_count), 0, only.covered.tmp.maf$t_alt_count)
+  only.covered.tmp.maf$t_total_count <- ifelse(is.na(only.covered.tmp.maf$t_total_count), 0, only.covered.tmp.maf$t_total_count)
   return(only.covered.tmp.maf)
 }
 
 # melting genotype tables into maf-like format
-table_to_maf = function(tmp.table,sample.table){
+table_to_maf <- function(tmp.table, sample.table) {
   # tmp.table = fillouts.dt
   # sample.table = sample.sheet
   # tmp.table = ret.006.table
   # sample.table = ret.006.sample.sheet
   # extract information for plasma and tumor
-  tmp.table = data.table(tmp.table)
-  lapply(sample.table[Sample_Type %in% c('duplex')]$Sample_Barcode,function(y){
-    sample.call.status.colname = paste0(y,'___duplex.called')
-    sample.af.colname = paste0(y,'___total')
-    tmp.table[,eval(y) := paste0(get(sample.call.status.colname),' | ',get(sample.af.colname))]
+  tmp.table <- data.table(tmp.table)
+  lapply(sample.table[Sample_Type %in% c("duplex")]$Sample_Barcode, function(y) {
+    sample.call.status.colname <- paste0(y, "___duplex.called")
+    sample.af.colname <- paste0(y, "___total")
+    tmp.table[, eval(y) := paste0(get(sample.call.status.colname), " | ", get(sample.af.colname))]
   })
-  lapply(sample.table[Sample_Type %in% c('DMP_Tumor')]$Sample_Barcode,function(y){
-    tmp.table[,eval(y) := paste0(case_when(
-      !is.na(get('DMP')) & get(paste0(sample.table[Sample_Type %in% c('duplex')]$Sample_Barcode[1],'___duplex.called')) != 'Not Covered' ~ 'Called',
-      !is.na(get('DMP')) & get(paste0(sample.table[Sample_Type %in% c('duplex')]$Sample_Barcode[1],'___duplex.called')) == 'Not Covered' ~ 'Called (but not covered in ACCESS)',
-      is.na(get('DMP')) & as.numeric(gsub('/.*','',get(paste0(y,'___DMP_Tumor')))) > 3 ~ 'Genotyped',
-      TRUE ~ 'Not Called'
-    ),' | ',get(paste0(y,'___DMP_Tumor')))]
+  lapply(sample.table[Sample_Type %in% c("DMP_Tumor")]$Sample_Barcode, function(y) {
+    tmp.table[, eval(y) := paste0(case_when(
+      !is.na(get("DMP")) & get(paste0(sample.table[Sample_Type %in% c("duplex")]$Sample_Barcode[1], "___duplex.called")) != "Not Covered" ~ "Called",
+      !is.na(get("DMP")) & get(paste0(sample.table[Sample_Type %in% c("duplex")]$Sample_Barcode[1], "___duplex.called")) == "Not Covered" ~ "Called (but not covered in ACCESS)",
+      is.na(get("DMP")) & as.numeric(gsub("/.*", "", get(paste0(y, "___DMP_Tumor")))) > 3 ~ "Genotyped",
+      TRUE ~ "Not Called"
+    ), " | ", get(paste0(y, "___DMP_Tumor")))]
   })
-  processed.tmp.table = tmp.table[,!grep('___',colnames(tmp.table)),with = F] %>%
+  processed.tmp.table <- tmp.table[, !grep("___", colnames(tmp.table)), with = F] %>%
     # melting data frame by tumor samples
-    melt(id.vars = c('Hugo_Symbol','Chromosome','Start_Position','End_Position','Variant_Classification','HGVSp_Short',
-                     'Reference_Allele','Tumor_Seq_Allele2','ExAC_AF','Hotspot','DMP','duplex_support_num','call_confidence','CH'),
-         variable.name = "Tumor_Sample_Barcode", value.name = "call_info") %>%
-    mutate(call_confidence =  gsub(' \\| ','',str_extract(call_info,'.*.\\| ')),call_info = gsub('.*.\\| ','',call_info)) %>% rowwise() %>%
-    mutate(t_alt_count = ifelse(grepl('-[0-9]+-',call_info),
-                                # SV parsing
-                                sum(as.numeric(str_split(call_info,'-|\\(')[[1]][1:2])),
-                                # SNV parsing
-                                as.numeric(gsub(' |\\/.*.','',call_info))),
-           t_total_count = ifelse(grepl('-[0-9]+-',call_info),
-                                  # SV parsing
-                                  as.numeric(str_split(call_info,'-|\\(')[[1]][3]),
-                                  # SNV parsing
-                                  as.numeric(gsub('.*.\\/|\\(.*.','',call_info)))) %>% data.table()
+    melt(
+      id.vars = c(
+        "Hugo_Symbol", "Chromosome", "Start_Position", "End_Position", "Variant_Classification", "HGVSp_Short",
+        "Reference_Allele", "Tumor_Seq_Allele2", "ExAC_AF", "Hotspot", "DMP", "duplex_support_num", "call_confidence", "CH"
+      ),
+      variable.name = "Tumor_Sample_Barcode", value.name = "call_info"
+    ) %>%
+    mutate(call_confidence = gsub(" \\| ", "", str_extract(call_info, ".*.\\| ")), call_info = gsub(".*.\\| ", "", call_info)) %>%
+    rowwise() %>%
+    mutate(
+      t_alt_count = ifelse(grepl("-[0-9]+-", call_info),
+        # SV parsing
+        sum(as.numeric(str_split(call_info, "-|\\(")[[1]][1:2])),
+        # SNV parsing
+        as.numeric(gsub(" |\\/.*.", "", call_info))
+      ),
+      t_total_count = ifelse(grepl("-[0-9]+-", call_info),
+        # SV parsing
+        as.numeric(str_split(call_info, "-|\\(")[[1]][3]),
+        # SNV parsing
+        as.numeric(gsub(".*.\\/|\\(.*.", "", call_info))
+      )
+    ) %>%
+    data.table()
   return(processed.tmp.table)
 }
 
 # main graphing function --------------------------------------------------
 
 #' @export
-plot_all_events = function(
-  master.ref,results.dir,
-  criteria = 'stringent'
-){
+plot_all_events <- function(
+                            master.ref, results.dir,
+                            criteria = "stringent") {
   # # test input section -----------------------------------------------------------
   # master.ref = fread('/juno/work/bergerm1/bergerlab/zhengy1/access_data_analysis/data/example_master_file.csv')
   # results.dir = paste0('/juno/work/bergerm1/MSK-ACCESS/ACCESS-Projects/test_access/access_data_analysis/output_042020/')
   # # criteria <- 'permissive'
   # criteria <- 'stringent'
-  # 
+  #
   # graph by patient --------------------------------------------------------
-  output.dir = paste0(results.dir,'/plots/')
+  output.dir <- paste0(results.dir, "/plots/")
   dir.create(output.dir)
   # for plotting consistency
-  status_id = c('Called' = 19, 'Not Called' =  4, 'Signed out' = 15,
-                'Not Signed out' = 13, 'Not Covered' = 8, 'Genotyped' = 17)
-  
+  status_id <- c(
+    "Called" = 19, "Not Called" = 4, "Signed out" = 15,
+    "Not Signed out" = 13, "Not Covered" = 8, "Genotyped" = 17
+  )
+
   # snv_sv_table = list.files(paste0(results.dir,'/results_',criteria,'_combined/'),full.names = T)
-  lapply(unique(master.ref$cmo_patient_id),function(x){
+  lapply(unique(master.ref$cmo_patient_id), function(x) {
     # THIS PLOTS PLASMA SAMPLES ONLY
     # SNV
-    tmp.table = fread(list.files(paste0(results.dir,'/results_',criteria,'_combined/'),x,full.names = T))[
-      call_confidence == 'High' | grepl('Protein Fusion: in frame',HGVSp_Short)
-      ]
-    tmp.sample.sheets <- fread(paste0(results.dir,'/',x,'/',x,'_sample_sheet.tsv'))[,.(Sample_Barcode,cmo_patient_id,Sample_Type)]
-    tmp.table = table_to_maf(tmp.table,tmp.sample.sheets)
-    tmp.table = data.table(process_maf_for_graph(tmp.table))
-    
+    tmp.table <- fread(list.files(paste0(results.dir, "/results_", criteria, "_combined/"), x, full.names = T))[
+      call_confidence == "High" | grepl("Protein Fusion: in frame", HGVSp_Short)
+    ]
+    tmp.sample.sheets <- fread(paste0(results.dir, "/", x, "/", x, "_sample_sheet.tsv"))[, .(Sample_Barcode, cmo_patient_id, Sample_Type)]
+    tmp.table <- table_to_maf(tmp.table, tmp.sample.sheets)
+    tmp.table <- data.table(process_maf_for_graph(tmp.table))
+
     # CNA
-    tmp.cna = do.call(rbind,lapply(master.ref[cmo_patient_id == x]$cmo_sample_id_plasma,function(y){
-      fread(paste0(results.dir,'/CNA_final_call_set/',y,'_cna_final_call_set.txt'))
+    tmp.cna <- do.call(rbind, lapply(master.ref[cmo_patient_id == x]$cmo_sample_id_plasma, function(y) {
+      fread(paste0(results.dir, "/CNA_final_call_set/", y, "_cna_final_call_set.txt"))
     }))
-    
-    # transform sample IDs into times
-    if(all(!is.na(as.Date(master.ref[cmo_patient_id == x]$collection_date,'%m/%d/%y')))){
-      transform.vector = structure(as.Date(master.ref[cmo_patient_id == x]$collection_date,'%m/%d/%y'),
-                                   names = master.ref[cmo_patient_id == x]$cmo_sample_id_plasma)
-      print(transform.vector)      
-    }else{
-      transform.vector = structure(as.character(master.ref[cmo_patient_id == x]$collection_date),
-                                   names = master.ref[cmo_patient_id == x]$cmo_sample_id_plasma)
+
+    if (all(!is.na(as.Date(master.ref[cmo_patient_id == x]$collection_date, "%m/%d/%y")))) {
+      transform.vector <- structure(as.Date(master.ref[cmo_patient_id == x]$collection_date, "%m/%d/%y"),
+        names = master.ref[cmo_patient_id == x]$cmo_sample_id_plasma
+      )
+      print("###Date Presentation:####")
+      print(transform.vector)
+    }
+    else {
+      transform.vector <- structure(as.character(master.ref[cmo_patient_id == x]$collection_date),
+        names = master.ref[cmo_patient_id == x]$cmo_sample_id_plasma
+      )
       print(transform.vector)
     }
-    tmp.table$Tumor_Sample_Barcode = transform.vector[tmp.table$Tumor_Sample_Barcode]
-    
-    if(nrow(tmp.table) == 0 | all(tmp.table$t_alt_count == 0)){
-      print('skiping to the next')
-      if(nrow(tmp.cna)) stop(paste0('Need to make CNA only file for: ',x))
+    tmp.table$Tumor_Sample_Barcode <- transform.vector[tmp.table$Tumor_Sample_Barcode]
+    print(tmp.table)
+    if (nrow(tmp.table) == 0 | all(tmp.table$t_alt_count == 0)) {
+      print("skiping to the next")
+      if (nrow(tmp.cna)) stop(paste0("Need to make CNA only file for: ", x))
       return()
     }
-    
-    colourCount = nrow(unique(tmp.table[,.(Hugo_Symbol,HGVSp_Short)]))
-    getPalette = colorRampPalette(brewer.pal(8, "Set2"))
-    SNV.SV.plot = ggplot(tmp.table) +
-      geom_line(aes(x = Tumor_Sample_Barcode, y = ifelse(t_total_count == 0, 0, as.numeric(t_alt_count/t_total_count)),
-                    color = paste0(Hugo_Symbol,' ',ifelse(grepl('^p\\.',HGVSp_Short),HGVSp_Short,'')),group = paste0(Hugo_Symbol,'_',HGVSp_Short))) +
-      geom_point(aes(x = Tumor_Sample_Barcode, y = ifelse(t_total_count == 0, 0, as.numeric(t_alt_count/t_total_count)),
-                     color = paste0(Hugo_Symbol,' ',ifelse(grepl('^p\\.',HGVSp_Short),HGVSp_Short,'')),shape = call_confidence),size = 1.5) +
-      labs(title=x,x='Time Point', y='VAF') + #scale_x_date(date_labels = "%Y %b %d") +
-      scale_shape_manual(values=status_id,name = 'Call Status') + scale_color_manual(values = getPalette(colourCount),name = 'Alteration') +
-      theme_minimal() + scale_y_log10() +
-      theme(panel.grid.major = element_blank(),legend.position="top",legend.box = "vertical",
-            axis.text.x = element_text(angle=45, hjust=1, face = 'bold'))
+
+    colourCount <- nrow(unique(tmp.table[, .(Hugo_Symbol, HGVSp_Short)]))
+    getPalette <- colorRampPalette(brewer.pal(8, "Set2"))
+    SNV.SV.plot <- ggplot(tmp.table) +
+      geom_line(aes(
+        x = Tumor_Sample_Barcode, y = ifelse(t_total_count == 0, 0, as.numeric(t_alt_count / t_total_count)),
+        color = paste0(Hugo_Symbol, " ", ifelse(grepl("^p\\.", HGVSp_Short), HGVSp_Short, "")), group = paste0(Hugo_Symbol, "_", HGVSp_Short)
+      )) +
+      geom_point(aes(
+        x = Tumor_Sample_Barcode, y = ifelse(t_total_count == 0, 0, as.numeric(t_alt_count / t_total_count)),
+        color = paste0(Hugo_Symbol, " ", ifelse(grepl("^p\\.", HGVSp_Short), HGVSp_Short, "")), shape = call_confidence
+      ), size = 1.5) +
+      labs(title = x, x = "Time Point", y = "VAF") +
+      scale_shape_manual(values = status_id, name = "Call Status") +
+      scale_color_manual(values = getPalette(colourCount), name = "Alteration") +
+      theme_minimal() +
+      scale_y_log10() +
+      scale_x_date(date_minor_breaks = "1 day", date_breaks = "1 week", date_labels = "%b %d") +
+      theme(
+        panel.grid.major = element_blank(), legend.position = "top", legend.box = "vertical",
+        axis.text.x = element_text(angle = 45, hjust = 1, face = "bold")
+      )
     print(SNV.SV.plot)
-    
-    if(nrow(tmp.cna) > 0){
-      tmp.cna = tmp.cna %>% mutate(Tumor_Sample_Barcode = factor(Tumor_Sample_Barcode,unique(tmp.sample.sheets[Sample_Type == 'duplex']$Sample_Barcode))) %>%
+
+    if (nrow(tmp.cna) > 0) {
+      tmp.cna <- tmp.cna %>%
+        mutate(Tumor_Sample_Barcode = factor(Tumor_Sample_Barcode, unique(tmp.sample.sheets[Sample_Type == "duplex"]$Sample_Barcode))) %>%
         # expand table on all empty samples without any calls
-        data.table() %>% dcast.data.table(Hugo_Symbol + CNA ~ Tumor_Sample_Barcode,drop = c(TRUE, FALSE),fill = 0,value.var = 'fc') %>%
-        melt.data.table(id.vars = c('Hugo_Symbol','CNA'),variable.name = 'Tumor_Sample_Barcode',value.name = 'fc') %>% data.table()
-      tmp.cna$Tumor_Sample_Barcode = transform.vector[tmp.cna$Tumor_Sample_Barcode]
-      
-      colourCount = nrow(unique(tmp.cna[,.(Hugo_Symbol,CNA)]))
-      getPalette = colorRampPalette(brewer.pal(8, "Set2"))
-      CNA.plot = ggplot(tmp.cna) +
-        geom_bar(aes(x = Tumor_Sample_Barcode,y = abs(fc),fill = paste0(Hugo_Symbol,'_',CNA)),position="dodge", stat="identity") +
-        labs(x='Time Point', y='Absolute fc') + #scale_x_date(date_labels = "%Y %b %d") +
-        scale_fill_manual(values = getPalette(colourCount),name = 'Alteration') +
-        theme_minimal() + theme(panel.grid.major = element_blank(),legend.position="bottom",axis.text.x = element_text(angle=45, hjust=1,face = 'bold'))
+        data.table() %>%
+        dcast.data.table(Hugo_Symbol + CNA ~ Tumor_Sample_Barcode, drop = c(TRUE, FALSE), fill = 0, value.var = "fc") %>%
+        melt.data.table(id.vars = c("Hugo_Symbol", "CNA"), variable.name = "Tumor_Sample_Barcode", value.name = "fc") %>%
+        data.table()
+      tmp.cna$Tumor_Sample_Barcode <- transform.vector[tmp.cna$Tumor_Sample_Barcode]
+
+      colourCount <- nrow(unique(tmp.cna[, .(Hugo_Symbol, CNA)]))
+      getPalette <- colorRampPalette(brewer.pal(8, "Set2"))
+      CNA.plot <- ggplot(tmp.cna) +
+        geom_bar(aes(x = Tumor_Sample_Barcode, y = abs(fc), fill = paste0(Hugo_Symbol, "_", CNA)), position = "dodge", stat = "identity") +
+        labs(x = "Time Point", y = "Absolute fc") +
+        scale_fill_manual(values = getPalette(colourCount), name = "Alteration") +
+        theme_minimal() +
+        scale_x_date(date_minor_breaks = "1 day", date_breaks = "1 week", date_labels = "%b %d") +
+        theme(panel.grid.major = element_blank(), legend.position = "bottom", axis.text.x = element_text(angle = 45, hjust = 1, face = "bold"))
       print(CNA.plot)
-      
-      pdf(paste0(output.dir,'/',x,'_all_events.pdf'),width = 10,height = 7)
-      print(ggarrange(SNV.SV.plot,CNA.plot,ncol = 1,heights = c(2,1)))
+
+      pdf(paste0(output.dir, "/", x, "_all_events.pdf"), width = 10, height = 7)
+      print(ggarrange(SNV.SV.plot, CNA.plot, ncol = 1, heights = c(2, 1)))
       dev.off()
-    }else{
-      pdf(paste0(output.dir,'/',x,'_all_events.pdf'),width = 10,height = 7)
+    } else {
+      pdf(paste0(output.dir, "/", x, "_all_events.pdf"), width = 10, height = 7)
       print(SNV.SV.plot)
       dev.off()
     }
@@ -239,22 +284,22 @@ suppressPackageStartupMessages({
 })
 
 if (!interactive()) {
-  
-  parser=ArgumentParser()
-  parser$add_argument('-m', '--masterref', type='character', help='File path to master reference file')
-  parser$add_argument('-o', '--resultsdir', type='character', help='Output directory')
-  parser$add_argument('-c', '--criteria', type='character', default = 'stringent',
-                      help='Calling criteria [default]')
-  args=parser$parse_args()
-  
-  master.ref = args$masterref
-  results.dir = args$resultsdir
-  criteria = args$criteria
-  
-  if(!criteria %in% c('stringent','permissive')){
-    stop('Criteria argument should be either stringent or permissive')
+  parser <- ArgumentParser()
+  parser$add_argument("-m", "--masterref", type = "character", help = "File path to master reference file")
+  parser$add_argument("-o", "--resultsdir", type = "character", help = "Output directory")
+  parser$add_argument("-c", "--criteria",
+    type = "character", default = "stringent",
+    help = "Calling criteria [default]"
+  )
+  args <- parser$parse_args()
+
+  master.ref <- args$masterref
+  results.dir <- args$resultsdir
+  criteria <- args$criteria
+
+  if (!criteria %in% c("stringent", "permissive")) {
+    stop("Criteria argument should be either stringent or permissive")
   }
-  
-  suppressWarnings(plot_all_events(fread(master.ref),results.dir,criteria))
-  
-}
+
+  suppressWarnings(plot_all_events(fread(master.ref), results.dir, criteria))
+}
\ No newline at end of file