get_lp_data = function(maf, geneID = NULL, AACol = NULL, refSeqID = NULL, proteinID = NULL, defaultYaxis = FALSE){

  if(is.null(geneID)){
    stop('Please provide a gene name.')
  }

  #Protein domain source.
  gff = system.file('extdata', 'protein_domains.RDs', package = 'maftools')
  gff = readRDS(file = gff)
  data.table::setDT(x = gff)

  mut = subsetMaf(maf = maf, includeSyn = FALSE, genes = geneID, query = "Variant_Type != 'CNV'")

  if(is.null(AACol)){
    pchange = c('HGVSp_Short', 'Protein_Change', 'AAChange')
    if(pchange[pchange %in% colnames(mut)] > 0){
      pchange = suppressWarnings(pchange[pchange %in% colnames(mut)][1])
      message(paste0("Assuming protein change information are stored under column ", pchange,". Use argument AACol to override if necessary."))
      colnames(mut)[which(colnames(mut) == pchange)] = 'AAChange'
    }else{
      message('Available fields:')
      print(colnames(mut))
      stop('AAChange field not found in MAF. Use argument AACol to manually specifiy field name containing protein changes.')
    }
  }else{
    colnames(mut)[which(colnames(mut) == AACol)] = 'AAChange'
  }

  prot.dat = mut[Hugo_Symbol %in% geneID, .(Variant_Type, Variant_Classification, AAChange)]
  if(nrow(prot.dat) == 0){
    stop(paste(geneID, 'does not seem to have any mutations!', sep=' '))
  }

  prot = gff[HGNC %in% geneID]

  if(nrow(prot) == 0){
    stop(paste('Structure for protein', geneID, 'not found.', sep=' '))
  }

  if(!is.null(refSeqID)){
    prot = gff[refseq.ID == refSeqID]
  } else if(!is.null(proteinID)){
    prot = gff[protein.ID == proteinID]
  } else{
    txs = unique(prot$refseq.ID)
    if(length(txs) > 1){
      message(paste(length(txs), ' transcripts available. Use arguments refSeqID or proteinID to manually specify tx name.', sep = ''))
      print(prot[!duplicated(protein.ID),.(HGNC, refseq.ID, protein.ID, aa.length)])
      prot = prot[which(prot$aa.length == max(prot$aa.length)),]
      if(length(unique(prot$refseq.ID)) > 1){
        prot = prot[which(prot$refseq.ID == unique(prot[,refseq.ID])[1]),]
        message(paste('Using longer transcript', unique(prot[,refseq.ID])[1], 'for now.', sep=' '))
      } else{
        message(paste('Using longer transcript', unique(prot[,refseq.ID])[1], 'for now.', sep=' '))
      }
    }
  }

  #Legth of protein
  len = as.numeric(max(prot$aa.length, na.rm = TRUE))
  #Remove NA's
  prot = prot[!is.na(Label)]
  prot = prot[,domain_lenght := End - Start][order(domain_lenght, decreasing = TRUE)][,domain_lenght := NULL]

  #hard coded colors for variant classification if user doesnt provide any

  sampleSize = as.numeric(maf@summary[ID %in% 'Samples', summary])
  mutRate = round(getGeneSummary(x = maf)[Hugo_Symbol %in% geneID, MutatedSamples]/sampleSize*100, digits = 2)
  cbioSubTitle = paste0(mutRate, "%")

  #prot.dat = prot.dat[Variant_Classification != 'Splice_Site']
  #Remove 'p.'
  prot.spl = strsplit(x = as.character(prot.dat$AAChange), split = '.', fixed = TRUE)
  prot.conv = sapply(sapply(prot.spl, function(x) x[length(x)]), '[', 1)

  prot.dat[,conv := prot.conv]
  #If conversions are in HGVSp_long (default HGVSp) format, we will remove strings Ter followed by anything (e.g; p.Asn1986GlnfsTer13)
  pos = gsub(pattern = 'Ter.*', replacement = '',x = prot.dat$conv)

  #Following parsing takes care of most of HGVSp_short and HGVSp_long format
  pos = gsub(pattern = '[[:alpha:]]', replacement = '', x = pos)
  pos = gsub(pattern = '\\*$', replacement = '', x = pos) #Remove * if nonsense mutation ends with *
  pos = gsub(pattern = '^\\*', replacement = '', x = pos) #Remove * if nonsense mutation starts with *
  pos = gsub(pattern = '\\*.*', replacement = '', x = pos) #Remove * followed by position e.g, p.C229Lfs*18


  #pos = as.numeric(sapply(strsplit(x = pos, split = '_', fixed = TRUE), '[[', 1))
  pos = as.numeric(sapply(X = strsplit(x = pos, split = '_', fixed = TRUE), FUN = function(x) x[1]))
  prot.dat[,pos := abs(pos)]

  if(nrow( prot.dat[is.na(pos)]) > 0){
    message(paste('Removed', nrow( prot.dat[is.na(prot.dat$pos),]), 'mutations for which AA position was not available', sep = ' '))
    #print(prot.dat[is.na(pos)])
    prot.dat = prot.dat[!is.na(pos)]
  }

  prot.snp.sumamry = prot.dat[,.N, .(Variant_Classification, conv, pos)]
  colnames(prot.snp.sumamry)[ncol(prot.snp.sumamry)] = 'count'
  maxCount = max(prot.snp.sumamry$count, na.rm = TRUE)

  prot.snp.sumamry = prot.snp.sumamry[order(prot.snp.sumamry$pos),]
  #prot.snp.sumamry$distance = c(0,diff(prot.snp.sumamry$pos))

  if(maxCount <= 5){
    prot.snp.sumamry$count2 = 1+prot.snp.sumamry$count
    lim.pos = 2:6
    lim.lab = 1:5
  }else{
    prot.snp.sumamry$count2 = 1+(prot.snp.sumamry$count * (5/max(prot.snp.sumamry$count)))
    lim.pos = prot.snp.sumamry[!duplicated(count2), count2]
    lim.lab = prot.snp.sumamry[!duplicated(count2), count]
  }

  if(length(lim.pos) > 6){
    lim.dat = data.table::data.table(pos = lim.pos, lab = lim.lab)
    lim.dat[,posRounded := round(pos)]
    lim.dat = lim.dat[!duplicated(posRounded)]
    lim.pos = lim.dat[,pos]
    lim.lab = lim.dat[,lab]
  }

  if(!defaultYaxis){
    lim.pos = c(min(lim.pos), max(lim.pos))
    lim.lab = c(min(lim.lab), max(lim.lab))
  }

  clusterSize = 10 #Change this later as an argument to user.
  repel = FALSE
  if(repel){
    prot.snp.sumamry = repelPoints(dat = prot.snp.sumamry, protLen = len, clustSize = clusterSize)
  }else{
    prot.snp.sumamry$pos2 = prot.snp.sumamry$pos
  }

  xlimPos = pretty(0:max(prot$aa.length))
  xlimPos[length(xlimPos)] = max(prot$aa.length)+3

  if(xlimPos[length(xlimPos)] - xlimPos[length(xlimPos)-1] <= 10){
    xlimPos = xlimPos[-(length(xlimPos)-1)]
  }

  return(list(prot.snp.sumamry, xlimPos, lim.pos, lim.lab, cbioSubTitle, prot))
}


label_pos = function(prot.snp.sumamry, labelPos = NULL, collapsePosLabel = TRUE){

    prot.snp.sumamry = data.table::data.table(prot.snp.sumamry)

    if(length(labelPos) == 1){
      if(labelPos != 'all'){
        prot.snp.sumamry$labThis = ifelse(test = prot.snp.sumamry$pos %in% labelPos, yes = 'yes', no = 'no')
        labDat = prot.snp.sumamry[labThis %in% 'yes']
      }else{
        labDat = prot.snp.sumamry
      }
    }else{
      prot.snp.sumamry$labThis = ifelse(test = prot.snp.sumamry$pos %in% labelPos, yes = 'yes', no = 'no')
      labDat = prot.snp.sumamry[labThis %in% 'yes']
    }

    if(nrow(labDat) == 0){
      message(paste0("Position ",labelPos, " doesn't seem to be mutated. Here are the mutated foci."))
      return(NULL)
    }



      uniquePos = unique(labDat[,pos2])
      labDatCollapsed = data.table::data.table()
      for(i in 1:length(uniquePos)){
        uniqueDat = labDat[pos2 %in% uniquePos[i]]
        if(nrow(uniqueDat) > 1){
          maxDat = max(uniqueDat[,count2])
          maxPos = unique(uniqueDat[,pos2])
          toLabel = uniqueDat[,conv]
          toLabel = paste(toLabel[1],paste(gsub(pattern = '^[A-z]*[[:digit:]]*', replacement = '', x = toLabel[2:length(toLabel)]), collapse = '/'), sep = '/')
          labDatCollapsed = rbind(labDatCollapsed, data.table::data.table(pos2 = maxPos, count2 = maxDat, conv = toLabel))
        }else{
          labDatCollapsed = rbind(labDatCollapsed, data.table::data.table(pos2 = uniqueDat[,pos2], count2 = uniqueDat[,count2], conv = uniqueDat[,conv]))
        }
      }
      labDat = labDatCollapsed

  labDat
}
