added barplots_subcolours.R that generates heatmap style barplots
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scripts/plotting/barplots_subcolours.R
Executable file
237
scripts/plotting/barplots_subcolours.R
Executable file
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#!/usr/bin/env Rscript
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getwd()
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setwd("~/git/LSHTM_analysis/scripts/plotting")
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getwd()
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source("Header_TT.R")
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drug = 'streptomycin'
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gene = 'gid'
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spec = matrix(c(
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"drug" , "d", 1, "character",
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"gene" , "g", 1, "character",
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"data_file1" , "fa", 2, "character",
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"data_file2" , "fb", 2, "character"
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), byrow = TRUE, ncol = 4)
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opt = getopt(spec)
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drug = opt$drug
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gene = opt$gene
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infile_params = opt$data_file1
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infile_metadata = opt$data_file2
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if(is.null(drug)|is.null(gene)) {
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stop("Missing arguments: --drug and --gene must both be specified (case-sensitive)")
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}
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#===========
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# Input
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#===========
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source("../functions/barplot_colour_function.R")
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source("get_plotting_dfs.R")
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#===========
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# output
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#===========
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# PS
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bp_subcols_duet = "barplot_coloured_PS.svg"
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plot_bp_subcols_duet = paste0(plotdir, "/", bp_subcols_duet)
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# LIG
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bp_subcols_lig = "barplot_coloured_LIG.svg"
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plot_bp_subcols_lig = paste0(plotdir, "/", bp_subcols_lig)
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##############################################################################
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#====================
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# Data for plots: PS
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#====================
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# sanity checks
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str(my_df_u)
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upos = unique(my_df_u$position)
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# should be a factor
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if (is.factor(my_df_u$duet_outcome)){
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print("duet_outcome is factor")
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}else{
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print("convert duet_outcome to factor")
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my_df_u$duet_outcome = as.factor(my_df_u$duet_outcome)
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}
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is.factor(my_df_u$duet_outcome)
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table(my_df_u$duet_outcome)
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# should be -1 and 1
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min(my_df_u$duet_scaled)
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max(my_df_u$duet_scaled)
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tapply(my_df_u$duet_scaled, my_df_u$duet_outcome, min)
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tapply(my_df_u$duet_scaled, my_df_u$duet_outcome, max)
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#=======================================================
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# Barplot (unordered) colour each nsSNP by stability
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## My colour FUNCTION: based on group and subgroup
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# in my case;
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# df = df
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# group = duet_outcome
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# subgroup = normalised score i.e duet_scaled
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#========================================================
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# check unique values in normalised data
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u = unique(my_df_u$duet_scaled)
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my_grp = my_df_u$duet_scaled #no rounding
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#-------------------------------------------------
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# Run this section if rounding is to be used
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#n = 3
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#my_df_u$duet_scaledR = round(my_df_u$duet_scaled, n)
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#ur = unique(my_df_u$duet_scaledR)
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#my_grp = my_df_u$duet_scaledR # rounding
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#---------------------------------------------------
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my_df_u$group <- paste0(my_df_u$duet_outcome, "_", my_grp, sep = "")
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# Call the function to create the palette based on the group defined above
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colours <- ColourPalleteMulti(my_df_u, "duet_outcome", "my_grp")
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print(paste0("Colour palette generated for: ", length(colours), " colours"))
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my_title = "Protein stability (DUET)"
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# axis label size
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my_xaxls = 12
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my_yaxls = 20
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# axes text size
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my_xaxts = 18
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my_yaxts = 20
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#********************
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# generate plot: PS
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# NO axis colours
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#********************
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print(paste0("plot name:", plot_bp_subcols_duet))
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svg(plot_bp_subcols_duet, width = 26, height = 4)
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g = ggplot(my_df_u, aes(factor(position, ordered = T)))
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outPlot_bp_ps = g +
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geom_bar(aes(fill = group), colour = "grey") +
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scale_fill_manual( values = colours
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, guide = "none") +
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theme( axis.text.x = element_text(size = my_xaxls
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, angle = 90
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, hjust = 1
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, vjust = 0.4)
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, axis.text.y = element_text(size = my_yaxls
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, angle = 0
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, hjust = 1
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, vjust = 0)
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, axis.title.x = element_text(size = my_xaxts)
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, axis.title.y = element_text(size = my_yaxts ) ) +
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labs(title = ""
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#title = my_title
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, x = "Position"
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, y = "Frequency")
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print(outPlot_bp_ps)
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dev.off()
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####################################################
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#====================
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# Data for plots: LIG
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#====================
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# sanity checks
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str(my_df_u_lig)
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upos = unique(my_df_u_lig$position)
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# should be a factor
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if (is.factor(my_df_u_lig$ligand_outcome)){
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print("ligand_outcome is factor")
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}else{
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print("convert ligand_outcome to factor")
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my_df_u_lig$ligand_outcome = as.factor(my_df_u_lig$ligand_outcome)
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}
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is.factor(my_df_u_lig$ligand_outcome)
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table(my_df_u_lig$ligand_outcome)
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# should be -1 and 1
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min(my_df_u_lig$affinity_scaled)
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max(my_df_u_lig$affinity_scaled)
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tapply(my_df_u_lig$affinity_scaled, my_df_u_lig$ligand_outcome, min)
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tapply(my_df_u_lig$affinity_scaled, my_df_u_lig$ligand_outcome, max)
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#=======================================================
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# Barplot (unordered) colour each nsSNP by stability
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## My colour FUNCTION: based on group and subgroup
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# in my case;
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# df = my_df_u_lig
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# group = ligand_outcome
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# subgroup = normalised score i.e affinity_scaled
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#========================================================
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# check unique values in normalised data
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u_lig = unique(my_df_u_lig$affinity_scaled)
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my_grp_lig = my_df_u_lig$affinity_scaled #no rounding
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#-------------------------------------------------
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# Run this section if rounding is to be used
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#n = 3
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#my_df_u_lig$affinity_scaledR = round(my_df_u_lig$affinity_scaled, n)
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#ur_lig = unique(my_df_u_lig$affinity_scaledR)
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#my_grp_lig = my_df_u_lig$affinity_scaledR # rounding
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#---------------------------------------------------
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my_df_u_lig$group_lig <- paste0(my_df_u_lig$ligand_outcome, "_"
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, my_grp_lig
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, sep = "")
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# Call the function to create the palette based on the group defined above
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colours_lig <- ColourPalleteMulti(my_df_u_lig
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, "ligand_outcome"
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, "my_grp_lig")
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print(paste0("Colour palette generated for: "
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, length(colours_lig)
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, " colours_lig"))
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my_title_lig = "Ligand Affinity"
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# axis label size
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my_xaxls = 12
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my_yaxls = 20
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# axes text size
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my_xaxts = 18
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my_yaxts = 20
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#******************
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# generate plot: LIG
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# NO axis colours
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#******************
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print(paste0("plot name:", plot_bp_subcols_lig))
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svg(plot_bp_subcols_lig, width = 26, height = 4)
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g2 = ggplot(my_df_u_lig, aes(factor(position, ordered = T)))
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outPlot_bp_lig = g2 +
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geom_bar(aes(fill = group_lig), colour = "grey") +
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scale_fill_manual( values = colours_lig
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, guide = "none") +
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theme( axis.text.x = element_text(size = my_xaxls
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, angle = 90
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, hjust = 1
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, vjust = 0.4)
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, axis.text.y = element_text(size = my_yaxls
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, angle = 0
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, hjust = 1
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, vjust = 0)
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, axis.title.x = element_text(size = my_xaxts)
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, axis.title.y = element_text(size = my_yaxts ) ) +
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labs(title = ""
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#title = my_title_lig
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, x = "Position"
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, y = "Frequency")
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print(outPlot_bp_lig)
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dev.off()
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######################################################################=
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# End of script
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######################################################################=
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