290 lines
9.2 KiB
R
290 lines
9.2 KiB
R
#!/usr/bin/env Rscript
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#########################################################
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# TASK: AF, OR and stability plots: PS
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# Output: 1 SVG
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#########################################################
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# Installing and loading required packages
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##########################################################
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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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library(ggplot2)
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library(data.table)
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#source("combining_dfs_plotting.R")
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#source("../functions/bp_subcolours.R")
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source("get_plotting_dfs.R")
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source("subcols_axis.R")
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###########################
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# Data for PS plots
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# you need merged_df3_comp/merged_df_comp
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# since these have unique SNPs
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###########################
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no_or_index = which(is.na(my_df_u_cols$or_mychisq))
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my_df_u_cols_clean = my_df_u_cols[-no_or_index,]
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#%%%%%%%%%%%%%%%%%%%%%%%%
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# REASSIGNMENT
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df = my_df_u_cols_clean
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#%%%%%%%%%%%%%%%%%%%%%%%%%
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cols_to_select = colnames(mut_pos_cols)
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mut_pos_cols_clean = df[colnames(df)%in%cols_to_select]
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mut_pos_cols_clean = unique(mut_pos_cols_clean[, 1:length(mut_pos_cols_clean)])
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########################################################################
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# end of data extraction and cleaning for plots #
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########################################################################
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#===========================
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# Barplot with axis colours:
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#===========================
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#================
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# Inspecting mut_pos_cols
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# position numbers and colours and assigning axis colours based on lab_fg
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# of the correct df
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# open file from desktop ("sample_axis_cols") for cross checking
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#================
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# very important!
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#my_axis_colours = mut_pos_cols$lab_fg
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if (nrow(mut_pos_cols_clean) == length(unique(df$position)) ){
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print("PASS: lengths checked, assigning axis colours")
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my_axis_colours = mut_pos_cols_clean$lab_fg
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cat("length of axis colours:", length(my_axis_colours)
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, "\nwhich corresponds to the number of positions on the x-axis of the plot")
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}else{
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print("FAIL:lengths mismatch, could not assign axis colours")
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quit()
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}
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# unique positions
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upos = unique(df$position); length(upos)
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table(df$duet_outcome)
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# add frequency of positions (from lib data.table)
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setDT(df)[, pos_count := .N, by = .(position)]
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# this is cummulative
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table(df$pos_count)
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# use group by on this
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library(dplyr)
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snpsBYpos_df <- df %>%
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group_by(position) %>%
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summarize(snpsBYpos = mean(pos_count))
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table(snpsBYpos_df$snpsBYpos)
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snp_count = sort(unique(snpsBYpos_df$snpsBYpos))
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# sanity checks
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# should be a factor
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if (is.factor(df$duet_outcome)){
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print("duet_outcome is factor")
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}else{
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print("converting duet_outcome to factor")
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df$duet_outcome = as.factor(df$duet_outcome)
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}
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is.factor(df$duet_outcome)
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# should be -1 and 1
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min(df$duet_scaled)
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max(df$duet_scaled)
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# sanity checks
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tapply(df$duet_scaled, df$duet_outcome, min)
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tapply(df$duet_scaled, df$duet_outcome, max)
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# My colour FUNCTION: based on group and subgroup
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# in my case;
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# df = df
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# group = duet_outcome
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# subgroup = normalised score i.e duet_scaled
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# check unique values in normalised data
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u = unique(df$duet_scaled)
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cat("No. of unique values in normalised data:", length(u))
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# Define group
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# Create an extra column called group which contains the "gp name and score"
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# so colours can be generated for each unique values in this column
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my_grp = df$duet_scaled # no rounding
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df$group <- paste0(df$duet_outcome, "_", my_grp, sep = "")
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# Call the function to create the palette based on the group defined above
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colours <- ColourPalleteMulti(df, "duet_outcome", "my_grp")
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print(paste0("Colour palette generated for: ", length(colours), " colours"))
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my_title = "Protein stability (DUET)"
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cat("No. of axis colours: ", length(my_axis_colours))
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#******************
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# generate plot: barplot unordered by frequency with axis colours
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#******************
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class(df$lab_bg)
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# define cartesian coord
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my_xlim = length(unique(df$position)); my_xlim
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# axis label size
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my_xals = 18
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my_yals = 18
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# axes text size
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my_xats = 14
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my_yats = 18
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g3 = ggplot(df, aes(factor(position, ordered = T)))
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p3 = g3 +
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coord_cartesian(xlim = c(1, my_xlim)
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#, ylim = c(0, 6)
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, ylim = c(0, max(snp_count))
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, clip = "off") +
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geom_bar(aes(fill = group), colour = "grey") +
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scale_fill_manual(values = colours
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, guide = "none") +
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geom_tile(aes(,-0.8, width = 0.95, height = 0.85)
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, fill = df$lab_bg) +
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geom_tile(aes(,-1.2, width = 0.95, height = -0.2)
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, fill = df$lab_bg2) +
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# Here it"s important to specify that your axis goes from 1 to max number of levels
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theme(axis.text.x = element_text(size = my_xats
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, angle = 90
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, hjust = 1
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, vjust = 0.4
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, colour = my_axis_colours)
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, axis.text.y = element_text(size = my_yats
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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_xals)
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, axis.title.y = element_text(size = my_yals+2 )
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, axis.ticks.x = element_blank()) +
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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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p3
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#=================
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# generate plot: AF by position unordered, not coloured
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#=================
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my_ats = 20 # axis text size
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my_als = 22 # axis label size
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g1 = ggplot(df)
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p1 = g1 +
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geom_bar(aes(x = factor(position, ordered = T)
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, y = af*100
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#, fill = duet_outcome
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)
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, color = "black"
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, fill = "lightgrey"
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, stat = "identity") +
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theme(axis.text.x = element_blank()
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, axis.text.y = element_text(size = my_ats
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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_blank()
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, axis.title.y = element_text(size = my_als) ) +
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labs(title = ""
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#, size = 100
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#, x = "Wild-type position"
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, y = "MAF(%)")
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p1
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#=================
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# generate plot: OR by position unordered
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#=================
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my_ats = 20 # axis text size
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my_als = 22 # axis label size
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g2 = ggplot(df)
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p2 = g2 +
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geom_bar(aes(x = factor(position, ordered = T)
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, y = or_mychisq
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#, fill = duet_outcome
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)
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, colour = "black"
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, fill = "lightgray"
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, stat = "identity") +
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scale_y_continuous(limits = c(0, 450))+
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theme(axis.text.x = element_blank()
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, axis.text.y = element_text(size = my_ats
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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_blank()
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, axis.title.y = element_text(size = my_als) ) +
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labs(#title = "OR by position"
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#, x = "Wild-type position"
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y = "OR")
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p2
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########################################################################
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# end of DUET barplots #
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########################################################################
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#============================
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# combined plot 1: UNlabelled
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#============================
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ps_combined = "af_or_combined_PS_v2.svg"
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plot_ps_combined = paste0(plotdir,"/", ps_combined)
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cat("combined plot Unlabelled:", plot_ps_combined)
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svg(plot_ps_combined , width = 26, height = 12)
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OutPlot_combined = cowplot::plot_grid(p1, p2, p3
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, ncol = 1
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, align = 'v')
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OutPlot_combined
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dev.off()
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#============================
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# combined plot 2: labelled
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#============================
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ps_combined_labelled = "af_or_combined_PS_labelled_v2.svg"
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plot_ps_combined_labelled = paste0(plotdir,"/", ps_combined_labelled)
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cat("combined plot Labelled:", plot_ps_combined_labelled)
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svg(plot_ps_combined_labelled , width = 26, height = 12)
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OutPlot_combined_labelled = cowplot::plot_grid(p1, p2, p3
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, ncol = 1
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#, labels = c("(a)", "(b)", "(c)")
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, labels = "AUTO"
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, label_size = 25
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, align = 'hv'
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, hjust = -0.4)
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OutPlot_combined_labelled
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dev.off()
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#============================
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# combined plot 2: labelled
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# ISMB poster July 2021
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#============================
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ps_combined_labelled_poster = "af_or_combined_PS_labelled_v2_poster.svg"
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plot_ps_combined_labelled_poster = paste0(plotdir,"/", ps_combined_labelled_poster)
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cat("combined plot Labelled:", plot_ps_combined_labelled_poster)
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svg(plot_ps_combined_labelled_poster , width = 26, height = 8)
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OutPlot_combined_labelled_poster = cowplot::plot_grid(p2, p3
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, ncol = 1
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#, labels = c("(a)", "(b)", "(c)")
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, labels = "AUTO"
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, label_size = 25
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, align = 'hv'
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, hjust = -0.4)
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OutPlot_combined_labelled_poster
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dev.off()
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