added logo_plots.R that now produces all logo plots while sourcing the get_plotting_df.R script
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3 changed files with 271 additions and 4 deletions
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@ -108,8 +108,9 @@ cat("No. of rows in my_data:", nrow(logo_data)
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, "\nDistinct positions corresponding to snps:", length(c1)
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, "\nDistinct positions corresponding to snps:", length(c1)
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, "\n===========================================================")
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, "\n===========================================================")
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#=======================================================================
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#=======================================================================
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#%% logo plots from dataframe
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#==================
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# logo data: OR
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#==================
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foo = logo_data[, c("position"
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foo = logo_data[, c("position"
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, "mutant_type","duet_scaled", "or_mychisq"
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, "mutant_type","duet_scaled", "or_mychisq"
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, "mut_prop_polarity", "mut_prop_water")]
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, "mut_prop_polarity", "mut_prop_water")]
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@ -132,7 +133,6 @@ position_or = as.numeric(colnames(wide_df_or))
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#==================
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#==================
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# logo data: logOR
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# logo data: logOR
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#==================
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#==================
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# extracting data with log10R
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logo_data_plot_logor = logo_data[, c("position", "mutant_type", "log10or")]
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logo_data_plot_logor = logo_data[, c("position", "mutant_type", "log10or")]
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wide_df_logor <- logo_data_plot_logor %>% spread(position, log10or, fill = 0.0)
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wide_df_logor <- logo_data_plot_logor %>% spread(position, log10or, fill = 0.0)
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@ -217,6 +217,20 @@ rownames(tab_wt)
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identical(colnames(tab_mt), colnames(tab_wt))
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identical(colnames(tab_mt), colnames(tab_wt))
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identical(ncol(tab_mt), ncol(tab_wt))
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identical(ncol(tab_mt), ncol(tab_wt))
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#----------------------------------
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# logo data OR: multiple nsSNPs (>1)
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#----------------------------------
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logo_data_or_mult = my_data_snp[, c("position", "mutant_type", "or_mychisq")]
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#wide_df_or <- logo_data_or %>% spread(position, or_mychisq, fill = 0.0)
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wide_df_or_mult <- logo_data_or_mult %>% spread(position, or_mychisq, fill = NA)
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wide_df_or_mult = as.matrix(wide_df_or_mult)
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rownames(wide_df_or_mult) = wide_df_or_mult[,1]
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wide_df_or_mult = wide_df_or_mult[,-1]
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str(wide_df_or_mult)
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position_or_mult = as.numeric(colnames(wide_df_or_mult))
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########################################################################
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########################################################################
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# End of script
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# End of script
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########################################################################
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########################################################################
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253
scripts/plotting/logo_plots.R
Executable file
253
scripts/plotting/logo_plots.R
Executable file
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@ -0,0 +1,253 @@
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#!/usr/bin/env Rscript
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#########################################################
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# TASK: producing logo-type plot showing
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## OR
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## Log OR
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# multiple muts (>1 per position) coloured by aa property
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## mutant_type
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## wild_type
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# Note: Replaced scripts:
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## logo_plot.R
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## logo_multiple_muts.R
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## logo_combined.R
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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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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("get_plotting_dfs.R")
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#===========
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# output
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#===========
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logo_or_plotname = "logo_or_plot.svg"
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plot_logo_or = paste0(plotdir,"/", logo_or_plotname)
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logo_logOR_plotname = "logo_logOR_plot.svg"
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plot_logo_logOR = paste0(plotdir,"/", logo_logOR_plotname)
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logo_multiple_muts = "logo_multiple_muts.svg"
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plot_logo_multiple_muts = paste0(plotdir,"/", logo_multiple_muts)
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logo_combined_labelled = "logo_combined_labelled.svg"
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plot_logo_combined_labelled = paste0(plotdir,"/", logo_combined_labelled)
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#########################################################
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#==================================
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# Output
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# Logo plot OR: custom height (OR)
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#==================================
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cat("Logo plot with OR as y axis:", plot_logo_or)
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svg(plot_logo_or, width = 30 , height = 6)
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logo_or = ggseqlogo(wide_df_or
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, method = "custom"
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, seq_type = "aa") + ylab("my custom height") +
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theme( axis.text.x = element_text(size = 12
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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 = 22
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, angle = 0
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, hjust = 1
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, vjust = 0)
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, axis.title.y = element_text(size = 25)
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, axis.title.x = element_text(size = 20)
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#, legend.position = "bottom") +
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, legend.position = "none")+
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#, legend.text = element_text(size = 15)
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#, legend.title = element_text(size = 15))+
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scale_x_discrete("Position"
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#, breaks
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, labels = position_or
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, limits = factor(1:length(position_or))) +
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ylab("Odds Ratio")
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print(logo_or)
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#dev.off()
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#=============================================
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# Output
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# Logo plot LOG OR: custom height (Log10 OR)
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#=============================================
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cat("Logo plot with log10 OR as y axis:", plot_logo_logOR)
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svg(plot_logo_logOR, width = 30 , height = 6)
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logo_logOR = ggseqlogo(wide_df_logor_m
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, method = "custom"
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, seq_type="aa") + ylab("my custom height") +
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theme(legend.position = "bottom"
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, axis.text.x = element_text(size = 13
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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 = 20
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, angle = 0
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, hjust = 1
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, vjust = 0)
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, axis.title.y = element_text(size = 25)
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, axis.title.x = element_text(size = 20))+
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scale_x_discrete("Position"
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#, breaks
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, labels = position_logor
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, limits = factor(1:length(position_logor)))+
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ylab("Log (Odds Ratio)") +
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scale_y_continuous(limits = c(0, 9))
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print(logo_logOR)
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#dev.off()
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#*****************************
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# Mutant logo plot: >1 nsSNP
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#******************************
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p0 = ggseqlogo(tab_mt
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, method = 'custom'
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, seq_type = 'aa') +
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#ylab('my custom height') +
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theme(axis.text.x = element_blank()) +
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theme(text=element_text(family="FreeSans"))+
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theme_logo()+
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scale_x_continuous(breaks = 1:ncol(tab_mt)
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, labels = colnames(tab_mt))+
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scale_y_continuous( breaks = 1:max_mult_mut
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, limits = c(0, max_mult_mut))
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#p0
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cat('\nDone: p0')
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# further customisation
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mut_logo_p = p0 + theme(legend.position = "none"
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, legend.title = element_blank()
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, legend.text = element_text(size = 20)
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, axis.text.x = element_text(size = 14, angle = 90)
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, axis.text.y = element_blank())
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#mut_logo_p
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cat('\nDone: p0+mut_logo_p')
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#*************************
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# Wild logo plot: >1 nsSNP
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#*************************
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p2 = ggseqlogo(tab_wt
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, method = 'custom'
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, seq_type = 'aa'
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#, col_scheme = "taylor"
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#, col_scheme = chemistry2
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) +
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#ylab('my custom height') +
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theme(text=element_text(family="FreeSans"))+
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theme(axis.text.x = element_blank()
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, axis.text.y = element_blank()) +
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theme_logo() +
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scale_x_continuous(breaks = 1:ncol(tab_wt)
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, labels = colnames(tab_wt))
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#p2
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cat('\nDone: p2')
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# further customise
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wt_logo_p = p2 +
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theme(legend.position = "bottom"
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#, legend.title = element_blank()
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, legend.title = element_text("Amino acid properties", size = 20)
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, legend.text = element_text(size = 20)
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, axis.text.x = element_text(size = 14, angle = 90)
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, axis.text.y = element_blank()
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, axis.title.x = element_text(size = 22))+
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labs(x= "Position")
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#wt_logo_p
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cat('\nDone: wt_logo_p')
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#***********************
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# Logo OR >1 nsSNP
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#***********************
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logo_or_mult_p = ggseqlogo(wide_df_or_mult, method="custom", seq_type="aa") + ylab("my custom height") +
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theme(axis.text.x = element_text(size = 14
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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 = 18
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, angle = 0
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, hjust = 1
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, vjust = 0)
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, axis.title.y = element_text(size = 18)
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, axis.title.x = element_blank()
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, legend.position = "none")+
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scale_x_discrete( labels = position_or_mult
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, limits = factor(1:length(position_or_mult))) +
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scale_y_discrete(breaks = c(50, 150, 250, 350)
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, labels = c(50, 150, 250, 350)
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, limits = c(50, 150, 250, 350)
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) +
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xlab("Position") +
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ylab("Odds Ratio")
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#logo_or_mult_p
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cat('\nDone: logo_or_mult_p')
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#=========================================
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# Output
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# Combined plot: logo_mutliple_muts.svg
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#=========================================
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#suppressMessages( require(cowplot) )
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cat('\nDone: wt_logo_p')
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#plot_grid(p1, p3, ncol = 1, align = 'v')
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cat('\nDone: mut_logo_p + wt_logo_p')
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# colour scheme: https://rdrr.io/cran/ggseqlogo/src/R/col_schemes.r
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cat("\nOutput plot:", plot_logo_multiple_muts, "\n")
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svg(plot_logo_multiple_muts, width = 32, height = 10)
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mult_muts_combined = cowplot::plot_grid(mut_logo_p, wt_logo_p
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, nrow = 2
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, align = "v"
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, rel_heights = c(3/4, 1/4))
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print(mult_muts_combined)
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#dev.off()
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#======================================================
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# Output
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# Combined ALL logo plots: logOR, mut_logo and mut_logo
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#=====================================================
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cat("Output plot:", plot_logo_combined_labelled)
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svg(plot_logo_combined_labelled, width = 25, height = 10)
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all_logo_plots = cowplot::plot_grid(logo_or_mult_p
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, mut_logo_p
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, wt_logo_p
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, nrow = 3
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, align = "hv"
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#, labels = c("(a)","(b)", "(c)")
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, labels = "AUTO"
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, rel_heights = c(3/8, 3/8, 1.5/8)
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, rel_widths = c(0.85, 1, 1)
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, label_size = 25)
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print(all_logo_plots)
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#dev.off()
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