Tanushree Tunstall
bdbc97c40a
which annoyingly throws away lots of useful data that RShiny needs for clickable plots. Also split the "flame bar" for ligand distance out into separate functions in generate_distance_colour_map.R. This can now be easily incorporated into any "wide" graph showing all positions.
138 lines
No EOL
5.2 KiB
R
Executable file
138 lines
No EOL
5.2 KiB
R
Executable file
#!/usr/bin/env Rscript
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#########################################################
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# TASK: function for barplot showing no. of sites with nsSNP
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# count
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#########################################################
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# load libraries and functions
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library(ggplot2)
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library(data.table)
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library(dplyr)
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theme_set(theme_grey())
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#=================================================================
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# site_snp_count_bp(): barplots for no. of sites and nsSNP count
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# input args
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## df containing data to plot
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## df column name containing site/position numbers
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## ...opt args
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# TODO:
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# legend params, currently it appears as title
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# visually might be nicer for it to be inside the plot
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#=================================================================
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site_snp_count_bp <- function (plotdf
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, df_colname = "position"
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#, bp_plot_title = ""
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#, leg_title = "Legend title"
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, leg_text_size = 20
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, axis_text_size = 25
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, axis_label_size = 22
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, xaxis_title = "Number of nsSNPs"
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, yaxis_title = "Number of Sites"
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, title_colour = "chocolate4"
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, subtitle_text = NULL
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, subtitle_size = 20
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, subtitle_colour = "pink")
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{
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# dim of plotdf
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cat(paste0("\noriginal df dimensions:"
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, "\nNo. of rows:", nrow(plotdf)
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, "\nNo. of cols:", ncol(plotdf)
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, "\nNow adding column: frequency of mutational positions"))
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#-------------------------------------------
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# adding column: snpcount for each position
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#-------------------------------------------
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setDT(plotdf)[, pos_count := .N, by = .(eval(parse(text = df_colname)))]
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cat("\nCumulative nssnp count\n"
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, table(plotdf$pos_count))
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# calculating total no. of mutations
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tot_muts = sum(table(plotdf$pos_count))
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# sanity check
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if(tot_muts == nrow(plotdf)){
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cat("\nPASS: total number of mutations match"
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, "\nTotal no. of nsSNPs:", tot_muts)
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} else{
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cat("\nWARNING: total no. of muts = ", tot_muts
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, "\nExpected = ", nrow(plotdf))
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}
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# revised dimensions
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cat(paste0("\nrevised df dimensions:"
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, "\nNo. of rows:", nrow(plotdf)
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, "\nNo. of cols:", ncol(plotdf)))
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#------------------------------------------------------
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# creating df: average count of snpcount for each position
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# created in earlier step
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#-------------------------------------------------------
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# use group by on pos_count
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snpsBYpos_df <- plotdf %>%
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dplyr::group_by(eval(parse(text = df_colname))) %>%
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dplyr::summarise(snpsBYpos = mean(pos_count)) # changed from summarize!
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cat("\nnssnp count per position\n"
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, table(snpsBYpos_df$snpsBYpos)
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, "\n")
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# calculating total no. of sites associated with nsSNPs
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tot_sites = sum(table(snpsBYpos_df$snpsBYpos))
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# sanity check
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if(tot_sites == length(unique(plotdf$position))){
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cat("\nPASS: total number of mutation sites match"
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, "\nTotal no. of sites with nsSNPs:", tot_sites)
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} else{
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cat("WARNING: total no. of sites = ", tot_sites
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, "\nExpected = ", length(unique(plotdf$position)))
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}
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# FIXME: should really be legend title
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# but atm being using as plot title
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#my_leg_title
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bp_plot_title = paste0("Total nsSNPs: ", tot_muts
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, ", Total no. of nsSNPs sites: ", tot_sites)
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#-------------
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# start plot 2
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#--------------
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# to make x axis display all positions
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# not sure if to use with sort or directly
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my_x = sort(unique(snpsBYpos_df$snpsBYpos))
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ggplot(snpsBYpos_df, aes(x = snpsBYpos)) +
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geom_bar(aes (alpha = 0.5)
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, show.legend = FALSE) +
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scale_x_continuous(breaks = unique(snpsBYpos_df$snpsBYpos)) +
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geom_label(stat = "count", aes(label = ..count..)
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, color = "black"
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, size = 10) +
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theme(axis.text.x = element_text(size = axis_text_size
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, angle = 0)
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, axis.text.y = element_text(size = axis_text_size
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, angle = 0
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, hjust = 1)
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, axis.title.x = element_text(size = axis_label_size)
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, axis.title.y = element_text(size = axis_label_size)
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#, legend.position = c(0.73,0.8)
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#, legend.text = element_text(size = leg_text_size)
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#, legend.title = element_text(size = axis_label_size)
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, plot.title = element_text(size = leg_text_size
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, colour = title_colour)
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, plot.subtitle = element_text(size = subtitle_size
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, hjust = 0.5
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, colour = subtitle_colour)) +
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labs(title = bp_plot_title
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, subtitle = subtitle_text
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, x = xaxis_title
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, y = yaxis_title)
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}
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########################################################################
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# end of function
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######################################################################## |