scripts generating axis coloured subcols bp for PS

scripts/plotting/barplots_subcolours_aa_PS.R

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+getwd()
+setwd('~/git/LSHTM_analysis/scripts/plotting')
+getwd()
+
+#########################################################
+# TASK:
+
+#########################################################
+
+############################################################
+# 1: Installing and loading required packages and functions
+############################################################
+
+#source('Header_TT.R')
+source('barplot_colour_function.R')
+
+############################################################
+# 2: Read file: struct params data with columns containing
+# colours for axis labels
+############################################################
+#source("subcols_axis.R")
+source("subcols_axis_PS.R")
+
+# this should return
+# mut_pos_cols
+# my_df
+# my_df_u: df with unique mutations
+
+# clear excess variable
+# "mut_pos_cols" is just for inspection in case you need to cross check
+# position numbers and colours
+# open file from deskptop ("sample_axis_cols") for cross checking
+
+table(mut_pos_cols$lab_bg)
+sum( table(mut_pos_cols$lab_bg) ) == nrow(mut_pos_cols) # should  be True
+     
+table(mut_pos_cols$lab_bg2)
+sum( table(mut_pos_cols$lab_bg2) ) ==  nrow(mut_pos_cols) # should  be True
+
+table(mut_pos_cols$lab_fg)
+sum( table(mut_pos_cols$lab_fg) ) ==  nrow(mut_pos_cols) # should  be True
+
+# very important!
+my_axis_colours = mut_pos_cols$lab_fg
+
+# now clear mut_pos_cols
+rm(mut_pos_cols) 
+
+###########################
+# 2: Plot: DUET scores
+###########################
+#==========================
+# Plot 2: Barplot with scores (unordered)
+# corresponds to duet_outcome
+# Stacked Barplot with colours: duet_outcome @ position coloured by 
+# stability scores. This is a barplot where each bar corresponds 
+# to a SNP and is coloured by its corresponding DUET stability value.
+# Normalised values (range between -1 and 1 ) to aid visualisation
+# NOTE: since barplot plots discrete values, colour = score, so number of
+# colours will be equal to the no. of unique normalised scores 
+# rather than a continuous scale
+# will require generating the colour scale separately.
+#============================
+# sanity checks
+upos = unique(my_df$position)
+
+table(my_df$duet_outcome)
+table(my_df_u$duet_outcome)
+
+#=========================== 
+# Data preparation for plots
+#===========================
+# REASSIGNMENT as necessary
+df <- my_df_u
+rm(my_df, my_df_u)
+
+# add frequency of positions
+library(data.table)
+setDT(df)[, pos_count := .N, by = .(position)]
+
+# this is cummulative
+table(df$pos_count)
+
+# use group by on this
+library(dplyr)
+snpsBYpos_df <- df %>%
+  group_by(position) %>%
+  summarize(snpsBYpos = mean(pos_count))
+
+table(snpsBYpos_df$snpsBYpos)
+
+snp_count = sort(unique(snpsBYpos_df$snpsBYpos))
+
+# sanity checks
+# should be a factor
+is.factor(df$duet_outcome)
+#TRUE
+
+table(df$duet_outcome)
+
+# should be -1 and 1
+min(df$duet_scaled)
+max(df$duet_scaled)
+
+# sanity checks
+# very important!!!!
+tapply(df$duet_scaled, df$duet_outcome, min)
+
+tapply(df$duet_scaled, df$duet_outcome, max)
+
+# My colour FUNCTION: based on group and subgroup
+# in my case;
+# df = df
+# group = duet_outcome
+# subgroup = normalised score i.e duet_scaled
+
+# check unique values in normalised data
+u = unique(df$duet_scaled) 
+
+#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+# Run this section if rounding is to be used
+# specify number for rounding
+n = 3 
+df$duet_scaledR = round(df$duet_scaled, n)  
+ur = unique(df$duet_scaledR)
+
+# create an extra column called group which contains the "gp name and score" 
+# so colours can be generated for each unique values in this column
+
+#my_grp = df$duet_scaledR # rounding
+my_grp = df$duet_scaled # no rounding
+#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+df$group <- paste0(df$duet_outcome, "_", my_grp, sep = "") 
+
+# Call the function to create the palette based on the group defined above
+colours <- ColourPalleteMulti(df, "duet_outcome", "my_grp")
+print(paste0('Colour palette generated for: ', length(colours), ' colours'))
+my_title = "Protein stability (DUET)"
+
+#========================
+# plot with axis colours
+#========================
+class(df$lab_bg)
+
+# define cartesian coord
+my_xlim = length(unique(df$position)); my_xlim
+
+# axis label size
+my_xals = 18
+my_yals = 18
+
+# axes text size
+my_xats = 14
+my_yats = 18
+
+#******************
+# generate plot: with axis colours
+#******************
+# plot name and location
+# outdir/ (should be imported from reading file)
+print(paste0('plot will be in:', outdir))
+
+bp_aa_subcols_duet = "barplot_acoloured_PS.svg"
+plot_bp_aa_subcols_duet = paste0(outdir, "/plots/", bp_aa_subcols_duet)
+
+print(paste0('plot name:', plot_bp_aa_subcols_duet))
+
+svg(plot_bp_aa_subcols_duet, width = 26, height = 4)
+
+g = ggplot(df, aes(factor(position, ordered = T)))
+
+outPlot = g + 
+  coord_cartesian(xlim = c(1, my_xlim)
+                  #, ylim = c(0, 6)
+                  , ylim = c(0, max(snp_count))
+                  , clip = "off") +
+  geom_bar(aes(fill = group), colour = "grey") +
+  scale_fill_manual(values = colours
+                     , guide = 'none') +
+  geom_tile(aes(,-0.8, width = 0.95, height = 0.85)
+            , fill = df$lab_bg) +
+  geom_tile(aes(,-1.2, width = 0.95, height = -0.2)
+            , fill = df$lab_bg2) +
+  
+# Here it's important to specify that your axis goes from 1 to max number of levels
+  theme(axis.text.x = element_text(size = my_xats
+                                    , angle = 90
+                                    , hjust = 1
+                                    , vjust = 0.4
+                                    , colour = my_axis_colours)
+         , axis.text.y = element_text(size = my_yats 
+                                      , angle = 0
+                                      , hjust = 1
+                                      , vjust = 0)
+         , axis.title.x = element_text(size = my_xals)
+         , axis.title.y = element_text(size = my_yals ) 
+         , axis.ticks.x = element_blank()) +
+  labs(title = ""
+       , x = "position"
+       , y = "Frequency")
+
+print(outPlot)
+dev.off()
+
+#!!!!!!!!!!!!!!!!
+#Warning message:
+#  Vectorized input to `element_text()` is not officially supported.
+#Results may be unexpected or may change in future versions of ggplot2. 
+#!!!!!!!!!!!!!!!!!
+
+# for sanity and good practice
+#rm(df)