getwd()
setwd("~/git/LSHTM_analysis/mcsm_analysis/pyrazinamide/scripts/plotting")
getwd()
source("../Header_TT.R")
source("../barplot_colour_function.R")
############################################################
# Output dir for plots
############################################################
out_dir = "~/git/Data/pyrazinamide/output/plots"
source("subcols_axis.R")
table(mut_pos_cols$lab_bg)
#blue   cornflowerblue    green       purple    white  yellow
#2        2                2            4       117     3
sum( table(mut_pos_cols$lab_bg) ) == nrow(mut_pos_cols) # should  be True
table(mut_pos_cols$lab_bg2)
#green white
#2   128
sum( table(mut_pos_cols$lab_bg2) ) ==  nrow(mut_pos_cols) # should  be True
table(mut_pos_cols$lab_fg)
#black white
#124     6
sum( table(mut_pos_cols$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)
str(my_df$DUET_outcome)
colnames(my_df)
#===========================
# Data preparation for plots
#===========================
#!!!!!!!!!!!!!!!!!
# REASSIGNMENT
df <- my_df
#!!!!!!!!!!!!!!!!!
rm(my_df)
# sanity checks
# should be a factor
is.factor(df$DUET_outcome)
#TRUE
table(df$DUET_outcome)
#Destabilizing   Stabilizing
#288              47
# should be -1 and 1
min(df$ratioDUET)
max(df$ratioDUET)
# sanity checks
# very important!!!!
tapply(df$ratioDUET, df$DUET_outcome, min)
#Destabilizing   Stabilizing
#-1.0000000     0.01065719
tapply(df$ratioDUET, df$DUET_outcome, max)
#Destabilizing   Stabilizing
#-0.003875969     1.0000000
# check unique values in normalised data
u = unique(df$ratioDUET) # 323
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# Run this section if rounding is to be used
# specify number for rounding
n = 3
df$ratioDUETR = round(df$ratioDUET, n)  # 335, 40
u = unique(df$ratioDUETR) # 287
# create an extra column called group which contains the "gp name and score"
# so colours can be generated for each unique values in this column
my_grp = df$ratioDUETR
df$group <- paste0(df$DUET_outcome, "_", my_grp, sep = "")  # 335,41
# Call the function to create the palette based on the group defined above
colours <- ColourPalleteMulti(df, "DUET_outcome", "my_grp")
my_title = "Protein stability (DUET)"
library(ggplot2)
# axis label size
my_xaxls = 13
my_yaxls = 15
# axes text size
my_xaxts = 15
my_yaxts = 15
# no ordering of x-axis according to frequency
g = ggplot(df, aes(factor(Position, ordered = T)))
g +
geom_bar(aes(fill = group), colour = "grey") +
scale_fill_manual( values = colours
, guide = 'none') +
theme( axis.text.x = element_text(size = my_xaxls
, angle = 90
, hjust = 1
, vjust = 0.4)
, axis.text.y = element_text(size = my_yaxls
, angle = 0
, hjust = 1
, vjust = 0)
, axis.title.x = element_text(size = my_xaxts)
, axis.title.y = element_text(size = my_yaxts ) ) +
labs(title = my_title
, x = "Position"
, y = "Frequency")
class(df$lab_bg)
# make this a named vector
# define cartesian coord
my_xlim = length(unique(df$Position)); my_xlim
# axis label size
my_xals = 15
my_yals = 15
# axes text size
my_xats = 15
my_yats = 18
# using geom_tile
g = ggplot(df, aes(factor(Position, ordered = T)))
g +
coord_cartesian(xlim = c(1, my_xlim)
, ylim = c(0, 6)
, clip = "off") +
geom_bar(aes(fill = group), colour = "grey") +
scale_fill_manual( values = colours
, guide = 'none') +
geom_tile(aes(,-0.8, width = 0.9, height = 0.85)
, fill = df$lab_bg) +
geom_tile(aes(,-1.2, width = 0.9, height = -0.2)
, fill = df$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 = my_title
, x = "Position"
, y = "Frequency")
class(df$lab_bg)
# make this a named vector
# define cartesian coord
my_xlim = length(unique(df$Position)); my_xlim
# axis label size
my_xals = 18
my_yals = 18
# axes text size
my_xats = 14
my_yats = 18
my_plot_name = "barplot_PS_acoloured.svg"
out_file = paste0(out_dir, "/", my_plot_name); outfile
svg(outfile, width = 26, height = 4)
svg(out_file, width = 26, height = 4)
# using geom_tile
g = ggplot(df, aes(factor(Position, ordered = T)))
outFile = g +
coord_cartesian(xlim = c(1, my_xlim)
, ylim = c(0, 6)
, clip = "off"
) +
geom_bar(aes(fill = group), colour = "grey") +
scale_fill_manual( values = colours
, guide = 'none') +
#  geom_tile(aes(,-0.6, width = 0.9, height = 0.7)
#            , fill = df$lab_bg) +
#  geom_tile(aes(,-1, width = 0.9, height = 0.3)
#            , fill = df$lab_bg2) +
geom_tile(aes(,-0.8, width = 0.9, height = 0.85)
, fill = df$lab_bg) +
geom_tile(aes(,-1.2, width = 0.9, height = -0.2)
, fill = df$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(outFile)
dev.off()