added script for coloured axis for ligand affinity
This commit is contained in:
parent
c5d47c1a18
commit
12c24d974e
1 changed files with 296 additions and 0 deletions
|
|
@ -0,0 +1,296 @@
|
||||||
|
getwd()
|
||||||
|
setwd("~/git/LSHTM_analysis/mcsm_analysis/pyrazinamide/scripts/plotting")
|
||||||
|
getwd()
|
||||||
|
|
||||||
|
############################################################
|
||||||
|
# 1: Installing and loading required packages and functions
|
||||||
|
############################################################
|
||||||
|
|
||||||
|
source("../Header_TT.R")
|
||||||
|
source("../barplot_colour_function.R")
|
||||||
|
|
||||||
|
############################################################
|
||||||
|
# Output dir for plots
|
||||||
|
############################################################
|
||||||
|
out_dir = "~/git/Data/pyrazinamide/output/plots"
|
||||||
|
|
||||||
|
############################################################
|
||||||
|
# 2: call script the prepares the data with columns containing
|
||||||
|
# colours for axis labels
|
||||||
|
############################################################
|
||||||
|
|
||||||
|
source("subcols_axis_LIG.R")
|
||||||
|
|
||||||
|
# this should return
|
||||||
|
#mut_pos_cols: 52, 4
|
||||||
|
#my_df: 169, 39
|
||||||
|
|
||||||
|
# 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!: should be the length of the unique positions
|
||||||
|
my_axis_colours = mut_pos_cols$lab_fg
|
||||||
|
|
||||||
|
# now clear mut_pos_cols
|
||||||
|
rm(mut_pos_cols)
|
||||||
|
|
||||||
|
###########################
|
||||||
|
# 2: Plot: Lig scores
|
||||||
|
###########################
|
||||||
|
#==========================
|
||||||
|
# Plot 2: Barplot with scores (unordered)
|
||||||
|
# corresponds to Lig_outcome
|
||||||
|
# Stacked Barplot with colours: Lig_outcome @ position coloured by
|
||||||
|
# stability scores. This is a barplot where each bar corresponds
|
||||||
|
# to a SNP and is coloured by its corresponding PredAff stability value.
|
||||||
|
# Normalised values (range between -1 and 1 ) to aid visualisation
|
||||||
|
# NOTE: since barplot plots discrete values, colour = score, so number of
|
||||||
|
# colours will be equal to the no. of unique normalised scores
|
||||||
|
# rather than a continuous scale
|
||||||
|
# will require generating the colour scale separately.
|
||||||
|
#============================
|
||||||
|
# sanity checks
|
||||||
|
upos = unique(my_df$Position)
|
||||||
|
|
||||||
|
str(my_df$Lig_outcome)
|
||||||
|
|
||||||
|
colnames(my_df)
|
||||||
|
|
||||||
|
#===========================
|
||||||
|
# Data preparation for plots
|
||||||
|
#===========================
|
||||||
|
#!!!!!!!!!!!!!!!!!
|
||||||
|
# REASSIGNMENT
|
||||||
|
df <- my_df
|
||||||
|
#!!!!!!!!!!!!!!!!!
|
||||||
|
|
||||||
|
rm(my_df)
|
||||||
|
|
||||||
|
# sanity checks
|
||||||
|
# should be a factor
|
||||||
|
is.factor(df$Lig_outcome);
|
||||||
|
#FALSE
|
||||||
|
|
||||||
|
df$Lig_outcome = as.factor(df$Lig_outcome)
|
||||||
|
is.factor(df$Lig_outcome);
|
||||||
|
#TRUE
|
||||||
|
|
||||||
|
table(df$Lig_outcome)
|
||||||
|
|
||||||
|
# check the range
|
||||||
|
min(df$ratioPredAff)
|
||||||
|
max(df$ratioPredAff)
|
||||||
|
|
||||||
|
# sanity checks
|
||||||
|
# very important!!!!
|
||||||
|
tapply(df$ratioPredAff, df$Lig_outcome, min)
|
||||||
|
|
||||||
|
tapply(df$ratioPredAff, df$Lig_outcome, max)
|
||||||
|
|
||||||
|
# My colour FUNCTION: based on group and subgroup
|
||||||
|
# in my case;
|
||||||
|
# df = df
|
||||||
|
# group = Lig_outcome
|
||||||
|
# subgroup = normalised score i.e ratioPredAff
|
||||||
|
|
||||||
|
# Prepare data: round off ratioPredAff scores
|
||||||
|
# round off to 3 significant digits:
|
||||||
|
# 323 if no rounding is performed: used to generate the original graph
|
||||||
|
# 287 if rounded to 3 places
|
||||||
|
# FIXME: check if reducing precicion creates any ML prob
|
||||||
|
|
||||||
|
# check unique values in normalised data
|
||||||
|
u = unique(df$ratioPredAff)
|
||||||
|
|
||||||
|
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||||
|
# Run this section if rounding is to be used
|
||||||
|
# specify number for rounding
|
||||||
|
n = 3
|
||||||
|
df$ratioPredAffR = round(df$ratioPredAff, n)
|
||||||
|
u = unique(df$ratioPredAffR)
|
||||||
|
|
||||||
|
# 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$ratioPredAffR
|
||||||
|
df$group <- paste0(df$Lig_outcome, "_", my_grp, sep = "")
|
||||||
|
|
||||||
|
# ELSE
|
||||||
|
# uncomment the below if rounding is not required
|
||||||
|
|
||||||
|
#my_grp = df$ratioPredAff
|
||||||
|
#df$group <- paste0(df$Lig_outcome, "_", my_grp, sep = "")
|
||||||
|
|
||||||
|
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||||
|
|
||||||
|
#******************
|
||||||
|
# generate plot
|
||||||
|
#******************
|
||||||
|
|
||||||
|
# Call the function to create the palette based on the group defined above
|
||||||
|
colours <- ColourPalleteMulti(df, "Lig_outcome", "my_grp")
|
||||||
|
my_title = "Ligand Affinity"
|
||||||
|
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")
|
||||||
|
|
||||||
|
#========================
|
||||||
|
# plot with axis colours
|
||||||
|
#========================
|
||||||
|
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 = 0.95, 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 = my_title
|
||||||
|
, x = "Position"
|
||||||
|
, y = "Frequency")
|
||||||
|
|
||||||
|
#========================
|
||||||
|
# output plot as svg/png
|
||||||
|
#========================
|
||||||
|
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 = 16 #14 in PS
|
||||||
|
my_yats = 18
|
||||||
|
|
||||||
|
# set output dir for plots
|
||||||
|
#getwd()
|
||||||
|
#setwd("~/git/Data/pyrazinamide/output/plots")
|
||||||
|
#getwd()
|
||||||
|
|
||||||
|
plot_name = "barplot_LIG_acoloured.svg"
|
||||||
|
my_plot_name = paste0(out_dir, "/", plot_name); my_plot_name
|
||||||
|
|
||||||
|
svg(my_plot_name, width = 26, height = 4)
|
||||||
|
|
||||||
|
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 = 0.95, 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(outFile)
|
||||||
|
dev.off()
|
||||||
|
|
||||||
|
# for sanity and good practice
|
||||||
|
#rm(df)
|
||||||
Loading…
Add table
Add a link
Reference in a new issue