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output corr plots with coloured dots

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Tanushree Tunstall 2020-10-06 17:47:24 +01:00
parent 9d2d6cfd84
commit e60b4c5492
1 changed files with 24 additions and 141 deletions
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165
scripts/plotting/corr_PS_LIG.R
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@ -14,7 +14,7 @@ getwd()
source("Header_TT.R") source("Header_TT.R")
require(cowplot) require(cowplot)
source("combining_dfs_plotting.R") source("combining_dfs_plotting.R")
source("my_pairs_panel.R") # with lower panel turned off
# should return the following dfs, directories and variables # should return the following dfs, directories and variables
# PS combined: # PS combined:
@ -51,84 +51,29 @@ cat(paste0("Variables imported:"
#======= #=======
# output # output
#======= #=======
# can't combine by cowplot because not ggplots
#corr_plot_combined = "corr_combined.svg"
#plot_corr_plot_combined = paste0(plotdir,"/", corr_plot_combined)
# PS # PS
corr_ps = "corr_PS.svg" corr_ps = "corr_PS.svg"
plot_corr_ps = paste0(plotdir,"/", corr_ps) plot_corr_ps = paste0(plotdir,"/", corr_ps)
corr_ps_duet_col = "corr_PS_duet_coloured.svg"
plot_corr_ps_duet_col = paste0(plotdir,"/", corr_ps_duet_col)
corr_upper_ps = "corr_upper_PS.svg"
plot_corr_upper_ps = paste0(plotdir,"/", corr_upper_ps)
# LIG # LIG
corr_lig = "corr_LIG.svg" corr_lig = "corr_LIG.svg"
plot_corr_lig = paste0(plotdir,"/", corr_lig) plot_corr_lig = paste0(plotdir,"/", corr_lig)
corr_upper_lig = "corr_upper_LIG.svg"
plot_corr_upper_lig = paste0(plotdir,"/", corr_upper_lig)
#################################################################### ####################################################################
# end of loading libraries and functions # # end of loading libraries and functions #
######################################################################## ########################################################################
#%%%%%%%%%%%%%%%%%%%%%%%%% #%%%%%%%%%%%%%%%%%%%%%%%%%
df_ps = merged_df3_comp df_ps = merged_df3
df_lig = merged_df3_comp_lig df_lig = merged_df3_lig
#%%%%%%%%%%%%%%%%%%%%%%%%% #%%%%%%%%%%%%%%%%%%%%%%%%%
rm( merged_df2, merged_df2_comp, merged_df2_lig, merged_df2_comp_lig, my_df_u, my_df_u_lig) rm( merged_df2, merged_df2_comp, merged_df2_lig, merged_df2_comp_lig, my_df_u, my_df_u_lig)
########################################################################
# end of data extraction and cleaning for plots #
######################################################################## ########################################################################
#============================ ################################
# adding foldx scaled values # Data for Correlation plots: PS
# scale data b/w -1 and 1 #################################
#============================
n = which(colnames(df_ps) == "ddg"); n
my_min = min(df_ps[,n]); my_min
my_max = max(df_ps[,n]); my_max
df_ps$foldx_scaled = ifelse(df_ps[,n] < 0
, df_ps[,n]/abs(my_min)
, df_ps[,n]/my_max)
# sanity check
my_min = min(df_ps$foldx_scaled); my_min
my_max = max(df_ps$foldx_scaled); my_max
if (my_min == -1 && my_max == 1){
cat("PASS: foldx ddg successfully scaled b/w -1 and 1"
, "\nProceeding with assigning foldx outcome category")
}else{
cat("FAIL: could not scale foldx ddg values"
, "Aborting!")
}
#================================
# adding foldx outcome category
# ddg<0 = "Stabilising" (-ve)
#=================================
c1 = table(df_ps$ddg < 0)
df_ps$foldx_outcome = ifelse(df_ps$ddg < 0, "Stabilising", "Destabilising")
c2 = table(df_ps$ddg < 0)
if ( all(c1 == c2) ){
cat("PASS: foldx outcome successfully created")
}else{
cat("FAIL: foldx outcome could not be created. Aborting!")
exit()
}
table(df_ps$foldx_outcome)
#====================== #======================
# adding log cols # adding log cols
@ -160,9 +105,6 @@ corr_data_ps = df_ps[cols_to_select]
dim(corr_data_ps) dim(corr_data_ps)
#p_italic = substitute(paste("-Log(", italic('P'), ")"));p_italic
#p_adjusted_italic = substitute(paste("-Log(", italic('P adjusted'), ")"));p_adjusted_italic
# assign nice colnames (for display) # assign nice colnames (for display)
my_corr_colnames = c("DUET" my_corr_colnames = c("DUET"
@ -171,7 +113,7 @@ my_corr_colnames = c("DUET"
, "Log (OR)" , "Log (OR)"
, "-Log (P)" , "-Log (P)"
, "AF" , "MAF"
, "duet_outcome" , "duet_outcome"
, drug) , drug)
@ -194,15 +136,12 @@ head(my_corr_ps)
# deep red: #ae301e # deep red: #ae301e
#--------------------------------------- #---------------------------------------
# generate corr PS plot 1: both panels # generate corr PS plot: both panels
#--------------------------------------- #---------------------------------------
cat("Corr plot PS DUET with coloured dots:", plot_corr_ps) cat("Corr plot PS DUET with coloured dots:", plot_corr_ps)
svg(plot_corr_ps, width = 15, height = 15) svg(plot_corr_ps, width = 15, height = 15)
#cat("Corr plot PS DUET with coloured dots:",plot_corr_ps_duet_col) pairs.panels(my_corr_ps[1:(length(my_corr_ps)-1)]
#svg(plot_corr_ps_duet_col, width = 15, height = 15)
OutPlot1 = pairs.panels(my_corr_ps[1:(length(my_corr_ps)-1)]
, method = "spearman" # correlation method , method = "spearman" # correlation method
, hist.col = "grey" ##00AFBB , hist.col = "grey" ##00AFBB
, density = TRUE # show density plots , density = TRUE # show density plots
@ -211,12 +150,10 @@ OutPlot1 = pairs.panels(my_corr_ps[1:(length(my_corr_ps)-1)]
, rug = F , rug = F
, breaks = "Sturges" , breaks = "Sturges"
, show.points = T , show.points = T
#, bg = c("#f8766d", "#00bfc4")[unclass(factor(my_corr_ps$duet_outcome))] # can't use colour as duet and foldx are opposite , bg = c("#f8766d", "#00bfc4")[unclass(factor(my_corr_ps$duet_outcome))] # foldx colours are reveresed
#, pch = 21 # for bg , pch = 21 # for bg
, pch = 19
, jitter = T , jitter = T
, alpha = 1 , alpha = 1
#, points(pch = 19, col = c("#f8766d", "#00bfc4"))
, cex = 1.8 , cex = 1.8
, cex.axis = 2 , cex.axis = 2
, cex.labels = 4 , cex.labels = 4
@ -225,40 +162,15 @@ OutPlot1 = pairs.panels(my_corr_ps[1:(length(my_corr_ps)-1)]
) )
print(OutPlot1)
dev.off() dev.off()
corr_ps_rho = corr.test(my_corr_ps[1:5], method = "spearman")$r
#---------------------------------------------- corr_ps_p = corr.test(my_corr_ps[1:5], method = "spearman")$p
# generate corr PS plot 2: upper_panel only
#----------------------------------------------
cat("Corr plot upper PS:", plot_corr_upper_ps)
svg(plot_corr_upper_ps, width = 15, height = 15)
OutPlot1_upper = my_pp(my_corr_ps[1:(length(my_corr_ps)-1)] # no lower panel
, method = "spearman" # correlation method
, hist.col = "grey" ##00AFBB
, density = TRUE # show density plots
, ellipses = F # show correlation ellipses
, stars = T
, rug = F
, breaks = "Sturges"
, show.points = F
, cex = 3
, cex.axis = 1.6
, cex.labels = 4
, cex.cor = 1
, smooth = F
)
print(OutPlot1_upper)
dev.off()
################################################################################################ ################################################################################################
#=========================== ###################################
# Data for Correlation plots: LIG # Data for Correlation plots: LIG
#=========================== ##################################
table(df_lig$ligand_outcome) table(df_lig$ligand_outcome)
df_lig$log10_or_mychisq = log10(df_lig$or_mychisq) df_lig$log10_or_mychisq = log10(df_lig$or_mychisq)
@ -289,7 +201,7 @@ my_corr_colnames = c("Ligand Affinity"
, "Log (OR)" , "Log (OR)"
, "-Log (P)" , "-Log (P)"
, "AF" , "MAF"
, "ligand_outcome" , "ligand_outcome"
, drug) , drug)
@ -308,13 +220,13 @@ my_corr_lig = corr_data_lig[start:(end-offset)]
head(my_corr_lig) head(my_corr_lig)
#--------------------------------------- #---------------------------------------
# generate corr LIG plot 1: both panels # generate corr LIG plot: both panels
#--------------------------------------- #---------------------------------------
cat("Corr LIG plot:", plot_corr_lig) cat("Corr LIG plot:", plot_corr_lig)
svg(plot_corr_lig, width = 15, height = 15) svg(plot_corr_lig, width = 15, height = 15)
# uncomment as necessary # uncomment as necessary
OutPlot2 = pairs.panels(my_corr_lig[1:(length(my_corr_lig)-1)] pairs.panels(my_corr_lig[1:(length(my_corr_lig)-1)]
, method = "spearman" # correlation method , method = "spearman" # correlation method
, hist.col = "grey" ##00AFBB , hist.col = "grey" ##00AFBB
, density = TRUE # show density plots , density = TRUE # show density plots
@ -323,12 +235,9 @@ OutPlot2 = pairs.panels(my_corr_lig[1:(length(my_corr_lig)-1)]
, rug = F , rug = F
, breaks = "Sturges" , breaks = "Sturges"
, show.points = T , show.points = T
#, bg = c("#f8766d", "#00bfc4")[unclass(factor(my_corr_lig$ligand_outcome))] # can't use colour as duet and foldx are opposite , bg = c("#f8766d", "#00bfc4")[unclass(factor(my_corr_lig$ligand_outcome))]
#, pch = 21 # for bg , pch = 21 # for bg
, pch = 19
, jitter = T , jitter = T
#, alpha = .05
#, points(pch = 19, col = c("#f8766d", "#00bfc4"))
, cex = 2 , cex = 2
, cex.axis = 2 , cex.axis = 2
, cex.labels = 4 , cex.labels = 4
@ -336,35 +245,9 @@ OutPlot2 = pairs.panels(my_corr_lig[1:(length(my_corr_lig)-1)]
, smooth = F , smooth = F
) )
print(OutPlot2)
dev.off()
#---------------------------------------
# generate corr LIG plot 2: upper panels
#---------------------------------------
cat("Corr LIG plot:", plot_corr_upper_lig)
svg(plot_corr_upper_lig, width = 15, height = 15)
# uncomment as necessary
OutPlot2_upper = my_pp(my_corr_lig[1:(length(my_corr_lig)-1)]
, method = "spearman" # correlation method
, hist.col = "grey" ##00AFBB
, density = TRUE # show density plots
, ellipses = F # show correlation ellipses
, stars = T
, rug = F
, breaks = "Sturges"
, show.points = F
#, alpha = .05
#, points(pch = 19, col = c("#f8766d", "#00bfc4"))
, cex = 3
, cex.axis = 1.6
, cex.labels = 4
, cex.cor = 1
, smooth = F
)
print(OutPlot2_upper)
dev.off() dev.off()
corr_lig_rho = corr.test(my_corr_lig[1:4], method = "spearman")$r
corr_lig_p = corr.test(my_corr_lig[1:4], method = "spearman")$p
####################################################### #######################################################