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updated corr_PS_LIG.R to output both styles of corr plots

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Tanushree Tunstall 2020-09-17 17:04:03 +01:00
parent ea5d5bda44
commit 883207bc4b
1 changed files with 105 additions and 38 deletions
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111
scripts/plotting/corr_PS_LIG.R
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@ -59,10 +59,16 @@ cat(paste0("Variables imported:"
corr_ps = "corr_PS.svg"
plot_corr_ps = paste0(plotdir,"/", corr_ps)
corr_upper_ps = "corr_upper_PS.svg"
plot_corr_upper_ps = paste0(plotdir,"/", corr_upper_ps)
# LIG
corr_lig = "corr_LIG.svg"
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 #
########################################################################
@ -159,8 +165,8 @@ my_corr_colnames = c("DUET"
, "Foldx"
, "Log(OR)"
, "-Log(P)"
, "Log (OR)"
, "-Log (P)"
, "AF"
@ -173,9 +179,6 @@ colnames(corr_data_ps)
colnames(corr_data_ps) <- my_corr_colnames
colnames(corr_data_ps)
#-----------------
# generate corr PS plot
#-----------------
start = 1
end = which(colnames(corr_data_ps) == drug); end # should be the last column
offset = 1
@ -187,11 +190,14 @@ head(my_corr_ps)
# deep blue :#007d85
# deep red: #ae301e
#---------------------------------------
# generate corr PS plot 1: both panels
#---------------------------------------
cat("Corr plot PS:", plot_corr_ps)
svg(plot_corr_ps, width = 15, height = 15)
#OutPlot1 = pairs.panels([1:(length(my_corr_ps)-1)]
OutPlot1 = my_pp(my_corr_ps[1:(length(my_corr_ps)-1)]
OutPlot1 = pairs.panels(my_corr_ps[1:(length(my_corr_ps)-1)]
, method = "spearman" # correlation method
, hist.col = "grey" ##00AFBB
, density = TRUE # show density plots
@ -206,8 +212,8 @@ OutPlot1 = my_pp(my_corr_ps[1:(length(my_corr_ps)-1)]
#, alpha = .05
#, points(pch = 19, col = c("#f8766d", "#00bfc4"))
, cex = 3
, cex.axis = 1.5
, cex.labels = 2.1
, cex.axis = 2
, cex.labels = 4
, cex.cor = 1
, smooth = F
@ -216,6 +222,39 @@ OutPlot1 = my_pp(my_corr_ps[1:(length(my_corr_ps)-1)]
print(OutPlot1)
dev.off()
#----------------------------------------------
# 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 = T
, bg = c("#f8766d", "#00bfc4")[unclass(factor(my_corr_ps$duet_outcome))]
, pch = 21
, jitter = T
#, alpha = .05
#, points(pch = 19, col = c("#f8766d", "#00bfc4"))
, cex = 3
, cex.axis = 1.6
, cex.labels = 4
, cex.cor = 1
, smooth = F
)
print(OutPlot1_upper)
dev.off()
################################################################################################
#===========================
# Data for Correlation plots: LIG
#===========================
@ -224,11 +263,9 @@ table(df_lig$ligand_outcome)
df_lig$log10_or_mychisq = log10(df_lig$or_mychisq)
df_lig$neglog_pval_fisher = -log10(df_lig$pval_fisher)
df_lig$log10_or_kin = log10(df_lig$or_kin)
df_lig$neglog_pwald_kin = -log10(df_lig$pwald_kin)
# subset data to generate pairwise correlations
cols_to_select = c("affinity_scaled"
@ -248,8 +285,8 @@ dim(corr_data_lig)
# assign nice colnames (for display)
my_corr_colnames = c("Ligand Affinity"
, "Log(OR)"
, "-Log(P)"
, "Log (OR)"
, "-Log (P)"
, "AF"
@ -262,10 +299,6 @@ colnames(corr_data_lig)
colnames(corr_data_lig) <- my_corr_colnames
colnames(corr_data_lig)
#-----------------
# generate corr LIG plot
#-----------------
start = 1
end = which(colnames(corr_data_lig) == drug); end # should be the last column
offset = 1
@ -273,11 +306,14 @@ offset = 1
my_corr_lig = corr_data_lig[start:(end-offset)]
head(my_corr_lig)
#---------------------------------------
# generate corr LIG plot 1: both panels
#---------------------------------------
cat("Corr LIG plot:", plot_corr_lig)
svg(plot_corr_lig, width = 15, height = 15)
#OutPlot2 = pairs.panels(my_corr_lig[1:(length(my_corr_lig)-1)]
OutPlot2 = my_pp(my_corr_lig[1:(length(my_corr_lig)-1)]
# uncomment as necessary
OutPlot2 = pairs.panels(my_corr_lig[1:(length(my_corr_lig)-1)]
, method = "spearman" # correlation method
, hist.col = "grey" ##00AFBB
, density = TRUE # show density plots
@ -292,13 +328,44 @@ OutPlot2 = my_pp(my_corr_lig[1:(length(my_corr_lig)-1)]
#, alpha = .05
#, points(pch = 19, col = c("#f8766d", "#00bfc4"))
, cex = 3
, cex.axis = 1.5
, cex.labels = 2.1
, cex.axis = 2
, cex.labels = 4
, cex.cor = 1
, 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 = T
, bg = c("#f8766d", "#00bfc4")[unclass(factor(my_corr_lig$ligand_outcome))]
, pch = 21
, jitter = T
#, 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()
#######################################################
library(lattice)