406 lines
14 KiB
R
Executable file
406 lines
14 KiB
R
Executable file
#!/usr/bin/env Rscript
|
|
#########################################################
|
|
# TASK: Barplots for mCSM DUET, ligand affinity, and foldX
|
|
# basic barplots with count of mutations
|
|
# basic barplots with frequency of count of mutations
|
|
|
|
# , df_colname = ""
|
|
# , leg_title = ""
|
|
# , ats = 25 # axis text size
|
|
# , als = 22 # axis label size
|
|
# , lts = 20 # legend text size
|
|
# , ltis = 22 # label title size
|
|
# , geom_ls = 10 # geom_label size
|
|
# , yaxis_title = "Number of nsSNPs"
|
|
# , bp_plot_title = ""
|
|
# , label_categories = c("Destabilising", "Stabilising")
|
|
# , title_colour = "chocolate4"
|
|
# , subtitle_text = NULL
|
|
# , sts = 20
|
|
# , subtitle_colour = "pink"
|
|
# #, leg_position = c(0.73,0.8) # within plot area
|
|
# , leg_position = "top"
|
|
# , bar_fill_values = c("#F8766D", "#00BFC4")
|
|
#########################################################
|
|
|
|
#=======================================================================
|
|
#=======
|
|
# output
|
|
#=======
|
|
outdir_images = paste0("~/git/Writing/thesis/images/results/"
|
|
, tolower(gene), "/")
|
|
cat("plots will output to:", outdir_images)
|
|
|
|
###########################################################
|
|
df3 = merged_df3
|
|
# FIXME: port to a common script
|
|
#=================
|
|
# PREFORMATTING: for consistency
|
|
#=================
|
|
df3$sensitivity = ifelse(df3$dst_mode == 1, "R", "S")
|
|
table(df3$sensitivity)
|
|
|
|
# ConSurf labels
|
|
consurf_colOld = "consurf_colour_rev"
|
|
consurf_colNew = "consurf_outcome"
|
|
df3[[consurf_colNew]] = df3[[consurf_colOld]]
|
|
df3[[consurf_colNew]] = as.factor(df3[[consurf_colNew]])
|
|
df3[[consurf_colNew]]
|
|
levels(df3$consurf_outcome) = c( "nsd", 1, 2, 3, 4, 5, 6, 7, 8, 9)
|
|
levels(df3$consurf_outcome)
|
|
|
|
# SNAP2 labels
|
|
snap2_colname = "snap2_outcome"
|
|
df3[[snap2_colname]] <- str_replace(df3[[snap2_colname]], "effect", "Effect")
|
|
df3[[snap2_colname]] <- str_replace(df3[[snap2_colname]], "neutral", "Neutral")
|
|
|
|
##############################################################
|
|
gene_all_cols = colnames(df3)[colnames(df3)%in%all_cols]
|
|
|
|
gene_outcome_cols = colnames(df3)[colnames(df3)%in%c(outcome_cols_stability
|
|
, outcome_cols_affinity
|
|
, outcome_cols_conservation)]
|
|
gene_outcome_cols
|
|
|
|
|
|
#=======================================================================
|
|
#------------------------------
|
|
# stability barplots:
|
|
outcome_cols_stability
|
|
# label_categories should be = levels(as.factor(plot_df[[df_colname]]))
|
|
#------------------------------
|
|
sts = 22
|
|
subtitle_colour = "black"
|
|
geom_ls = 10
|
|
|
|
# duetP
|
|
duetP = stability_count_bp(plotdf = df3
|
|
, df_colname = "duet_outcome"
|
|
, leg_title = "mCSM-DUET"
|
|
#, label_categories = labels_duet
|
|
, yaxis_title = "Number of nsSNPs"
|
|
, leg_position = "none"
|
|
, subtitle_text = "mCSM-DUET"
|
|
, geom_ls = geom_ls
|
|
, bar_fill_values = c("#F8766D", "#00BFC4")
|
|
, sts = sts
|
|
, subtitle_colour= subtitle_colour)
|
|
|
|
# foldx
|
|
foldxP = stability_count_bp(plotdf = df3
|
|
, df_colname = "foldx_outcome"
|
|
#, leg_title = "FoldX"
|
|
#, label_categories = labels_foldx
|
|
, yaxis_title = ""
|
|
, leg_position = "none"
|
|
, subtitle_text = "FoldX"
|
|
, geom_ls = geom_ls
|
|
, bar_fill_values = c("#F8766D", "#00BFC4")
|
|
, sts = sts
|
|
, subtitle_colour= subtitle_colour)
|
|
|
|
|
|
# deepddg
|
|
deepddgP = stability_count_bp(plotdf = df3
|
|
, df_colname = "deepddg_outcome"
|
|
#, leg_title = "DeepDDG"
|
|
#, label_categories = labels_deepddg
|
|
, yaxis_title = "Number of nsSNPs"
|
|
, leg_position = "none"
|
|
, subtitle_text = "DeepDDG"
|
|
, geom_ls = geom_ls
|
|
, bar_fill_values = c("#F8766D", "#00BFC4")
|
|
, sts = sts
|
|
, subtitle_colour= subtitle_colour)
|
|
|
|
|
|
# deepddg
|
|
dynamut2P = stability_count_bp(plotdf = df3
|
|
, df_colname = "ddg_dynamut2_outcome"
|
|
#, leg_title = "Dynamut2"
|
|
#, label_categories = labels_ddg_dynamut2_outcome
|
|
, yaxis_title = ""
|
|
, leg_position = "none"
|
|
, subtitle_text = "Dynamut2"
|
|
, geom_ls = geom_ls
|
|
, bar_fill_values = c("#F8766D", "#00BFC4")
|
|
, sts = sts
|
|
, subtitle_colour= subtitle_colour)
|
|
|
|
dynamut2P
|
|
|
|
# extract common legend
|
|
common_legend = get_legend(duetP +
|
|
guides(color = guide_legend(nrow = 1)) +
|
|
theme(legend.position = "top"))
|
|
|
|
#==========================
|
|
# output: STABILITY PLOTS
|
|
#===========================
|
|
bp_stability_CLP = paste0(outdir_images
|
|
, tolower(gene)
|
|
,"_bp_stability_CL.svg")
|
|
|
|
svg(bp_stability_CLP, width = 15, height = 12)
|
|
print(paste0("plot filename:", bp_stability_CLP))
|
|
|
|
cowplot::plot_grid(
|
|
common_legend,
|
|
cowplot::plot_grid(duetP, foldxP
|
|
, deepddgP, dynamut2P
|
|
, nrow = 2
|
|
, ncol = 2
|
|
#, labels = c("(a)", "(b)", "(c)", "(d)")
|
|
, labels = "AUTO"
|
|
, label_size = 25)
|
|
, ncol = 1
|
|
, nrow = 2
|
|
, rel_heights = c(0.4/10,9/10))
|
|
|
|
dev.off()
|
|
###########################################################
|
|
#=========================
|
|
# Affinity outcome
|
|
# check this var: outcome_cols_affinity
|
|
# get from preformatting or put in globals
|
|
#==========================
|
|
DistCutOff = 10
|
|
LigDist_colname # = "ligand_distance" # from globals
|
|
ppi2Dist_colname = "interface_dist"
|
|
naDist_colname = "TBC"
|
|
|
|
###########################################################
|
|
# get plotting data within the distance
|
|
df3_lig = df3[df3[[LigDist_colname]]<DistCutOff,]
|
|
df3_ppi2 = df3[df3[[ppi2Dist_colname]]<DistCutOff,]
|
|
df3_na = df3[df3[[naDist_colname]]<DistCutOff,]
|
|
common_bp_title = paste0("Sites <", DistCutOff, angstroms_symbol)
|
|
|
|
#------------------------------
|
|
# barplot for ligand affinity:
|
|
# <10 Ang of ligand
|
|
#------------------------------
|
|
mLigP = stability_count_bp(plotdf = df3_lig
|
|
, df_colname = "ligand_outcome"
|
|
#, leg_title = "mCSM-lig"
|
|
#, label_categories = labels_lig
|
|
, yaxis_title = "Number of nsSNPs"
|
|
, leg_position = "none"
|
|
, subtitle_text = "mCSM-lig"
|
|
, geom_ls = geom_ls
|
|
, bar_fill_values = c("#F8766D", "#00BFC4")
|
|
, sts = sts
|
|
, subtitle_colour= subtitle_colour
|
|
, bp_plot_title = paste(common_bp_title, "ligand")
|
|
)
|
|
|
|
#------------------------------
|
|
# barplot for ligand affinity:
|
|
# <10 Ang of ligand
|
|
# mmCSM-lig: will be the same no. of sites but the effect will be different
|
|
#------------------------------
|
|
mmLigP = stability_count_bp(plotdf = df3_lig
|
|
, df_colname = "mmcsm_lig_outcome"
|
|
#, leg_title = "mmCSM-lig"
|
|
#, label_categories = labels_mmlig
|
|
, yaxis_title = ""
|
|
, leg_position = "none"
|
|
, subtitle_text = "mmCSM-lig"
|
|
, geom_ls = geom_ls
|
|
, bar_fill_values = c("#F8766D", "#00BFC4")
|
|
, sts = sts
|
|
, subtitle_colour= subtitle_colour
|
|
, bp_plot_title = paste(common_bp_title, "ligand")
|
|
)
|
|
|
|
#------------------------------
|
|
# barplot for ppi2 affinity
|
|
# <10 Ang of interface
|
|
#------------------------------
|
|
ppi2P = stability_count_bp(plotdf = df3_ppi2
|
|
, df_colname = "mcsm_ppi2_outcome"
|
|
#, leg_title = "mCSM-ppi2"
|
|
#, label_categories = labels_ppi2
|
|
, yaxis_title = ""
|
|
, leg_position = "none"
|
|
, subtitle_text = "mCSM-ppi2"
|
|
, geom_ls = geom_ls
|
|
, bar_fill_values = c("#F8766D", "#00BFC4")
|
|
, sts = sts
|
|
, subtitle_colour= subtitle_colour
|
|
, bp_plot_title = paste(common_bp_title, "interface")
|
|
)
|
|
|
|
# extract common legend
|
|
common_legend_aff = get_legend(mLigP +
|
|
guides(color = guide_legend(nrow = 1)) +
|
|
theme(legend.position = "top"))
|
|
|
|
#==========================
|
|
# output: AFFINITY PLOTS
|
|
#==========================
|
|
bp_affinity_CLP = paste0(outdir_images
|
|
,tolower(gene)
|
|
,"_bp_affinity_CL.svg" )
|
|
|
|
print(paste0("plot filename:", bp_stability_CLP))
|
|
svg(bp_affinity_CLP, width = 15, height = 6.5)
|
|
|
|
cowplot::plot_grid(
|
|
common_legend,
|
|
cowplot::plot_grid(mLigP, mmLigP
|
|
, ppi2P
|
|
, nrow = 1
|
|
, ncol = 3
|
|
#, labels = c("(a)", "(b)", "(c)", "(d)")
|
|
, labels = "AUTO"
|
|
, label_size = 25)
|
|
, ncol = 1
|
|
, nrow = 2
|
|
, rel_heights = c(0.4/10,9/10))
|
|
#, rel_widths = c(1,1,1))
|
|
|
|
|
|
dev.off()
|
|
|
|
################################################################
|
|
#=========================
|
|
# Conservation outcome
|
|
# check this var:
|
|
outcome_cols_conservation
|
|
#==========================
|
|
# provean
|
|
proveanP = stability_count_bp(plotdf = df3
|
|
, df_colname = "provean_outcome"
|
|
#, leg_title = "PROVEAN"
|
|
#, label_categories = labels_provean
|
|
, yaxis_title = ""
|
|
, leg_position = "top"
|
|
, subtitle_text = "PROVEAN"
|
|
, geom_ls = geom_ls
|
|
, bar_fill_values = c("#F8766D", "#00BFC4")
|
|
, sts = sts
|
|
, subtitle_colour= subtitle_colour)
|
|
|
|
|
|
# snap2
|
|
snap2P = stability_count_bp(plotdf = df3
|
|
, df_colname = "snap2_outcome"
|
|
#, leg_title = "SNAP2"
|
|
#, label_categories = labels_snap2
|
|
, yaxis_title = "Number of nsSNPs"
|
|
, leg_position = "top"
|
|
, subtitle_text = "SNAP2"
|
|
, geom_ls = geom_ls
|
|
, bar_fill_values = c("#F8766D", "#00BFC4")
|
|
, sts = sts
|
|
, subtitle_colour= subtitle_colour)
|
|
|
|
# consurf
|
|
consurfP = stability_count_bp(plotdf = df3
|
|
, df_colname = "consurf_outcome"
|
|
#, leg_title = "ConSurf"
|
|
#, label_categories = labels_consurf
|
|
, yaxis_title = ""
|
|
, leg_position = "top"
|
|
, subtitle_text = "ConSurf"
|
|
, geom_ls = 5
|
|
, bar_fill_values = consurf_colours # from globals
|
|
, sts = sts
|
|
, subtitle_colour= subtitle_colour)
|
|
|
|
consurfP
|
|
#============================
|
|
# output: CONSERVATION PLOTS
|
|
#============================
|
|
bp_conservation_CLP = paste0(outdir_images
|
|
,tolower(gene)
|
|
,"_bp_conservation_CL.svg" )
|
|
|
|
print(paste0("plot filename:", bp_conservation_CLP))
|
|
svg(bp_conservation_CLP, width = 15, height = 6.5)
|
|
|
|
cowplot::plot_grid(proveanP, snap2P, consurfP
|
|
, nrow = 1
|
|
, ncol = 3
|
|
#, labels = c("(a)", "(b)", "(c)", "(d)")
|
|
, labels = "AUTO"
|
|
, label_size = 25
|
|
#, rel_heights = c(0.4/10,9/10))
|
|
, rel_widths = c(0.9, 0.9, 1.1))
|
|
|
|
|
|
dev.off()
|
|
|
|
#####################################################################
|
|
#===============================================================
|
|
# ------------------------------
|
|
# bp site site count: ALL
|
|
# <10 Ang ligand
|
|
# ------------------------------
|
|
posC_all = site_snp_count_bp(plotdf = df3
|
|
, df_colname = "position"
|
|
, xaxis_title = ""
|
|
, yaxis_title = "Number of Sites"
|
|
, subtitle_size = 20)
|
|
|
|
|
|
# ------------------------------
|
|
# bp site site count: mCSM-lig
|
|
# < 10 Ang ligand
|
|
# ------------------------------
|
|
common_bp_title = paste0("Sites <", DistCutOff, angstroms_symbol)
|
|
|
|
posC_lig = site_snp_count_bp(plotdf = df3_lig
|
|
, df_colname = "position"
|
|
, xaxis_title = "Number of nsSNPs"
|
|
, yaxis_title = "" #+ annotate("text", x = 1.5, y = 2.2, label = "Text No. 1")
|
|
|
|
, subtitle_text = paste0(common_bp_title, " ligand")
|
|
, subtitle_size = 20
|
|
, subtitle_colour = subtitle_colour)
|
|
# ------------------------------
|
|
# bp site site count: ppi2
|
|
# < 10 Ang interface
|
|
# ------------------------------
|
|
|
|
posC_ppi2 = site_snp_count_bp(plotdf = df3_ppi2
|
|
, df_colname = "position"
|
|
, xaxis_title = ""
|
|
, yaxis_title = ""
|
|
, subtitle_text = paste0(common_bp_title, " interface")
|
|
, subtitle_size = 20
|
|
, subtitle_colour = subtitle_colour)
|
|
|
|
# ------------------------------
|
|
#FIXME: bp site site count: na
|
|
# < 10 Ang TBC
|
|
# ------------------------------
|
|
# posC_na = site_snp_count_bp(plotdf = df3_na
|
|
# , df_colname = "position"
|
|
# , xaxis_title = ""
|
|
# , yaxis_title = "")
|
|
|
|
|
|
#===========================
|
|
# output: SITE SNP count:
|
|
# all + affinity
|
|
#==========================
|
|
pos_count_combined_CLP = paste0(outdir_images
|
|
,tolower(gene)
|
|
,"_pos_count_PS_AFF.svg")
|
|
|
|
|
|
svg(pos_count_combined_CLP, width = 15, height = 6.5)
|
|
print(paste0("plot filename:", pos_count_combined_CLP))
|
|
|
|
cowplot::plot_grid(posC_all, posC_lig, posC_ppi2
|
|
#, posC_na
|
|
, nrow = 1
|
|
, ncol = 3
|
|
#, labels = c("(a)", "(b)", "(c)", "(d)")
|
|
, labels = "AUTO"
|
|
, label_size = 25)
|
|
|
|
dev.off()
|
|
#===============================================================
|