363 lines
14 KiB
R
363 lines
14 KiB
R
#!/usr/bin/env Rscript
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#########################################################
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# TASK: Barplots
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# basic barplots with outcome
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# basic barplots with frequency of count of mutations
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#########################################################
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#=============
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# Data: Input
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#==============
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source("~/git/LSHTM_analysis/config/alr.R")
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source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")
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#cat("\nSourced plotting cols as well:", length(plotting_cols))
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####################################################
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class(merged_df3)
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df3 = subset(merged_df3, select = -c(pos_count))
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#=======
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# output
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#=======
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outdir_images = paste0("~/git/Writing/thesis/images/results/", tolower(gene), "/")
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cat("plots will output to:", outdir_images)
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##########################################################
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# blue, red bp
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sts = 8
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lts = 8
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ats = 8
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als = 8
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ltis = 8
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geom_ls = 2.2
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#pos_count
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subtitle_size = 8
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geom_ls_pc = 2.2
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leg_text_size = 8
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axis_text_size = 8
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axis_label_size = 8
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###########################################################
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#------------------------------
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# plot default sizes
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#------------------------------
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#=========================
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# Affinity outcome
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# check this var: outcome_cols_affinity
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# get from preformatting or put in globals
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#==========================
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DistCutOff
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LigDist_colname # = "ligand_distance" # from globals
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ppi2Dist_colname
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naDist_colname
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###########################################################
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# get plotting data within the distance
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df3_lig = df3[df3[[LigDist_colname]]<DistCutOff,]
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df3_ppi2 = df3[df3[[ppi2Dist_colname]]<DistCutOff,]
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df3_na = df3[df3[[naDist_colname]]<DistCutOff,]
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common_bp_title = paste0("Sites <", DistCutOff, angstroms_symbol)
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#------------------------------
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# barplot for ligand affinity:
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# <10 Ang of ligand
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#------------------------------
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mLigP = stability_count_bp(plotdf = df3_lig
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, df_colname = "ligand_outcome"
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#, leg_title = "mCSM-lig"
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#, bp_plot_title = paste(common_bp_title, "ligand")
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, yaxis_title = "Number of nsSNPs"
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, leg_position = "none"
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, subtitle_text = "mCSM\nLig"
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, bar_fill_values = c("#F8766D", "#00BFC4")
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, subtitle_colour= "black"
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, sts = sts
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, lts = lts
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, ats = ats
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, als = als
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, ltis = ltis
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, geom_ls = geom_ls
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)
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mLigP
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#------------------------------
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# barplot for ligand affinity:
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# <10 Ang of ligand
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# mmCSM-lig: will be the same no. of sites but the effect will be different
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#------------------------------
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mmLigP = stability_count_bp(plotdf = df3_lig
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, df_colname = "mmcsm_lig_outcome"
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#, leg_title = "mmCSM-lig"
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#, label_categories = labels_mmlig
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#, bp_plot_title = paste(common_bp_title, "ligand")
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, yaxis_title = ""
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, leg_position = "none"
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, subtitle_text = "mmCSM\nLig"
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, bar_fill_values = c("#F8766D", "#00BFC4")
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, subtitle_colour= "black"
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, sts = sts
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, lts = lts
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, ats = ats
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, als = als
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, ltis = ltis
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, geom_ls = geom_ls
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)
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mmLigP
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#------------------------------
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# barplot for ppi2 affinity
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# <10 Ang of interface
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#------------------------------
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if (tolower(gene)%in%geneL_ppi2){
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ppi2P = stability_count_bp(plotdf = df3_ppi2
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, df_colname = "mcsm_ppi2_outcome"
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#, leg_title = "mCSM-ppi2"
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#, label_categories = labels_ppi2
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#, bp_plot_title = paste(common_bp_title, "PP-interface")
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, yaxis_title = "Number of nsSNPs"
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, leg_position = "none"
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, subtitle_text = "mCSM\nPPI2"
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, bar_fill_values = c("#F8766D", "#00BFC4")
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, subtitle_colour= "black"
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, sts = sts
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, lts = lts
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, ats = ats
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, als = als
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, ltis = ltis
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, geom_ls = geom_ls
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)
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ppi2P
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}
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#----------------------------
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# barplot for ppi2 affinity
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# <10 Ang of interface
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#------------------------------
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if (tolower(gene)%in%geneL_na){
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nca_distP = stability_count_bp(plotdf = df3_na
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, df_colname = "mcsm_na_outcome"
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#, leg_title = "mCSM-NA"
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#, label_categories =
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#, bp_plot_title = paste(common_bp_title, "Dist to NA")
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, yaxis_title = "Number of nsSNPs"
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, leg_position = "none"
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, subtitle_text = "mCSM\nNA"
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, bar_fill_values = c("#F8766D", "#00BFC4")
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, subtitle_colour= "black"
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, sts = sts
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, lts = lts
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, ats = ats
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, als = als
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, ltis = ltis
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, geom_ls = geom_ls
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)
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nca_distP
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}
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#####################################################################
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# ------------------------------
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# bp site site count: mCSM-lig
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# < 10 Ang ligand
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# ------------------------------
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common_bp_title = paste0("Sites <", DistCutOff, angstroms_symbol)
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posC_lig = site_snp_count_bp(plotdf = df3_lig
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, df_colname = "position"
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, xaxis_title = "Number of nsSNPs"
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, yaxis_title = "Number of Sites"
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, subtitle_colour = "chocolate4"
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, subtitle_text = ""
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, subtitle_size = subtitle_size
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, geom_ls = geom_ls_pc
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, leg_text_size = leg_text_size
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, axis_text_size = axis_text_size
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, axis_label_size = axis_label_size)
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posC_lig
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#------------------------------
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# bp site site count: ppi2
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# < 10 Ang interface
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#------------------------------
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if (tolower(gene)%in%geneL_ppi2){
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posC_ppi2 = site_snp_count_bp(plotdf = df3_ppi2
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, df_colname = "position"
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, xaxis_title = "Number of nsSNPs"
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, yaxis_title = "Number of Sites"
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, subtitle_colour = "chocolate4"
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, subtitle_text = ""
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, subtitle_size = subtitle_size
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, geom_ls = geom_ls_pc
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, leg_text_size = leg_text_size
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, axis_text_size = axis_text_size
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, axis_label_size = axis_label_size)
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posC_ppi2
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}
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#------------------------------
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# bp site site count: NCA dist
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# < 10 Ang nca
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#------------------------------
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if (tolower(gene)%in%geneL_na){
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posC_nca = site_snp_count_bp(plotdf = df3_na
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, df_colname = "position"
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, xaxis_title = "Number of nsSNPs"
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, yaxis_title = "Number of Sites"
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, subtitle_colour = "chocolate4"
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, subtitle_text = ""
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, subtitle_size = subtitle_size
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, geom_ls = geom_ls_pc
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, leg_text_size = leg_text_size
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, axis_text_size = axis_text_size
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, axis_label_size = axis_label_size)
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posC_nca
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}
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#===============================================================
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#------------------------------
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# bp site site count: ALL
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# <10 Ang ligand
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#------------------------------
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posC_all = site_snp_count_bp(plotdf = df3
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, df_colname = "position"
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, xaxis_title = "Number of nsSNPs"
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, yaxis_title = "Number of Sites"
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, subtitle_colour = "chocolate4"
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, subtitle_text = "All mutations sites"
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, subtitle_size = subtitle_size
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, geom_ls = geom_ls_pc
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, leg_text_size = leg_text_size
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, axis_text_size = axis_text_size
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, axis_label_size = axis_label_size)
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posC_all
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##################################################################
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consurfP = stability_count_bp(plotdf = df3
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, df_colname = "consurf_outcome"
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#, leg_title = "ConSurf"
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#, label_categories = labels_consurf
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, yaxis_title = "Number of nsSNPs"
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, leg_position = "top"
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, subtitle_text = "ConSurf"
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, bar_fill_values = consurf_colours # from globals
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, subtitle_colour= "black"
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, sts = sts
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, lts = lts
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, ats = ats
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, als = als
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, ltis = ltis
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, geom_ls = geom_ls)
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consurfP
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##############################################################
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sts_so = 10
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lts_so = 10
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ats_so = 10
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als_so = 10
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ltis_so = 10
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geom_ls_so = 2.5
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#===================
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# Stability
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#===================
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# duetP
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duetP = stability_count_bp(plotdf = df3
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, df_colname = "duet_outcome"
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, leg_title = "mCSM-DUET"
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#, label_categories = labels_duet
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, yaxis_title = "Number of nsSNPs"
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, leg_position = "none"
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, subtitle_text = "mCSM-DUET"
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, bar_fill_values = c("#F8766D", "#00BFC4")
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, subtitle_colour= "black"
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, sts = sts_so
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, lts = lts_so
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, ats = ats_so
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, als = als_so
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, ltis = ltis_so
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, geom_ls = geom_ls_so)
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duetP
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# foldx
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foldxP = stability_count_bp(plotdf = df3
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, df_colname = "foldx_outcome"
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#, leg_title = "FoldX"
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#, label_categories = labels_foldx
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, yaxis_title = ""
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, leg_position = "none"
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, subtitle_text = "FoldX"
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, bar_fill_values = c("#F8766D", "#00BFC4")
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, sts = sts_so
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, lts = lts_so
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, ats = ats_so
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, als = als_so
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, ltis = ltis_so
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, geom_ls = geom_ls_so)
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foldxP
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# deepddg
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deepddgP = stability_count_bp(plotdf = df3
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, df_colname = "deepddg_outcome"
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#, leg_title = "DeepDDG"
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#, label_categories = labels_deepddg
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, yaxis_title = ""
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, leg_position = "none"
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, subtitle_text = "DeepDDG"
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, bar_fill_values = c("#F8766D", "#00BFC4")
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, sts = sts_so
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, lts = lts_so
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, ats = ats_so
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, als = als_so
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, ltis = ltis_so
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, geom_ls = geom_ls_so)
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deepddgP
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# deepddg
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dynamut2P = stability_count_bp(plotdf = df3
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, df_colname = "ddg_dynamut2_outcome"
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#, leg_title = "Dynamut2"
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#, label_categories = labels_ddg_dynamut2_outcome
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, yaxis_title = ""
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, leg_position = "none"
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, subtitle_text = "Dynamut2"
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, bar_fill_values = c("#F8766D", "#00BFC4")
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, sts = sts_so
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, lts = lts_so
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, ats = ats_so
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, als = als_so
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, ltis = ltis_so
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, geom_ls = geom_ls_so)
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dynamut2P
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# provean
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proveanP = stability_count_bp(plotdf = df3
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, df_colname = "provean_outcome"
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#, leg_title = "PROVEAN"
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#, label_categories = labels_provean
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, yaxis_title = "Number of nsSNPs"
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, leg_position = "none" # top
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, subtitle_text = "PROVEAN"
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, bar_fill_values = c("#D01C8B", "#F1B6DA") # light pink and deep
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, sts = sts_so
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, lts = lts_so
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, ats = ats_so
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, als = als_so
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, ltis = ltis_so
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, geom_ls = geom_ls_so)
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proveanP
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# snap2
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snap2P = stability_count_bp(plotdf = df3
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, df_colname = "snap2_outcome"
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#, leg_title = "SNAP2"
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#, label_categories = labels_snap2
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, yaxis_title = ""
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, leg_position = "none" # top
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, subtitle_text = "SNAP2"
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, bar_fill_values = c("#D01C8B", "#F1B6DA") # light pink and deep
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, sts = sts_so
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, lts = lts_so
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, ats = ats_so
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, als = als_so
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, ltis = ltis_so
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, geom_ls = geom_ls_so)
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snap2P
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#####################################################################################
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