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