added lineage plots in one
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4 changed files with 177 additions and 261 deletions
172
scripts/plotting/plotting_thesis/linage_bp_dist.R
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172
scripts/plotting/plotting_thesis/linage_bp_dist.R
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#!/usr/bin/env Rscript
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#########################################################
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# TASK: Lineage plots [merged_df2]
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# Count
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# Diversity
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# Average stability dist
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# Avergae affinity dist: optional
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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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#===============
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#Quick numbers checks
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#===============
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nsample_lin = merged_df2[merged_df2$lineage%in%c("L1", "L2", "L3", "L4"),]
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if ( all(table(nsample_lin$sensitivity)== table(nsample_lin$mutation_info_labels)) ){
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cat("\nTotal no. of samples belonging to L1-l4 for", gene,":", nrow(nsample_lin)
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, "\nCounting R and S samples")
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if( sum(table(nsample_lin$sensitivity)) == nrow(nsample_lin) ){
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cat("\nPASSNumbers cross checked:")
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print(table(nsample_lin$sensitivity))
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}
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}else{
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stop("Abort: Numbers mismatch. Please check")
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}
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########################################################################
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###################################################
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# Lineage barplots #
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###################################################
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#===============================
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# lineage sample and SNP count
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#===============================
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lin_countP = lin_count_bp(lf_data = lineage_dfL[['lin_lf']]
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, all_lineages = F
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, x_categ = "sel_lineages"
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, y_count = "p_count"
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, use_lineages = c("L1", "L2", "L3", "L4")
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, bar_fill_categ = "count_categ"
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, display_label_col = "p_count"
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, bar_stat_stype = "identity"
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, d_lab_size = 8
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, d_lab_col = "black"
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, my_xats = 25 # x axis text size
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, my_yats = 25 # y axis text sized_lab_size
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, my_xals = 25 # x axis label size
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, my_yals = 25 # y axis label size
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, my_lls = 25 # legend label size
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, bar_col_labels = c("SNPs", "Total Samples")
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, bar_col_values = c("grey50", "gray75")
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, bar_leg_name = ""
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, leg_location = "top"
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, y_log10 = F
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, y_scale_percent = FALSE
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, y_label = c("Count")
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)
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#===============================
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# lineage SNP diversity count
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#===============================
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lin_diversityP = lin_count_bp_diversity(lf_data = lineage_dfL[['lin_wf']]
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, x_categ = "sel_lineages"
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, y_count = "snp_diversity"
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#, all_lineages = F
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, use_lineages = c("L1", "L2", "L3", "L4")
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, display_label_col = "snp_diversity_f"
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, bar_stat_stype = "identity"
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, x_lab_angle = 90
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, d_lab_size =9
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, my_xats = 25 # x axis text size
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, my_yats = 25 # y axis text size
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, my_xals = 25 # x axis label size
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, my_yals = 25 # y axis label size
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, my_lls = 25 # legend label size
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, y_log10 = F
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, y_scale_percent = F
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, leg_location = "top"
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, y_label = "Percent" #"SNP diversity"
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, bp_plot_title = "nsSNP diversity"
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, title_colour = "black" #"chocolate4"
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, subtitle_text = NULL
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, sts = 20
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, subtitle_colour = "#350E20FF")
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#=============================================
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# Output plots: Lineage count and Diversity
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#=============================================
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# lineage_bp_CL = paste0(outdir_images
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# ,tolower(gene)
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# ,"_lineage_bp_CL_Tall.svg")
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#
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# cat("Lineage barplots:", lineage_bp_CL)
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# svg(lineage_bp_CL, width = 8, height = 15)
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#
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# cowplot::plot_grid(lin_countP, lin_diversityP
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# #, labels = c("(a)", "(b)", "(c)", "(d)")
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# , nrow = 2
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# # , ncols = 2
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# , labels = "AUTO"
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# , label_size = 25)
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#
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# dev.off()
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########################################################################
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###################################################
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# Stability dist #
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###################################################
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# scaled_cols_stability = c("duet_scaled"
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# , "deepddg_scaled"
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# , "ddg_dynamut2_scaled"
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# , "foldx_scaled"
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# , "avg_stability_scaled")
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my_xlabel = paste0("Average stability ", "(", stability_suffix, ")"); my_xlabel
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#plotdf = merged_df2[merged_df2$lineage%in%c("L1", "L2", "L3", "L4"),]
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linP_dm_om = lineage_distP(merged_df2
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, with_facet = F
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, x_axis = "avg_stability_scaled"
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, y_axis = "lineage_labels"
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, x_lab = my_xlabel
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, use_lineages = c("L1", "L2", "L3", "L4")
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#, fill_categ = "mutation_info_orig", fill_categ_cols = c("#E69F00", "#999999")
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, fill_categ = "sensitivity"
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, fill_categ_cols = c("red", "blue")
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, label_categories = c("Resistant", "Sensitive")
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, leg_label = "Mutation group"
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, my_ats = 22 # axis text size
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, my_als = 22 # axis label size
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, my_leg_ts = 22
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, my_leg_title = 22
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, my_strip_ts = 22
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, alpha = 0.56
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)
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linP_dm_om
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###################################################
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# Affinity dist [OPTIONAL] #
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###################################################
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# scaled_cols_affinity = c("affinity_scaled"
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# , "mmcsm_lig_scaled"
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# , "mcsm_ppi2_scaled"
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# , "mcsm_na_scaled"
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# , "avg_affinity_scaled")
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# lineage_distP(merged_df2
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# , with_facet = F
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# , x_axis = "avg_affinity_scaled"
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# , y_axis = "lineage_labels"
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# , x_lab = my_xlabel
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# , use_lineages = c("L1", "L2", "L3", "L4")
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# #, fill_categ = "mutation_info_orig", fill_categ_cols = c("#E69F00", "#999999")
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# , fill_categ = "sensitivity"
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# , fill_categ_cols = c("red", "blue")
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# , label_categories = c("Resistant", "Sensitive")
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# , leg_label = "Mutation group"
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# , my_ats = 22 # axis text size
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# , my_als = 22 # axis label size
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# , my_leg_ts = 22
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# , my_leg_title = 22
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# , my_strip_ts = 22
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# , alpha = 0.56
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# )
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#!/usr/bin/env Rscript
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#!/usr/bin/env Rscript
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###########################################
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# TASK: generate plots for lineage
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# Individual plots in
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#lineage_bp_both.R
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#linage_dist_ens_stability.R
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###########################################
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###########################################
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my_label_size = 25
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my_label_size = 25
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#!/usr/bin/env Rscript
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#########################################################
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# TASK: Lineage dist plots for stability:
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# average the four tools
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# func from : lineage_dist.R
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# plotdf
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# , x_axis = "duet_scaled"
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# , y_axis = "lineage_labels"
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# , x_lab = "DUET"
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# , all_lineages = F
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# , use_lineages = c("L1", "L2", "L3", "L4")
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# , with_facet = F
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# , facet_wrap_var = "" # FIXME: document what this is for
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# , fill_categ = "mutation_info_labels"
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# , fill_categ_cols = c("#E69F00", "#999999")
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# , my_ats = 15 # axis text size
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# , my_als = 20 # axis label size
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# , my_leg_ts = 16
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# , my_leg_title = 16
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# , my_strip_ts = 20
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# , leg_pos = c(0.8, 0.9)
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# , leg_pos_wf = c("top", "left", "bottom", "right")
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# , leg_dir_wf = c("horizontal", "vertical")
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# , leg_label = ""
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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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#=======
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# Data
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#=======
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df2 = merged_df2
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#==================================
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# PREFORMATTING: for consistency
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# IMPORTANT for calculating effects
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#==================================
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head(df2$ddg_foldx)
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df2['ddg_foldxC'] = abs(df2$ddg_foldx)
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head(df2['ddg_foldxC'])
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# reverse signs for foldx scaled values for consistency with other tools
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df2['foldx_scaled_signC'] = abs(df2$foldx_scaled)
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# remove the old ones from
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rm_foldx_cols = c("ddg_foldx","foldx_scaled")
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raw_cols_stab_revised = raw_cols_stability[!raw_cols_stability%in%rm_foldx_cols]
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raw_cols_stab_revised = c(raw_cols_stab_revised,"ddg_foldxC")
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scaled_cols_stab_revised = scaled_cols_stability[!scaled_cols_stability%in%rm_foldx_cols]
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scaled_cols_stab_revised = c(scaled_cols_stab_revised, "foldx_scaled_signC")
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#=================
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# PREFORMATTING: for consistency
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#=================
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cols_to_extract = colnames(df2)[colnames(df2)%in%c(common_cols
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, outcome_cols_stability
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, raw_cols_stability
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, scaled_cols_stability
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, raw_cols_stab_revised
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, scaled_cols_stab_revised
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, "lineage","lineage_labels")]
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df2_plot = df2[, cols_to_extract]
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all(table(df2_plot$lineage) == table(df2_plot$lineage_labels))
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# find which stability cols to average: should contain revised foldx
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if ("foldx_scaled_signC"%in%colnames(df2_plot)){
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cat("\nPASS: finding stability cols to average")
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cols2avg_new = which(colnames(df2_plot)%in%scaled_cols_stab_revised)
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}else{
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stop("\nAbort: Foldx column has opposing sign. Can't proceed to avergae.")
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}
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# ensemble average across predictors
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df2_plot['ens_stab_new'] = rowMeans(df2_plot[, cols2avg_new])
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head(df2_plot$position); head(df2_plot$mutationinformation)
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table(df2_plot['ens_stab_new'])
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# scaling average values
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df2_plot["ens_stab_new_scaled"] = lapply(df2_plot["ens_stab_new"]
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, function(x) {
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scales::rescale_mid(x
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, to = c(-1,1)
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, from = c( min(df2_plot["ens_stab_new"])
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, max(df2_plot["ens_stab_new"]))
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, mid = 0
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#, from = c(0,1))
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)})
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min(df2_plot['ens_stab_new']); max(df2_plot['ens_stab_new'])
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foo = df2_plot[c("cols2avg_new", "ens_stab_new_scaled"),]
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min(df2_plot['ens_stab_new_scaled']); max(df2_plot['ens_stab_new_scaled'])
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###########################################################
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nrow(df2_plot)
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table(df2_plot$lineage)
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table(df2_plot$lineage_labels)
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#===============
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#Quick numbers checks
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#===============
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nsample_lin = df2_plot[df2_plot$lineage%in%c("L1", "L2", "L3", "L4"),]
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if ( all(table(nsample_lin$sensitivity)== table(nsample_lin$mutation_info_labels)) ){
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cat("\nTotal no. of samples belonging to L1-l4 for", gene,":", nrow(nsample_lin)
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, "\nCounting R and S samples")
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if( sum(table(nsample_lin$sensitivity)) == nrow(nsample_lin) ){
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cat("\nPASSNumbers cross checked:")
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print(table(nsample_lin$sensitivity))
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}
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}else{
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stop("Abort: Numbers mismatch. Please check")
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}
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#====================
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# Output Lineage plot
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#====================
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my_xlabel = paste0("Average stability ", "(", stability_suffix, ")"); my_xlabel
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# linD_ens_stabP = paste0(outdir_images
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# , tolower(gene)
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# ,"_linD_ens_stabP.svg")
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#
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# cat("\nOutput plot:", linD_ens_stabP)
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# svg(linD_ens_stabP, width = 10, height = 10)
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linP_dm_om = lineage_distP(df2_plot
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, with_facet = F
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, x_axis = "ens_stab_new_scaled"
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, y_axis = "lineage_labels"
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, x_lab = my_xlabel
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, use_lineages = c("L1", "L2", "L3", "L4")
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#, fill_categ = "mutation_info_orig", fill_categ_cols = c("#E69F00", "#999999")
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, fill_categ = "sensitivity"
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, fill_categ_cols = c("red", "blue")
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, label_categories = c("Resistant", "Sensitive")
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, leg_label = "Mutation group"
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, my_ats = 22 # axis text size
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, my_als = 22 # axis label size
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, my_leg_ts = 22
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, my_leg_title = 22
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, my_strip_ts = 22
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, alpha = 0.56
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)
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linP_dm_om
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#dev.off()
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###########################################
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my_label_size = 25
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linPlots_combined = paste0(outdir_images
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, tolower(gene)
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,"_linP_combined.svg")
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cat("\nOutput plot:", linPlots_combined)
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svg(linPlots_combined, width = 18, height = 12)
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cowplot::plot_grid(
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cowplot::plot_grid(lin_countP, lin_diversityP
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, nrow = 2
|
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# , ncols = 2
|
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, labels = "AUTO"
|
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||||||
, label_size = my_label_size),
|
|
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NULL,
|
|
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linP_dm_om,
|
|
||||||
nrow = 1,
|
|
||||||
labels = c("", "", "C"),
|
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||||||
label_size = my_label_size,
|
|
||||||
rel_widths = c(35, 3, 52)
|
|
||||||
)
|
|
||||||
dev.off()
|
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||||||
|
|
@ -1,75 +0,0 @@
|
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# get plotting_dfs()
|
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||||||
# using dfs [lf and wf] from lineage_dfL
|
|
||||||
# FIXME: add SNP diversity as the title
|
|
||||||
#===============================
|
|
||||||
# lineage sample and SNP count
|
|
||||||
#===============================
|
|
||||||
lin_countP = lin_count_bp(lf_data = lineage_dfL[['lin_lf']]
|
|
||||||
, all_lineages = F
|
|
||||||
, x_categ = "sel_lineages"
|
|
||||||
, y_count = "p_count"
|
|
||||||
, use_lineages = c("L1", "L2", "L3", "L4")
|
|
||||||
, bar_fill_categ = "count_categ"
|
|
||||||
, display_label_col = "p_count"
|
|
||||||
, bar_stat_stype = "identity"
|
|
||||||
, d_lab_size = 8
|
|
||||||
, d_lab_col = "black"
|
|
||||||
, my_xats = 25 # x axis text size
|
|
||||||
, my_yats = 25 # y axis text sized_lab_size
|
|
||||||
, my_xals = 25 # x axis label size
|
|
||||||
, my_yals = 25 # y axis label size
|
|
||||||
, my_lls = 25 # legend label size
|
|
||||||
, bar_col_labels = c("SNPs", "Total Samples")
|
|
||||||
, bar_col_values = c("grey50", "gray75")
|
|
||||||
, bar_leg_name = ""
|
|
||||||
, leg_location = "top"
|
|
||||||
, y_log10 = F
|
|
||||||
, y_scale_percent = FALSE
|
|
||||||
, y_label = c("Count")
|
|
||||||
)
|
|
||||||
|
|
||||||
#===============================
|
|
||||||
# lineage SNP diversity count
|
|
||||||
#===============================
|
|
||||||
lin_diversityP = lin_count_bp_diversity(lf_data = lineage_dfL[['lin_wf']]
|
|
||||||
, x_categ = "sel_lineages"
|
|
||||||
, y_count = "snp_diversity"
|
|
||||||
#, all_lineages = F
|
|
||||||
, use_lineages = c("L1", "L2", "L3", "L4")
|
|
||||||
, display_label_col = "snp_diversity_f"
|
|
||||||
, bar_stat_stype = "identity"
|
|
||||||
, x_lab_angle = 90
|
|
||||||
, d_lab_size =9
|
|
||||||
, my_xats = 25 # x axis text size
|
|
||||||
, my_yats = 25 # y axis text size
|
|
||||||
, my_xals = 25 # x axis label size
|
|
||||||
, my_yals = 25 # y axis label size
|
|
||||||
, my_lls = 25 # legend label size
|
|
||||||
, y_log10 = F
|
|
||||||
, y_scale_percent = F
|
|
||||||
, leg_location = "top"
|
|
||||||
, y_label = "Percent" #"SNP diversity"
|
|
||||||
, bp_plot_title = "nsSNP diversity"
|
|
||||||
, title_colour = "black" #"chocolate4"
|
|
||||||
, subtitle_text = NULL
|
|
||||||
, sts = 20
|
|
||||||
, subtitle_colour = "#350E20FF")
|
|
||||||
|
|
||||||
#=============================================
|
|
||||||
# Output plots: Lineage count and Diversity
|
|
||||||
#=============================================
|
|
||||||
# lineage_bp_CL = paste0(outdir_images
|
|
||||||
# ,tolower(gene)
|
|
||||||
# ,"_lineage_bp_CL_Tall.svg")
|
|
||||||
#
|
|
||||||
# cat("Lineage barplots:", lineage_bp_CL)
|
|
||||||
# svg(lineage_bp_CL, width = 8, height = 15)
|
|
||||||
#
|
|
||||||
# cowplot::plot_grid(lin_countP, lin_diversityP
|
|
||||||
# #, labels = c("(a)", "(b)", "(c)", "(d)")
|
|
||||||
# , nrow = 2
|
|
||||||
# # , ncols = 2
|
|
||||||
# , labels = "AUTO"
|
|
||||||
# , label_size = 25)
|
|
||||||
#
|
|
||||||
# dev.off()
|
|
||||||
Loading…
Add table
Add a link
Reference in a new issue