172 lines
7.1 KiB
R
172 lines
7.1 KiB
R
#!/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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lin_countP
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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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lin_diversityP
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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_lig_affinity_scaled")
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# lineage_distP(merged_df2
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# , with_facet = F
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# , x_axis = "avg_lig_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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