114 lines
3.4 KiB
R
114 lines
3.4 KiB
R
#!/usr/bin/env Rscript
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#########################################################
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# TASK: Lineage dist plots: ggridges
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# Output: 1 or 2 SVGs for PS stability
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##########################################################
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# Installing and loading required packages
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##########################################################
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getwd()
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setwd("~/git/LSHTM_analysis/scripts/plotting/")
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getwd()
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source("Header_TT.R") # also loads all my functions
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#===========
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# input
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#===========
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#drug = "streptomycin"
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#gene = "gid"
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source("get_plotting_dfs.R")
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spec = matrix(c(
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"drug" , "d", 1, "character",
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"gene" , "g", 1, "character",
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"data_file1" , "fa", 2, "character",
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"data_file2" , "fb", 2, "character"
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), byrow = TRUE, ncol = 4)
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opt = getopt(spec)
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drug = opt$drug
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gene = opt$gene
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infile_params = opt$data_file1
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infile_metadata = opt$data_file2
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if(is.null(drug)|is.null(gene)) {
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stop("Missing arguments: --drug and --gene must both be specified (case-sensitive)")
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}
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#=======
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# output
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#=======
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lineage_dist_dm_om_ps = "lineage_dist_dm_om_PS.svg"
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plot_lineage_dist_dm_om_ps = paste0(plotdir,"/", lineage_dist_dm_om_ps)
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#========================================================================
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###########################
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# Data for plots
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# you need merged_df2 or merged_df2_comp
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# since this is one-many relationship
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# i.e the same SNP can belong to multiple lineages
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# using the _comp dataset means
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# we lose some muts and at this level, we should use
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# as much info as available, hence use df with NA
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###########################
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#===================
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# Data for plots
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#===================
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# quick checks
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table(merged_df2$mutation_info_labels); levels(merged_df2$lineage_labels)
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table(merged_df2$lineage_labels); levels(merged_df2$mutation_info_labels)
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lin_dist_plot = merged_df2[merged_df2$lineage_labels%in%c("L1", "L2", "L3", "L4"),]
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table(lin_dist_plot$lineage_labels); nlevels(lin_dist_plot$lineage_labels)
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# refactor
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lin_dist_plot$lineage_labels = factor(lin_dist_plot$lineage_labels)
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nlevels(lin_dist_plot$lineage_labels)
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#-----------------------------------------------------------------------
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# IMPORTANT RESULTS to put inside table or text for interactive plots
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sum(table(lin_dist_plot$lineage_labels)) #{RESULT: Total number of samples for lineage}
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table(lin_dist_plot$lineage_labels)#{RESULT: No of samples within lineage}
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length(unique(lin_dist_plot$mutationinformation))#{Result: No. of unique mutations selected lineages contribute to}
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length(lin_dist_plot$mutationinformation)
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u2 = unique(merged_df2$mutationinformation)
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u = unique(lin_dist_plot$mutationinformation)
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check = u2[!u2%in%u]; print(check) #{Muts not present within selected lineages}
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#-----------------------------------------------------------------------
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# without facet
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linP_dm_om = lineage_distP(lin_dist_plot
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, with_facet = F
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, x_axis = "deepddg"
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, y_axis = "lineage_labels"
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, x_lab = "DeepDDG"
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, leg_label = "Mutation Class"
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)
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linP_dm_om
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# with facet
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linP_dm_om_facet = lineage_distP(lin_dist_plot
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, with_facet = T
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, facet_wrap_var = "mutation_info_labels"
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, leg_label = "Mutation Class"
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, leg_pos_wf = "none"
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, leg_dir_wf = "horizontal"
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)
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linP_dm_om_facet
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#=================
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# output plot:
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# without facet
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#=================
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svg(plot_lineage_dist_dm_om_ps)
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linP_dm_om
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dev.off()
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