msa dashboard
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301
msa/global.R
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301
msa/global.R
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library(shinycssloaders)
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library(DT)
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library(NGLVieweR)
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library(hash)
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load_target_globals=function(target){
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cat(paste0("Reloading Target: ", target))
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source(paste0("/srv/shiny-server/git/LSHTM_analysis/config/", target, ".R")) # load per-target config file
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invisible(assign(paste0(target, "_merged_df3"), read.csv(paste0("/srv/shiny-server/git/Misc/shiny_dashboard/data/",target,"-merged_df3.csv")), envir = .GlobalEnv))
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invisible(assign(paste0(target, "_merged_df2"), read.csv(paste0("/srv/shiny-server/git/Misc/shiny_dashboard/data/",target,"-merged_df2.csv")), envir = .GlobalEnv))
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invisible(assign(paste0(target, "_corr_df_m3_f"), read.csv(paste0("/srv/shiny-server/git/Misc/shiny_dashboard/data/",target,"-corr_df_m3_f.csv")), envir = .GlobalEnv))
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invisible(assign(paste0(target, "_lin_lf"), read.csv(paste0("/srv/shiny-server/git/Misc/shiny_dashboard/data/",target,"-lin_lf.csv")), envir = .GlobalEnv))
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invisible(assign(paste0(target, "_lin_wf"), read.csv(paste0("/srv/shiny-server/git/Misc/shiny_dashboard/data/",target,"-lin_wf.csv")), envir = .GlobalEnv))
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lapply(
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c(
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"duet",
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"mcsm_lig",
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"foldx",
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"deepddg",
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"dynamut2",
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"consurf",
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"snap2",
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"provean",
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"dist_gen",
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"mcsm_ppi2"#,
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#"mcsm_na"
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), function(x){
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wf_filename=paste0("/srv/shiny-server/git/Misc/shiny_dashboard/data/", tolower(gene), "-wf_", x ,".csv")
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wf_var=paste0("wf_",x)
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if (file.exists(wf_filename)){
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invisible(assign(wf_var,read.csv(wf_filename), envir = .GlobalEnv)) # FILTH
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}
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lf_filename=paste0("/srv/shiny-server/git/Misc/shiny_dashboard/data/", tolower(gene), "-lf_", x ,".csv")
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lf_var=paste0(target, "_lf_",x)
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if (file.exists(lf_filename)){
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invisible(assign(lf_var,read.csv(lf_filename), envir = .GlobalEnv)) # FILTH
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}
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}
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)
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}
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# populate target-specific *_unified_msa vars
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load_msa_global=function(gene){
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drug=target_map[[gene]]
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in_filename_msa = paste0(tolower(gene), "_msa.csv")
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infile_msa = paste0("/srv/shiny-server/git/Data/", drug, "/output/", in_filename_msa)
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print(infile_msa)
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msa1 = read.csv(infile_msa, header = F)
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msa_seq = msa1$V1
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infile_fasta = paste0("/srv/shiny-server/git/Data/", drug, "/input/", tolower(gene), "2_f2.fasta")
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print(infile_fasta)
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msa2 = read.csv(infile_fasta, header = F)
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wt_seq = msa2$V1
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target_name=paste0(gene, '_unified_msa')
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#print(target_name)
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invisible(assign(target_name, list(msa_seq = msa_seq, wt_seq = wt_seq), envir = .GlobalEnv))
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}
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#### Local Functions ####
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# Generate a conditionalPanel() for a given graph function and sidebar name combination
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generate_conditionalPanel = function(tab_name, plot_function, plot_df){
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# e.g.: list("lin_count_bp_diversity", "Lineage diversity count")
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cond=paste0("input.sidebar == '", tab_name, "'")
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conditionalPanel(condition=cond, box(
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title=tab_name
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, status = "info"
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, width=NULL
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, plotOutput(plot_function
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, click = "plot_click") %>% withSpinner(color="#0dc5c1")
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# , plotOutput(plot_function, click = "plot_click")
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)
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)
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}
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# FIXME: passing in the per-plot params is broken
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lin_sc=function(x, all_lineages = F, ...){
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lf_var = get(paste0(x,"_lin_lf"))
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wf_var = get(paste0(x,"_lin_wf"))
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cowplot::plot_grid(lin_count_bp_diversity(wf_var, all_lineages, ...), lin_count_bp(lf_var, all_lineages, ...))
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}
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options(shiny.port = 8000)
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options(shiny.host = '0.0.0.0') # This means "listen to all addresses on all interfaces"
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options(shiny.launch.browser = FALSE)
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options(width=120)
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options(DT.options = list(scrollX = TRUE))
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################ STATIC GLOBALS ONLY ##############
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# never quite sure where "outdir" gets set :-|
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# using dataframes instead of lists lets us avoid use of map()
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plot_functions_df=data.frame(
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tab_name=c(
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"LogoP SNP",
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"Lineage Sample Count",
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"Site SNP count",
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"Stability SNP by site",
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"DM OM Plots",
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"Correlation",
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"Lineage Distribution",
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"Consurf",
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"LogoP OR",
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"LogoP ED"
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),
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plot_function=c(
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"LogoPlotSnps",
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"lin_sc",
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"site_snp_count_bp",
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"bp_stability_hmap",
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"lf_bp2",
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"my_corr_pairs",
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"lineage_distP",
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"wideP_consurf3",
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"LogoPlotCustomH",
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"LogoPlotMSA"
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),
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plot_df=c(
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"mutable_df3" ,
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"lin_lf",
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"mutable_df3",
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"merged_df3" ,
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"lf_duet" ,
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"corr_df_m3_f",
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"merged_df2",
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"merged_df3",
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"merged_df2",
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"unified_msa"
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)
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)
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stability_boxes_df=data.frame(
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outcome_colname=c("duet_outcome",
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"foldx_outcome",
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"deepddg_outcome",
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"ddg_dynamut2_outcome",
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"mcsm_na_outcome",
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"mcsm_ppi2_outcome",
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"snap2_outcome",
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"consurf_outcome",
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"avg_stability_outcome"),
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stability_type=c(
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"DUET",
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"FoldX",
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"DeepDDG",
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"Dynamut2",
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"mCSM-NA",
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"mCSM-ppi2",
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"SNAP2",
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"Consurf",
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"Average"
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),
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stability_colname=c(
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"duet_scaled",
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"foldx_scaled",
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"deepddg_scaled",
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"ddg_dynamut2_scaled",
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"mcsm_na_scaled",
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"mcsm_ppi2_scaled",
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"snap2_scaled",
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"consurf_scaled",
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"avg_stability_scaled"
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)
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)
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table_columns = c(
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"position",
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"mutationinformation",
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"sensitivity",
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"ligand_distance",
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"avg_lig_affinity",
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"avg_lig_affinity_outcome",
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"avg_stability",
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"avg_stability_outcome",
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"or_mychisq",
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"maf",
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"snap2_outcome",
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"consurf_outcome",
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"provean_outcome",
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"rsa",
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"kd_values" ,
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"rd_values"
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)
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logoPlotSchemes <- list("chemistry"
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, "taylor"
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, "hydrophobicity"
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, "clustalx")
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dm_om_methods = c("DUET ΔΔG"
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, "Consurf"
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, "Deepddg ΔΔG"
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, "Dynamut2 ΔΔG"
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, "FoldX ΔΔG"
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, "Ligand affinity (log fold change)"
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, "mCSM-NA affinity ΔΔG"
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, "SNAP2")
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dm_om_map = hash(c(
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"DUET ΔΔG"
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, "Consurf"
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, "Deepddg ΔΔG"
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, "Dynamut2 ΔΔG"
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, "FoldX ΔΔG"
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, "Ligand affinity (log fold change)"
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, "mCSM-NA affinity ΔΔG"
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, "SNAP2"
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), c(
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"lf_duet"
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,"lf_consurf"
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,"lf_deepddg"
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,"lf_dynamut2"
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,"lf_foldx"
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,"lf_mcsm_lig"
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,"lf_mcsm_na"
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,"lf_snap2"
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)
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)
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#### target_map: handy gene/drug mapping hash ####
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target_map = hash(
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c(
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"alr",
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"gid",
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"embb",
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"pnca",
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"rpob",
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"katg"),
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c(
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"cycloserine",
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"streptomycin",
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"ethambutol",
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"pyrazinamide",
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"rifampicin",
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"isoniazid")
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)
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# load E V E R Y T H I N G
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lapply(c(
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"alr",
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"embb",
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"gid",
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"katg",
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"pnca",
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"rpob"
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),function(x){
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invisible(load_target_globals(x))
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invisible(load_msa_global(x)) # turn off to speed up start time at the expense of "LogoP ED"
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}
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)
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consurf_palette1 = c("0" = "yellow2"
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, "1" = "cyan1"
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, "2" = "steelblue2"
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, "3" = "cadetblue2"
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, "4" = "paleturquoise2"
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, "5" = "thistle3"
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, "6" = "thistle2"
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, "7" = "plum2"
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, "8" = "maroon"
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, "9" = "violetred2")
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consurf_palette2 = c("0" = "yellow2"
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, "1" = "forestgreen"
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, "2" = "seagreen3"
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, "3" = "palegreen1"
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, "4" = "darkseagreen2"
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, "5" = "thistle3"
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, "6" = "lightpink1"
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, "7" = "orchid3"
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, "8" = "orchid4"
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, "9" = "darkorchid4")
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# decreasing levels mess legend
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# consurf_colours_LEVEL = c(
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# "0" = rgb(1.00,1.00,0.59)
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# , "9" = rgb(0.63,0.16,0.37)
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# , "8" = rgb(0.94,0.49,0.67)
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# , "7" = rgb(0.98,0.78,0.86)
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# , "6" = rgb(0.98,0.92,0.96)
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# , "5" = rgb(1.00,1.00,1.00)
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# , "4" = rgb(0.84,0.94,0.94)
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# , "3" = rgb(0.65,0.86,0.90)
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# , "2" = rgb(0.29,0.69,0.75)
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# , "1" = rgb(0.04,0.49,0.51)
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# )
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consurf_colours = c(
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"0" = rgb(1.00,1.00,0.59)
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, "1" = rgb(0.04,0.49,0.51)
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, "2" = rgb(0.29,0.69,0.75)
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, "3" = rgb(0.65,0.86,0.90)
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, "4" = rgb(0.84,0.94,0.94)
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, "5" = rgb(1.00,1.00,1.00)
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, "6" = rgb(0.98,0.92,0.96)
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, "7" = rgb(0.98,0.78,0.86)
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, "8" = rgb(0.94,0.49,0.67)
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, "9" = rgb(0.63,0.16,0.37)
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)
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