new msa dash
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4 changed files with 393 additions and 98 deletions
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324
msa/global.R
324
msa/global.R
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@ -1,17 +1,47 @@
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# ***************************
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# ** I M P O R T A N T **
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# ***************************
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# DO NOT USE OR MODIFY THIS.
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# USE THE ONE IN THE 'Dashboards'
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# REPO
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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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# FIXME This is slow and should happen *once only*
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#source("~/git/LSHTM_analysis/scripts/Header_TT.R")
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# FIXME: these are needed but slow to load every time
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# source("~/git/LSHTM_analysis/config/alr.R")
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# source("~/git/LSHTM_analysis/config/gid.R")
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# source("~/git/LSHTM_analysis/config/pnca.R")
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# source("~/git/LSHTM_analysis/config/rpob.R")
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# source("~/git/LSHTM_analysis/config/katg.R")
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# TODO: this is TEMPORARY and will shortly get replaced with a target picker
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# that'll reload everything when changing targets. the lapply() is *much* quicker
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# than previous approaches
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# system.time({
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source("~/git/LSHTM_analysis/scripts/Header_TT.R")
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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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source(paste0("~/git/LSHTM_analysis/config/", target, ".R")) # load per-target config file
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invisible(assign(paste0(target, "_merged_df3"), read.csv(paste0("~/git/Misc/shiny_dashboard/data/",target,"-merged_df3.csv")), envir = .GlobalEnv))
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invisible(assign(paste0(target, "_merged_df2"), read.csv(paste0("~/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("~/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("~/git/Misc/shiny_dashboard/data/",target,"-lin_lf.csv")), envir = .GlobalEnv))
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invisible(assign(paste0(target, "_lin_wf"), read.csv(paste0("~/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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@ -26,12 +56,12 @@ load_target_globals=function(target){
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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_filename=paste0("~/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_filename=paste0("~/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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@ -42,37 +72,24 @@ load_target_globals=function(target){
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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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in_filename_msa = paste0(tolower(gene), "_msa.csv")
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infile_msa = paste0("~/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$V1
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infile_fasta = paste0("/srv/shiny-server/git/Data/", drug, "/input/", tolower(gene), "2_f2.fasta")
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infile_fasta = paste0("~/git/Data/", drug, "/input/", tolower(gene), "2_f2.fasta")
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print(infile_fasta)
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msa2 = read.csv(infile_fasta, header = F)
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wt_seq = msa2$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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@ -180,7 +197,7 @@ table_columns = c(
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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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"rsa",
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"kd_values" ,
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"rd_values"
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)
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@ -197,26 +214,6 @@ dm_om_methods = c("DUET 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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@ -235,7 +232,7 @@ target_map = hash(
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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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#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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@ -245,57 +242,188 @@ lapply(c(
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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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invisible(load_msa_global(x))
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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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#### Shiny UI #####
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if(interactive()){
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ui <- dashboardPage(
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#dashboardHeader(title = paste0(gene, "/", drug)),
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dashboardHeader(title = "Sequence Alignment"),
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dashboardSidebar(
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sidebarMenu( id = "sidebar",
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selectInput(
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"switch_target",
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label="Target",
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choices = 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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),
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selected="embb"),
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menuItem("LogoP ED", tabName="LogoP ED"),
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sliderInput(
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"display_position_full_range"
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, "Display Positions"
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, min=1, max=150, value=c(1,150)
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),
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conditionalPanel(
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condition="
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input.sidebar == 'LogoP SNP' ||
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input.sidebar == 'LogoP OR' ||
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input.sidebar == 'LogoP ED'",
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selectInput(
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"logoplot_colour_scheme",
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label="Logo Plot Colour Scheme",
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choices = logoPlotSchemes,
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selected="chemistry"
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)
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)
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)
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),
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body <- dashboardBody(
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tabItems(
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tabItem(tabName = "dashboard",
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h2("Dashboard tab content")
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),
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tabItem(tabName = "widgets",
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h2("Widgets tab content")
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)
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),
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# creates a 'Conditional Panel' containing a plot object from each of our
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# ggplot plot functions (and its associated data frame)
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fluidRow(
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column(
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width=12,
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plotOutput("LogoPlotMSA",
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click = "plot_click") %>% withSpinner(color="#0dc5c1")
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)
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)
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)
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)
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#### Shiny Backend Server #####
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server <- function(input, output, session) {
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observeEvent(
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{
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input$display_position_full_range #special-purpose for MSA
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input$logoplot_colour_scheme
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input$switch_target
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},
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{
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# C O M P A T I B I L I T Y
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#gene=input$switch_target
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#drug=target_map[[gene]]
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merged_df3=cbind(get(paste0(input$switch_target, '_merged_df3')))
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position_max=max(merged_df3[['position']])
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position_min=min(merged_df3[['position']])
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min_ligand_distance=min(merged_df3$ligand_distance)
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max_ligand_distance=max(merged_df3$ligand_distance)
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# FIXME: these are IMPORTANT
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# # add "pos_count" position count column
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# merged_df3=merged_df3 %>% dplyr::add_count(position)
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# merged_df3$pos_count=merged_df3$n
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# merged_df3$n=NULL
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#
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mutable_df3 = cbind(merged_df3)
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unified_msa = get(paste0(input$switch_target, '_unified_msa'))
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#
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# # re-sort the dataframe according to position count
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sorted_df = cbind(merged_df3)
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sorted_df = sorted_df %>% arrange(pos_count)
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#
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outdir = paste0("~/git/Data/", drug, '/output/')
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indir = paste0("~/git/Data/", drug , "/input/")
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#
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# source("~/git/LSHTM_analysis/scripts/plotting/logo_data_msa.R") # probably unnecessary...
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# source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")
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#### nasty special-purpose merged_df3 variants ####
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# FIXME: SLOW
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# corr_plotdf = corr_data_extract(
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# merged_df3
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# , gene = gene
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# , drug = drug
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# , extract_scaled_cols = F
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# )
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#input$stability_snp_param
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updateSliderInput(
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session,
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"display_position_range",
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min = position_min,
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max = position_max
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#, value = c(position_min, position_min+150)
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)
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updateSliderInput(
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session,
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"display_position_full_range",
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min = 1,
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max = position_max #,
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# value = c(position_min, position_min+150)
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)
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updateNumericInput(session, "selected_logop_snp_position", min = position_min, max = position_max, value = position_min)
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updateNumericInput(session, "selected_logop_ed_position", min = position_min, max = position_max, value = position_min)
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updateNumericInput(session, "corr_lig_dist", min = min_ligand_distance, max = max_ligand_distance, value = min_ligand_distance)
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stability_colname = stability_boxes_df[stability_boxes_df$stability_type==input$stability_snp_param,"stability_colname"]
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outcome_colname = stability_boxes_df[stability_boxes_df$stability_type==input$stability_snp_param,"outcome_colname"]
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display_position_range = input$display_position_range
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plot_min=display_position_range[1]
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plot_max=display_position_range[2]
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display_position_full_range = input$display_position_full_range
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full_range_min=display_position_full_range[1]
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full_range_max=display_position_full_range[2]
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logoplot_colour_scheme = input$logoplot_colour_scheme
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omit_snp_count = input$omit_snp_count
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print(paste0('Plotting positions between: ', plot_min, ' and ', plot_max))
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subset_mutable_df3=mutable_df3[(mutable_df3$position>=plot_min & mutable_df3$position <=plot_max),]
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subset_mutable_df3=mutable_df3[(mutable_df3$position>=plot_min & mutable_df3$position <=plot_max),]
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subset_sorted_df=sorted_df[(sorted_df$position>=plot_min & sorted_df$position <=plot_max),]
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#### LogoPlotMSA/Logo Plot ED ####
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output$LogoPlotMSA = renderPlot(
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LogoPlotMSA(target=input$switch_target,
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plot_positions=full_range_min:full_range_max,
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my_logo_col = logoplot_colour_scheme,
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aa_pos_drug = aa_pos_drug,
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active_aa_pos = active_aa_pos,
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aa_pos_lig1 = aa_pos_lig1,
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aa_pos_lig2 = aa_pos_lig2,
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aa_pos_lig3 = aa_pos_lig3
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)
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)
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}
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)
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#### EOF Shiny Server ####
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}
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################ Running Server ##############
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app <- shinyApp(ui, server)
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runApp(app)
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}
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105
msa/server.R
105
msa/server.R
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@ -0,0 +1,105 @@
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function(input, output, session) {
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observeEvent(
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{
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input$display_position_full_range #special-purpose for MSA
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input$logoplot_colour_scheme
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input$switch_target
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},
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{
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# C O M P A T I B I L I T Y
|
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#gene=input$switch_target
|
||||
#drug=target_map[[gene]]
|
||||
merged_df3=cbind(get(paste0(input$switch_target, '_merged_df3')))
|
||||
|
||||
position_max=max(merged_df3[['position']])
|
||||
position_min=min(merged_df3[['position']])
|
||||
min_ligand_distance=min(merged_df3$ligand_distance)
|
||||
max_ligand_distance=max(merged_df3$ligand_distance)
|
||||
# FIXME: these are IMPORTANT
|
||||
# # add "pos_count" position count column
|
||||
# merged_df3=merged_df3 %>% dplyr::add_count(position)
|
||||
# merged_df3$pos_count=merged_df3$n
|
||||
# merged_df3$n=NULL
|
||||
#
|
||||
mutable_df3 = cbind(merged_df3)
|
||||
unified_msa = get(paste0(input$switch_target, '_unified_msa'))
|
||||
#
|
||||
# # re-sort the dataframe according to position count
|
||||
sorted_df = cbind(merged_df3)
|
||||
sorted_df = sorted_df %>% arrange(pos_count)
|
||||
|
||||
#
|
||||
outdir = paste0("~/git/Data/", drug, '/output/')
|
||||
indir = paste0("~/git/Data/", drug , "/input/")
|
||||
#
|
||||
# source("~/git/LSHTM_analysis/scripts/plotting/logo_data_msa.R") # probably unnecessary...
|
||||
|
||||
# source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")
|
||||
|
||||
#### nasty special-purpose merged_df3 variants ####
|
||||
# FIXME: SLOW
|
||||
# corr_plotdf = corr_data_extract(
|
||||
# merged_df3
|
||||
# , gene = gene
|
||||
# , drug = drug
|
||||
# , extract_scaled_cols = F
|
||||
# )
|
||||
|
||||
#input$stability_snp_param
|
||||
|
||||
updateSliderInput(
|
||||
session,
|
||||
"display_position_range",
|
||||
min = position_min,
|
||||
max = position_max
|
||||
#, value = c(position_min, position_min+150)
|
||||
)
|
||||
updateSliderInput(
|
||||
session,
|
||||
"display_position_full_range",
|
||||
min = 1,
|
||||
max = position_max #,
|
||||
# value = c(position_min, position_min+150)
|
||||
)
|
||||
updateNumericInput(session, "selected_logop_snp_position", min = position_min, max = position_max, value = position_min)
|
||||
updateNumericInput(session, "selected_logop_ed_position", min = position_min, max = position_max, value = position_min)
|
||||
updateNumericInput(session, "corr_lig_dist", min = min_ligand_distance, max = max_ligand_distance, value = min_ligand_distance)
|
||||
|
||||
stability_colname = stability_boxes_df[stability_boxes_df$stability_type==input$stability_snp_param,"stability_colname"]
|
||||
outcome_colname = stability_boxes_df[stability_boxes_df$stability_type==input$stability_snp_param,"outcome_colname"]
|
||||
|
||||
display_position_range = input$display_position_range
|
||||
plot_min=display_position_range[1]
|
||||
plot_max=display_position_range[2]
|
||||
|
||||
display_position_full_range = input$display_position_full_range
|
||||
full_range_min=display_position_full_range[1]
|
||||
full_range_max=display_position_full_range[2]
|
||||
|
||||
logoplot_colour_scheme = input$logoplot_colour_scheme
|
||||
omit_snp_count = input$omit_snp_count
|
||||
|
||||
print(paste0('Plotting positions between: ', plot_min, ' and ', plot_max))
|
||||
|
||||
subset_mutable_df3=mutable_df3[(mutable_df3$position>=plot_min & mutable_df3$position <=plot_max),]
|
||||
|
||||
subset_mutable_df3=mutable_df3[(mutable_df3$position>=plot_min & mutable_df3$position <=plot_max),]
|
||||
subset_sorted_df=sorted_df[(sorted_df$position>=plot_min & sorted_df$position <=plot_max),]
|
||||
|
||||
|
||||
|
||||
#### LogoPlotMSA/Logo Plot ED ####
|
||||
output$LogoPlotMSA = renderPlot(
|
||||
LogoPlotMSA(target=input$switch_target,
|
||||
plot_positions=full_range_min:full_range_max,
|
||||
my_logo_col = logoplot_colour_scheme,
|
||||
aa_pos_drug = aa_pos_drug,
|
||||
active_aa_pos = active_aa_pos,
|
||||
aa_pos_lig1 = aa_pos_lig1,
|
||||
aa_pos_lig2 = aa_pos_lig2,
|
||||
aa_pos_lig3 = aa_pos_lig3
|
||||
)
|
||||
)
|
||||
}
|
||||
)
|
||||
}
|
||||
62
msa/ui.R
62
msa/ui.R
|
|
@ -0,0 +1,62 @@
|
|||
dashboardPage(
|
||||
#dashboardHeader(title = paste0(gene, "/", drug)),
|
||||
dashboardHeader(title = "Sequence Alignment"),
|
||||
|
||||
dashboardSidebar(
|
||||
sidebarMenu( id = "sidebar",
|
||||
selectInput(
|
||||
"switch_target",
|
||||
label="Target",
|
||||
choices = c(
|
||||
"alr",
|
||||
"embb",
|
||||
"gid",
|
||||
"katg",
|
||||
"pnca",
|
||||
"rpob"
|
||||
),
|
||||
selected="embb"),
|
||||
menuItem("LogoP ED", tabName="LogoP ED"),
|
||||
|
||||
sliderInput(
|
||||
"display_position_full_range"
|
||||
, "Display Positions"
|
||||
, min=1, max=150, value=c(1,150)
|
||||
),
|
||||
|
||||
conditionalPanel(
|
||||
condition="
|
||||
input.sidebar == 'LogoP SNP' ||
|
||||
input.sidebar == 'LogoP OR' ||
|
||||
input.sidebar == 'LogoP ED'",
|
||||
selectInput(
|
||||
"logoplot_colour_scheme",
|
||||
label="Logo Plot Colour Scheme",
|
||||
choices = logoPlotSchemes,
|
||||
selected="chemistry"
|
||||
)
|
||||
)
|
||||
)
|
||||
),
|
||||
body <- dashboardBody(
|
||||
|
||||
tabItems(
|
||||
tabItem(tabName = "dashboard",
|
||||
h2("Dashboard tab content")
|
||||
),
|
||||
|
||||
tabItem(tabName = "widgets",
|
||||
h2("Widgets tab content")
|
||||
)
|
||||
),
|
||||
# creates a 'Conditional Panel' containing a plot object from each of our
|
||||
# ggplot plot functions (and its associated data frame)
|
||||
fluidRow(
|
||||
column(
|
||||
width=12,
|
||||
plotOutput("LogoPlotMSA",
|
||||
click = "plot_click") %>% withSpinner(color="#0dc5c1")
|
||||
)
|
||||
)
|
||||
)
|
||||
)
|
||||
Loading…
Add table
Add a link
Reference in a new issue