thing
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3 changed files with 250 additions and 144 deletions
286
ml/global.R
286
ml/global.R
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@ -40,6 +40,12 @@ split_file = c(
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"_none_complete"
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)
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split_file_FS = c(
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"_70_30_complete",
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"_80_20_complete",
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"_sl_complete"
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)
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# necessary because the names will be wrong otherwise
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split_map = data.frame(
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files=c(
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@ -82,6 +88,23 @@ for (x in gene) {
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try({loaded_files[[load_name]] = read.csv(filename)})
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}
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}
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# Loader for per-gene Feature Selection CSVs
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for (x in gene) {
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#x=tolower(x)
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for (split in split_file_FS){
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filedata = paste0(x, split)
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filename = paste0(data_dir,'LSHTM_ML/output/genes/',x,split,'_FS.csv')
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#print(c(filename))
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#load_name=paste0(combo[gene==x,"drug"],'_',split_map['splits'][split_map['files']==split])
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load_name=paste0(x,'_baselineC_',split_map['splits'][split_map['files']==split], '_FS')
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print(load_name)
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# try() on its own is fine here because we don't need to do anything if it fails
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try({loaded_files[[load_name]] = read.csv(filename)})
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}
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}
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# Funky loader for combined data
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for (x in gene) {
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for (ac in c('_actual','_complete', '_FS')){
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@ -104,7 +127,9 @@ for (x in gene) {
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scores=c("F1", "ROC_AUC", "JCC", "MCC", "Accuracy", "Recall", "Precision")
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resample_types <<- unique(thing$resampling)
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#resample_types <<- unique(thing$resampling)
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resample_types = c("none", "Random Oversampling", "Over+Under", "Random Undersampling", "SMOTE")
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makeplot = function(x, # the DataFrame to plot
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selection, # scoring method e.g. 'MCC'
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@ -152,21 +177,24 @@ makeplot = function(x, # the DataFrame to plot
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)
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)
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}
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ggplot(data=plot_data, aes_string(x="Model_name",
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y=selection,
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fill="source_data",
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group=selection) ) +
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geom_bar(stat="identity"
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, width = 0.75
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, position=position_dodge2(padding=0.1, preserve='total', reverse=TRUE)
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ggplot(
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data=plot_data, aes_string(
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x="Model_name",
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y=selection,
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fill="source_data" #,
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#group=selection
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)
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) +
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geom_bar(
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stat="identity"
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, width = 0.75
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, position=position_dodge2(padding=0.1, preserve='total', reverse=TRUE)
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) +
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coord_cartesian(ylim = c(y_coord_min, 1)) +
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annotation_custom(grob) +
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# doesn't work with plotly but looks nice :-(
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geom_label(aes_string(label=selection),
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position=position_dodge(width = -0.75),
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#position=position_dodge2(padding=0.1),
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vjust = 1.5,
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#vjust = 1.5,
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alpha=0.75,
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fill="white"
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@ -174,107 +202,15 @@ makeplot = function(x, # the DataFrame to plot
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scale_color_manual(values = colour_range) +
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scale_fill_manual(values = colour_range) +
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# add little numbers for the BT bars only
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labs(x="",y=paste(selection,"Score")) +
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theme(
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axis.text.x = element_text(angle = 90),
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)
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# ggplotly()
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}
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if (interactive()){
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server=shinyServer(function(input, output) {
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observeEvent({
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input$combined_model
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input$combined_data
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input$combined_training_genes
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input$score_dropdown
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input$resample_dropdown
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input$drug_dropdown
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input$split_dropdown
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},{
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combined_model = input$combined_model
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selection = input$score_dropdown
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resampler = input$resample_dropdown
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selected_drug = input$drug_dropdown
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selected_split = input$split_dropdown
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combined_data = input$combined_data
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combined_training_genes = input$combined_training_genes
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selected_gene = combo[combo$drug == selected_drug,'gene']
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if (combined_data == "FS"){
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updateRadioButtons(
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inputId="combined_training_genes",
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choiceNames = c("One", "Two"),
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choiceValues = c("1", "2"),
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selected = "2"
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)
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} else{
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updateRadioButtons(
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inputId="combined_training_genes",
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choiceNames = c("Five", "Six"),
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choiceValues = c("5","6"),
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selected = "5"
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)
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}
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# hide stuff if selected
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if(combined_model == "combined") {
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#if(combined_model == TRUE) {
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hide("split_dropdown")
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#show("resample_dropdown")
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show("combined_data")
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show("combined_training_genes")
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filedata = paste0(combined_training_genes,
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'genes_logo_skf_BT_',
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selected_gene,
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'_',
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combined_data
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)
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print(filedata)
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print('doing COMBINED plot')
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output$plot <- renderPlot(makeplot(loaded_files[[filedata]],
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selection,
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"none", # always 'none' for combined plot
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gene = combo[drug==selected_drug,"gene"],
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combined_training_genes = combined_training_genes,
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display_combined = TRUE,
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)
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)
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# e.g.
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# makeplot(loaded_files$`5genes_logo_skf_BT_pnca_actual`, "MCC", "none" , gene = 'foo', combined_training_genes = '1234', display_combined = TRUE)
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} else {
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show("split_dropdown")
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#show("resample_dropdown")
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hide("combined_data")
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hide("combined_training_genes")
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filedata = paste0(combo[drug==selected_drug,"gene"],
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'_baselineC_',
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selected_split
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)
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print(filedata)
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print("doing GENE plot")
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output$plot <- renderPlot(makeplot(loaded_files[[filedata]],
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selection,
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resampler,
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gene = combo[drug==selected_drug,"gene"],
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display_combined = FALSE,
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)
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)
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}
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# 6genes_logo_skf_BT_gid_complete
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# filedata example for combined: 6genes_logo_skf_BT_embb_actual
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# 6genes_logo_skf_BT_embb_combined
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})
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}
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)
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ui=dashboardPage(skin="purple",
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dashboardHeader(title="Score Selector"),
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dashboardSidebar(
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@ -293,14 +229,14 @@ if (interactive()){
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radioButtons("combined_data",
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label="Data Type",
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choiceNames = c("Complete", "Actual", "Feature Selection"),
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choiceValues = c("complete", "actual", "FS"),
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choiceNames = c("Complete", "Actual"),
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choiceValues = c("complete", "actual"),
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selected="complete"
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),
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radioButtons("combined_training_genes",
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label="Training Genes",
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choiceNames = c("One", "Two", "Five", "Six"),
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choiceValues = c("1", "2", "5","6"),
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choiceNames = c("Five", "Six"),
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choiceValues = c("5","6"),
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selected = "5"
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),
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radioButtons("drug_dropdown",
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@ -327,13 +263,145 @@ if (interactive()){
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dashboardBody(
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useShinyjs(),
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#plotlyOutput("plot", height = 800),
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plotOutput("plot", height = 800),
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box(plotOutput("plot"), width="100%"),
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box(plotOutput("feature_plot"), width="100%", title="Feature Selection"),
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# %>% withSpinner(color="#0dc5c1"), # uncomment if you want the spinner
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#downloadButton("save", "Download Plot"),
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#DT::dataTableOut("plotdata"),
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verbatimTextOutput("debug")
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)
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)
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server=shinyServer(function(input, output, session) {
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observeEvent({
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input$combined_model
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input$combined_data
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input$combined_training_genes
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input$score_dropdown
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input$resample_dropdown
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input$drug_dropdown
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input$split_dropdown
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},{
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combined_model = input$combined_model
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selection = input$score_dropdown
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resampler = input$resample_dropdown
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selected_drug = input$drug_dropdown
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selected_split = input$split_dropdown
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combined_data = input$combined_data
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combined_training_genes = input$combined_training_genes
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selected_gene = combo[combo$drug == selected_drug,'gene']
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# if (combined_data == "FS"){
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# updateRadioButtons(
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# inputId="combined_training_genes",
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# choiceNames = c("One", "Two"),
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# choiceValues = c("1", "2"),
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# selected = "2"
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# )
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# } else{
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# updateRadioButtons(
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# inputId="combined_training_genes",
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# choiceNames = c("Five", "Six"),
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# choiceValues = c("5","6"),
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# selected = "5"
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# )
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# }
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# hide stuff if selected
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if(combined_model == "combined") {
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#if(combined_model == TRUE) {
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hide("split_dropdown")
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#show("resample_dropdown")
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show("combined_data")
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show("combined_training_genes")
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#show("feature_plot")
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filedata = paste0(combined_training_genes,
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'genes_logo_skf_BT_',
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selected_gene,
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'_',
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combined_data
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)
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feature_data = paste0(as.character(as.numeric(combined_training_genes)-4), # lol
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'genes_logo_skf_BT_',
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selected_gene,
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'_FS'
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)
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print(filedata)
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print('doing COMBINED plot')
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output$plot <- renderPlot(
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makeplot(
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loaded_files[[filedata]],
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selection,
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resampler,
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gene = combo[drug==selected_drug,"gene"],
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combined_training_genes = combined_training_genes,
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display_combined = TRUE
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),height=450
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)
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print("doing FEATURE SELECTION plot corresponding to COMBINED plot")
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output$feature_plot <- renderPlot(
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makeplot(
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loaded_files[[feature_data]],
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selection,
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"none", # always 'none' for Feature Selection
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gene = combo[drug==selected_drug,"gene"],
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combined_training_genes = "NO DATA",
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display_combined = TRUE
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),height=450
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)
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# e.g.
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# makeplot(loaded_files$`5genes_logo_skf_BT_pnca_actual`, "MCC", "none" , gene = 'foo', combined_training_genes = '1234', display_combined = TRUE)
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} else {
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show("split_dropdown")
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#show("resample_dropdown")
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hide("combined_data")
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hide("combined_training_genes")
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#hide("feature_plot")
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filedata = paste0(
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combo[drug==selected_drug,"gene"],
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'_baselineC_',
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selected_split
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)
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feature_data = paste0(
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combo[drug==selected_drug,"gene"],
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'_baselineC_',
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selected_split,
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"_FS"
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)
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print(filedata)
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print("doing GENE plot")
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output$plot <- renderPlot(makeplot(loaded_files[[filedata]],
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selection,
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resampler,
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gene = combo[drug==selected_drug,"gene"],
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display_combined = FALSE
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),height=450
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)
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print("doing FEATURE SELECTION plot corresponding to GENE plot")
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output$feature_plot <- renderPlot(makeplot(loaded_files[[feature_data]],
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selection,
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"none",
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gene = combo[drug==selected_drug,"gene"],
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display_combined = FALSE
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),height=450
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)
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}
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# 6genes_logo_skf_BT_gid_complete
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# filedata example for combined: 6genes_logo_skf_BT_embb_actual
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# 6genes_logo_skf_BT_embb_combined
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})
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}
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)
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app <- shinyApp(ui, server)
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runApp(app)
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}
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