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Tanushree Tunstall 2022-09-04 21:35:08 +01:00
parent d627e88aeb
commit 88aaf56729
3 changed files with 250 additions and 144 deletions
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286
ml/global.R
View file

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

96
ml/server.R
View file

@ -1,6 +1,5 @@
library(shiny) library(shiny)
shinyServer(function(input, output, session) {
shinyServer(function(input, output) {
observeEvent({ observeEvent({
input$combined_model input$combined_model
input$combined_data input$combined_data
@ -20,21 +19,21 @@ shinyServer(function(input, output) {
combined_training_genes = input$combined_training_genes combined_training_genes = input$combined_training_genes
selected_gene = combo[combo$drug == selected_drug,'gene'] selected_gene = combo[combo$drug == selected_drug,'gene']
if (combined_data == "FS"){ # if (combined_data == "FS"){
updateRadioButtons( # updateRadioButtons(
inputId="combined_training_genes", # inputId="combined_training_genes",
choiceNames = c("One", "Two"), # choiceNames = c("One", "Two"),
choiceValues = c("1", "2"), # choiceValues = c("1", "2"),
selected = "2" # selected = "2"
) # )
} else{ # } else{
updateRadioButtons( # updateRadioButtons(
inputId="combined_training_genes", # inputId="combined_training_genes",
choiceNames = c("Five", "Six"), # choiceNames = c("Five", "Six"),
choiceValues = c("5","6"), # choiceValues = c("5","6"),
selected = "5" # selected = "5"
) # )
} # }
# hide stuff if selected # hide stuff if selected
if(combined_model == "combined") { if(combined_model == "combined") {
#if(combined_model == TRUE) { #if(combined_model == TRUE) {
@ -43,23 +42,44 @@ shinyServer(function(input, output) {
#show("resample_dropdown") #show("resample_dropdown")
show("combined_data") show("combined_data")
show("combined_training_genes") show("combined_training_genes")
#show("feature_plot")
filedata = paste0(combined_training_genes, filedata = paste0(combined_training_genes,
'genes_logo_skf_BT_', 'genes_logo_skf_BT_',
selected_gene, selected_gene,
'_', '_',
combined_data combined_data
) )
feature_data = paste0(as.character(as.numeric(combined_training_genes)-4), # lol
'genes_logo_skf_BT_',
selected_gene,
'_FS'
)
print(filedata) print(filedata)
print('doing COMBINED plot') print('doing COMBINED plot')
output$plot <- renderPlot(makeplot(loaded_files[[filedata]], output$plot <- renderPlot(
selection, makeplot(
"none", # always 'none' for combined plot loaded_files[[filedata]],
gene = combo[drug==selected_drug,"gene"], selection,
combined_training_genes = combined_training_genes, resampler,
display_combined = TRUE, gene = combo[drug==selected_drug,"gene"],
combined_training_genes = combined_training_genes,
display_combined = TRUE
),height=450
) )
print("doing FEATURE SELECTION plot corresponding to COMBINED plot")
output$feature_plot <- renderPlot(
makeplot(
loaded_files[[feature_data]],
selection,
"none", # always 'none' for Feature Selection
gene = combo[drug==selected_drug,"gene"],
combined_training_genes = "NO DATA",
display_combined = TRUE
),height=450
) )
# e.g. # e.g.
# makeplot(loaded_files$`5genes_logo_skf_BT_pnca_actual`, "MCC", "none" , gene = 'foo', combined_training_genes = '1234', display_combined = TRUE) # makeplot(loaded_files$`5genes_logo_skf_BT_pnca_actual`, "MCC", "none" , gene = 'foo', combined_training_genes = '1234', display_combined = TRUE)
} else { } else {
@ -67,21 +87,39 @@ shinyServer(function(input, output) {
#show("resample_dropdown") #show("resample_dropdown")
hide("combined_data") hide("combined_data")
hide("combined_training_genes") hide("combined_training_genes")
filedata = paste0(combo[drug==selected_drug,"gene"], #hide("feature_plot")
'_baselineC_',
selected_split filedata = paste0(
combo[drug==selected_drug,"gene"],
'_baselineC_',
selected_split
) )
feature_data = paste0(
combo[drug==selected_drug,"gene"],
'_baselineC_',
selected_split,
"_FS"
)
print(filedata) print(filedata)
print("doing GENE plot") print("doing GENE plot")
output$plot <- renderPlot(makeplot(loaded_files[[filedata]], output$plot <- renderPlot(makeplot(loaded_files[[filedata]],
selection, selection,
resampler, resampler,
gene = combo[drug==selected_drug,"gene"], gene = combo[drug==selected_drug,"gene"],
display_combined = FALSE, display_combined = FALSE
),height=450
) )
print("doing FEATURE SELECTION plot corresponding to GENE plot")
output$feature_plot <- renderPlot(makeplot(loaded_files[[feature_data]],
selection,
"none",
gene = combo[drug==selected_drug,"gene"],
display_combined = FALSE
),height=450
) )
} }
# 6genes_logo_skf_BT_gid_complete # 6genes_logo_skf_BT_gid_complete

12
ml/ui.R
View file

@ -7,7 +7,6 @@ library(ggplot2)
library(grid) # for the info box library(grid) # for the info box
library(plotly) library(plotly)
library(shinycssloaders) library(shinycssloaders)
dashboardPage(skin="purple", dashboardPage(skin="purple",
dashboardHeader(title="Score Selector"), dashboardHeader(title="Score Selector"),
dashboardSidebar( dashboardSidebar(
@ -26,14 +25,14 @@ dashboardPage(skin="purple",
radioButtons("combined_data", radioButtons("combined_data",
label="Data Type", label="Data Type",
choiceNames = c("Complete", "Actual", "Feature Selection"), choiceNames = c("Complete", "Actual"),
choiceValues = c("complete", "actual", "FS"), choiceValues = c("complete", "actual"),
selected="complete" selected="complete"
), ),
radioButtons("combined_training_genes", radioButtons("combined_training_genes",
label="Training Genes", label="Training Genes",
choiceNames = c("One", "Two", "Five", "Six"), choiceNames = c("Five", "Six"),
choiceValues = c("1", "2", "5","6"), choiceValues = c("5","6"),
selected = "5" selected = "5"
), ),
radioButtons("drug_dropdown", radioButtons("drug_dropdown",
@ -60,7 +59,8 @@ dashboardPage(skin="purple",
dashboardBody( dashboardBody(
useShinyjs(), useShinyjs(),
#plotlyOutput("plot", height = 800), #plotlyOutput("plot", height = 800),
plotOutput("plot", height = 800), box(plotOutput("plot"), width="100%"),
box(plotOutput("feature_plot"), width="100%", title="Feature Selection"),
# %>% withSpinner(color="#0dc5c1"), # uncomment if you want the spinner # %>% withSpinner(color="#0dc5c1"), # uncomment if you want the spinner
#downloadButton("save", "Download Plot"), #downloadButton("save", "Download Plot"),
#DT::dataTableOut("plotdata"), #DT::dataTableOut("plotdata"),