Nothing
ui.modules_pcawg_unicox <- function(id) {
ns <- NS(id)
fluidPage(
fluidRow(
column(
3,
wellPanel(
shinyWidgets::prettyRadioButtons(
inputId = ns("profile"), label = "Select a genomic profile:",
choiceValues = c(
"mRNA", "miRNA_TMM", "miRNA_UQ",
"promoter_raw", "promoter_relative", "promoter_outlier",
"fusion", "APOBEC"
),
choiceNames = c(
"mRNA Expression", "miRNA Expression (TMM)",
"miRNA Expression (UQ)",
"Raw Promoter Activity",
"Relative Promoter Activity",
"Promoter Outlier",
"Gene Fusion",
"APOBEC mutagenesis"
),
animation = "jelly"
),
selectizeInput(
inputId = ns("Pancan_search"),
label = "Input a gene or formula (as signature)",
choices = NULL,
width = "100%",
options = list(
create = TRUE,
maxOptions = 5,
placeholder = "Enter a gene symbol, e.g. TP53",
plugins = list("restore_on_backspace")
)
),
# selectInput(inputId = ns("measure"), label = "Select Measure for plot", choices = c("OS", "PFI", "DSS", "DFI"), selected = "OS"),
selectInput(inputId = ns("threshold"), label = "Select Threshold for plot", choices = c(0.25, 0.5), selected = 0.5),
colourpicker::colourInput(inputId = ns("first_col"), "First color", "#6A6F68"),
colourpicker::colourInput(inputId = ns("second_col"), "Second color", "#E31A1C"),
colourpicker::colourInput(inputId = ns("third_col"), "Third color", "#377DB8"),
tags$hr(style = "border:none; border-top:2px solid #5E81AC;"),
shinyWidgets::actionBttn(
inputId = ns("search_bttn"),
label = "Go!",
style = "gradient",
icon = icon("search"),
color = "primary",
block = TRUE,
size = "sm"
)),
wellPanel(
numericInput(inputId = ns("height"), label = "Height", value = 8),
numericInput(inputId = ns("width"), label = "Width", value = 6),
prettyRadioButtons(
inputId = ns("device"),
label = "Choose plot format",
choices = c("pdf", "png"),
selected = "pdf",
inline = TRUE,
icon = icon("check"),
animation = "jelly",
fill = TRUE
),
downloadBttn(
outputId = ns("download"),
style = "gradient",
color = "default",
block = TRUE,
size = "sm"
)
)
),
column(
9,
plotOutput(ns("unicox_gene_tree"), height = "500px",width = "350px"),
hr(),
h5("NOTEs:"),
p("1. We define gene in certain cancer type as risky (log(Hazard Ratio) > 0) or protective (log(Hazard Ratio) < 0) or NS (No statistical significance, P value > 0.05)"),
p("2. We divide patients into different groups for comparison according to gene expression, you could choose the threshold for grouping (0.5 by default)"),
p("3. ", tags$a(href = "https://xenabrowser.net/datapages/?cohort=PCAWG%20(specimen%20centric)&removeHub=https%3A%2F%2Fxena.treehouse.gi.ucsc.edu%3A443&removeHub=https%3A%2F%2Fatacseq.xenahubs.net", "Genomic profile data source")),
DT::DTOutput(outputId = ns("tbl")),
shinyjs::hidden(
wellPanel(
id = ns("save_csv"),
downloadButton(ns("downloadTable"), "Save as csv")
)
)
)
)
)
}
server.modules_pcawg_unicox <- function(input, output, session) {
ns <- session$ns
profile_choices <- reactive({
switch(input$profile,
mRNA = list(all = pancan_identifiers$gene, default = "TP53"),
miRNA_TMM = list(all = pancan_identifiers$miRNA, default = "hsa-miR-769-3p"),
miRNA_UQ = list(all = pancan_identifiers$miRNA, default = "hsa-miR-769-3p"),
promoter_raw = list(all = names(load_data("pcawg_promoter_id")), default = "1:169863093:SCYL3"),
promoter_relative = list(all = names(load_data("pcawg_promoter_id")), default = "1:169863093:SCYL3"),
promoter_outlier = list(all = names(load_data("pcawg_promoter_id")), default = "1:169863093:SCYL3"),
fusion = list(all = pancan_identifiers$gene, default = "DPM1"),
APOBEC = list(all = c(
"tCa_MutLoad_MinEstimate", "APOBECtCa_enrich",
"A3A_or_A3B", "APOBEC_tCa_enrich_quartile", "APOBECrtCa_enrich",
"APOBECytCa_enrich", "APOBECytCa_enrich-APOBECrtCa_enrich",
"BH_Fisher_p-value_tCa", "ntca+tgan", "rtCa_to_G+rtCa_to_T",
"rtca+tgay", "tCa_to_G+tCa_to_T",
"ytCa_rtCa_BH_Fisher_p-value", "ytCa_rtCa_Fisher_p-value", "ytCa_to_G+ytCa_to_T",
"ytca+tgar"
), default = "APOBECtCa_enrich"),
list(all = "NONE", default = "NONE")
)
})
observe({
updateSelectizeInput(
session,
"Pancan_search",
choices = profile_choices()$all,
selected = profile_choices()$default,
server = TRUE
)
})
# Show waiter for plot
w <- waiter::Waiter$new(id = ns("unicox_gene_tree"), html = waiter::spin_hexdots(), color = "white")
colors <- reactive({
c(input$first_col, input$second_col, input$third_col)
})
observeEvent(input$search_bttn, {
if (nchar(input$Pancan_search) >= 1) {
shinyjs::show(id = "save_csv")
} else {
shinyjs::hide(id = "save_csv")
}
})
plot_func <- eventReactive(input$search_bttn, {
if (nchar(input$Pancan_search) >= 1) {
p <- vis_pcawg_unicox_tree(
Gene = input$Pancan_search,
# measure = input$measure,
threshold = input$threshold,
data_type = input$profile,
values = colors()
)
pdata <- p$data %>%
as.data.frame() %>%
dplyr::select(cancer, measure, n_contrast, n_ref, beta, HR_log, lower_95_log, upper_95_log, Type, p.value)
return(list(plot = p, data = pdata))
}
})
output$unicox_gene_tree <- renderPlot({
w$show() # Waiter add-ins
plot_func()$plot
})
output$download <- downloadHandler(
filename = function() {
paste0(input$Pancan_search, "_", input$profile, "_", input$measure, "_pcawg_unicox.", input$device)
},
content = function(file) {
p <- plot_func()$plot
if (input$device == "pdf") {
pdf(file, width = input$width, height = input$height)
print(p)
dev.off()
} else {
png(file, width = input$width, height = input$height, res = 600, units = "in")
print(p)
dev.off()
}
}
)
output$tbl <- renderDT(
plot_func()$data,
options = list(lengthChange = FALSE)
)
output$downloadTable <- downloadHandler(
filename = function() {
paste0(input$Pancan_search, "_", input$profile, "_", input$measure, "_pcawg_unicox.csv")
},
content = function(file) {
write.csv(plot_func()$data, file, row.names = FALSE)
}
)
}
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