inst/shiny/ui.R
In bioinformatist/CrossICC: An Interactive Consensus Clustering Framework for Multi-platform Data Analysis
options(spinner.type=4)
#required packages
suppressMessages(library(shiny))
suppressMessages(library(shinydashboard))
suppressMessages(library(shinyWidgets))
suppressMessages(library(shinycssloaders))
suppressMessages(library(DT))
#sider bar----
sidebar <- dashboardSidebar(width = 300,
sidebarMenu(id="sidername",selected='home',
menuItem("Home", tabName = "home", icon = icon("home")),
menuItem("CrossICC result viewer", icon = icon("eye"),tabName = "CrossICC"),
menuItem("Allocate New Sample", icon = icon("location-arrow"),tabName = "predict" ),
menuItem('Correlation analysis', tabName = 'correlation',icon = icon("th",lib = "glyphicon")),
menuItem('ssGSEA analysis', tabName = 'ssgsea',icon = icon("bar-chart")),
menuItem('Survival analysis', tabName = 'Survival',icon = icon("line-chart"))
)
)
#bodyHome ----
bodyHome <- tabItem("home",
fluidRow(
box(
width = 12,
status = "success",
solidHeader = TRUE,
title = strong("Wellcome to the CrossICC reporter"),
includeMarkdown("dom/Readmeshiny.md")
)
),
fluidRow(
box(
width = 4,
status = "info",
solidHeader = TRUE,
title = strong("CrossICC result viewer"),
p("This module provide several plot functions to help inteprate CrossICC result."),
img(src = "images/home_crossICC.png", align = "center", width="100%")
),
box(
width = 4,
status = "info",
solidHeader = TRUE,
title = strong("New sample allocator"),
p("After obtain a cluster system based on trained data, it would be applicable if we are going to allocate new samples.
In this module, users are encoraged uploading expression data of testing samples to figure out which cluster they belong to."),
img(src = "images/workflow.png", align = "center", width="100%")
),
box(
width = 4,
status = "info",
solidHeader = TRUE,
title = strong("Cancer related analysis functions"),
includeMarkdown("dom/home_cancerR.md"),
img(src = "images/cancerRelated.png", align = "center", width="100%")
)
),
fluidRow(
box(
width = 12,
status = "warning",
solidHeader = TRUE,
title = strong("Citation"),
h4("If you use CrossICC, please cite this paper:"),
p("Preparing in process")
)
))
#bodyCrossICC ----
bodyCrossICC <- tabItem("CrossICC",
h2("Visualize CrossICC object"),
fluidRow(
#setting panel
box(
title = div(shiny::icon("gear"), "Data upload & Configuration", inline =TRUE),
width = 3,
tabBox (
height = "100%", width = "100%",
id = "crossICCsettingPanel",
title = "",
side = "left",
selected = "crs01",
tabPanel(
title = div(icon("book"), "Upload"),
value = "crs01",
radioButtons(
"dataset",
strong("Loading CrossICC output"),
inline = TRUE,
c(Default = "default", Upload = "upload"),
selected = 'default'
),
conditionalPanel(
condition = "input.dataset == 'upload'",
fileInput(
'file1','CrossICC output data in RDS format',accept = c('application/rds', '.rds')
)
),
actionBttn("submit", div(
"Click ME to visualize result ",
icon("hand-right", lib = "glyphicon")
)),
div(align = 'center',h4("Your running parameters "), tableOutput("outputArguments"))
),
tabPanel(
title = div(icon("book"), "Setting"),
value = "crs02",
fluidRow(
switchInput(
inputId = "clusterRow",
label = "Cluster by Rows",
value = FALSE
),
switchInput(
inputId = "showRowNames",
label = "show row names",
value = FALSE
)
),
sliderInput("cross_size", "Zoom in/out graph:",min = 500, max = 1000, value = 800)
)
)
),
box(
width = 9,
title = "Visualization",
tabBox (
height = "100%", width = "100%",
id = "crossICCresultPanel",
side = "left",
selected = "cr06",
tabPanel(
title = div(icon("book"), "Summary"),
value = "cr01",
dataTableOutput("OutputResultSignature"),
box(
width = NULL, status = "success",
h4("Download Clustering result"),
downloadButton("OutputClusterResult"),
h4("Gene signature for each cluster"),
downloadButton("geneSignature", label = "Download Matrix")
)
),
tabPanel(
title = div(icon("th", lib = "glyphicon"), "Super Clustering"),
value = "cr02",
withSpinner(plotOutput("superclusterPlot", height = "100%"), color = "black"),
box(
width = NULL, status = "success",
radioButtons("DownloadSuperclusterPlotCheck","Choose file type to download:",
c("png", "pdf", "tiff"),inline = TRUE
),
downloadButton('DownloadSuperclusterPlot', 'Download')
)
),
tabPanel(
title = div(icon("signal", lib = "glyphicon"), "Silhouette Result"),
value = "cr03",
withSpinner(plotOutput("Silhouette",height = "100%"), color = "black")
,
box(
width = NULL, status = "success",
radioButtons("DownloadSilhouetteCheck","Choose file type to download:",
c("png", "pdf", "tiff"),inline = TRUE
),
downloadButton('DownloadSilhouette', 'Download Plot')
)
),
tabPanel(
title = div(icon("book"), "Expression heatmap by signagure"),
value = "cr04",
uiOutput("expressionHeatmapSelectPlatform"),
withSpinner(plotOutput("clusterexpress",height = "100%"), color = "black"),
box(
width = NULL, status = "success",
radioButtons("DownloadClusterexpressPlotCheck","Choose file type to download:",
c("png", "pdf", "tiff"),inline = TRUE
),
downloadButton('DownloadClusterexpressPlot', 'Download Plot'),
downloadButton('DownloadClusterExpressMatrix', 'Download Matrix')
)
),
tabPanel(
title = div(icon("book"), "Iteration Record"),
value = "cr05",
plotOutput("IterationPlot", height = "100%"),
box(
width = NULL, status = "success",
radioButtons("DownloadIterationPlotCheck","Choose file type to download:",
c("png", "pdf", "tiff"),inline = TRUE
)
# to be added
)
),
tabPanel(
title = div(icon("book"), "Readme"),
value = "cr06",
includeMarkdown("dom/CrossICCObject.Rmd")
)
)
)
))
#bodyPredict----
bodyPredict <- tabItem(
"predict",
h2("Allocate new samples with their expression value"),
fluidRow(
#setting panel
box(
title = "Input your data set for prediction",
background = "black",
width = 3,
radioButtons(
"dataset2",
strong("Data to predict"),
inline = TRUE,
c(Default = "default", Upload = "upload"),
selected = 'default'
),
conditionalPanel(
condition = "input.dataset2 == 'upload'",
fileInput(
'file2',
'Input dataset in matrix file',
accept = c('text/txt', c('.rds','.csv','.txt'))
),
downloadLink('DownloadPredictExampleFile', 'See example file ')
),
actionBttn("submit2", "Submit")
),
tabBox (
id = "PredictResultPanel",
title = h3("Analysis"),
width =9,
side = "right",
selected = "pre02",
tabPanel(
title = div(icon("book"), "PredictResult"),
value = "pre01",
downloadLink('DownloadPredictHeatmap', 'Download PDF'),
downloadLink('DownloadPredictClusterResult', 'Download Predicted Cluster Result'),
withSpinner(plotOutput("predictHeatmap", height = "800px"), color = "black")
),
tabPanel(
title = div(icon("book"), "Readme"),
value = "pre02",
includeMarkdown("dom/predict.Rmd")
)
)
)
)
# bodyCorrelation----
bodyCorrelation <- tabItem(
"correlation",
h2("Correlation analysis of the two cluster system"),
fluidRow(
valueBoxOutput("getRAbox", width = 4),
valueBoxOutput("getARIbox", width = 4),
valueBoxOutput("getJaccarddox", width = 4)
),
fluidRow(
box( width = 3,
title = "Analysis",
tabBox (
height = "100%", width = "100%",
selected = "caInput01",
side = "left",
tabPanel(
title = div(icon("table"), "Data Input"),
value = "caInput01",
radioGroupButtons(
"data3",
label = strong("clinical Dataset"),
choices = c(Default = "Default", Upload = "Upload"),
selected = 'Default',
status = "primary"
),
conditionalPanel(
condition = "input.data3 == 'Upload'",
fileInput(
'file3',
'Input dataset in matrix file',
accept =
c('text/txt', '.csv')
)
),
uiOutput("VariableSelectionUI1"),
uiOutput("VariableSelectionUI2"),
actionBttn("submit3", "Submit", style = "unite")
),
tabPanel(
title = div(icon("cog"), "Setting"),
value = "caInput01",
selectInput("cor_theme", "Plot Theme:",
c("default","Tufte","Economist","Solarized","Stata","Excel 2003","Inverse Gray","Fivethirtyeight","Tableau","Stephen","Wall Street","GDocs","Calc","Pander","Highcharts"))
,
sliderInput("corre_size", "Zoom in/out graph:",min = 500, max = 1000, value = 800)
)
)
),
box( width =9,
title = "Analysis",
tabBox (
height = "100%", width = "100%",
id = "clinicalResultPanel",
side = "left",
selected = "ca04",
tabPanel(
title = div(icon("book"), "Data"),
value = "ca01",
h3("Input Data "),
dataTableOutput("summaryCorrelationData")
),
tabPanel(title = div(icon("book"), "Contingency Table "),
value ="ca02",
dataTableOutput("ContingencyTableRender")
),
tabPanel(
title = div(icon("book"), "Plot"),
value = "ca03",
withSpinner(plotOutput("getCorplotRender",height = "100%"), color = "black"),
box(
width = NULL, status = "success",
radioButtons("DownloadCorrelationPlotCheck","Choose file type to download:",
c("png", "pdf", "tiff"),inline = TRUE,selected = "pdf"
),
downloadBttn('DownloadCorrelationPlot', 'Download')
# to be added
)
),
tabPanel(
title = div(icon("book"), "SankeyPlot"),
value = "ca04",
withSpinner(plotOutput("getSankyPlotRender",height = "100%"), color = "black"),
box(
width = NULL, status = "success",
radioButtons("DownloadsankeyPlotCheck","Choose file type to download:",
c("png", "pdf", "tiff"),inline = TRUE,selected = "pdf"
),
downloadBttn('DownloadSankeyPlot', 'Download')
# to be added
)
),
tabPanel(
title = div(icon("book"), "Read Me"),
value = "ca04",
includeMarkdown("dom/correlation.Rmd")
# ,includeHTML("dom/correlation.html")
)
)
)
)
)
# bodySsGSEA ----
bodySsGSEA <- tabItem("ssgsea",
h2("ssGSEA analysis"),
fluidRow(
#setting panel
box(
title = "Input dataset",
width = 3,
tabBox (id = "ssGseaSettingPanel",side = "left", selected = "ssgseaset01",
height = "100%", width = "100%",
tabPanel(
title = div(icon("book"), "Loading"),
value = "ssgseaset01",
# ssgsea data
radioGroupButtons(
"ssGSEAdata",
label = strong("Expression Data"),
choices = c(Example = "Example", Upload = "Upload"),
selected = 'Example',
status = "primary"
),
conditionalPanel(
condition = "input.ssGSEAdata == 'Upload'",
fileInput(
'ssGSEAdatafile',
'Input dataset in matrix file',
accept =
c('text/txt', '.csv')
)
),
radioGroupButtons(
"ssGSEASet",
label = strong("GENE SET"),
choices = c(KEGG = "KEGG",Default= "Default",Upload = "Upload"),
selected = 'Default',
status = "primary"
),
conditionalPanel(
condition = "input.ssGSEASet == 'Upload'",
fileInput(
'ssGSEAgenesetfile',
'Input Geneset file',
accept =
c('text/txt', '.csv')
)
)
),
tabPanel(
title = div(icon("book"), "Setting"),
value = "ssgseaset02",
sliderInput("ssgsea_size", "Zoom in/out graph:",min = 500, max = 1000, value = 800)
)
)
),
box(
title = "Analysis Result",
width =9,
tabBox (
height = "100%", width = "100%",
id = "ssGseaResultPanel", side = "left",selected = "ssgseaRes03",
tabPanel(
title = div(icon("book"), "Out Table"),
value = "ssgseaRes01",
dataTableOutput("ssGSEAmatrix")
),
tabPanel(
title = div(icon("book"), "Plot"),
value = "ssgseaRes02"
),
tabPanel(
title = div(icon("book"), "Read Me"),
value = "ssgseaRes03"
,includeMarkdown("dom/ssGSEA.Rmd")
)
)
)
))
# bodySurvival ----
bodySurival <- tabItem(
"Survival",
h2("Survival evaluation of the clustering system"),
fluidRow(
#setting panel
box(
title = "Input dataset",
width = 3,
tabBox (id = "SurvivalSettingPanel" , side = "left",selected = "survivalset01",
height = "100%", width = "100%",
tabPanel(
title = div(icon("book"), "Loading"),
value = "survivalset01",
radioGroupButtons(
"data5",
label = strong("Survival Dataset"),
choices = c(Default = "Default", Upload = "Upload"),
selected = 'Default',
status = "primary"
),
conditionalPanel(
condition = "input.data5 == 'Upload'",
fileInput(
'survivalFile',
'Input dataset in matrix file',
accept =
c('text/txt', '.csv')
)
),
uiOutput("survivalFeatureSelect1"),
uiOutput("survivalTimeSelect1"),
uiOutput("survivalStatusSelect1"),
actionBttn("submit5", "Submit", style = "unite")
),
tabPanel(
title = div(icon("book"), "Setting"),
value = "survivalset02",
sliderInput("survival_size", "Zoom in/out graph:",min = 500, max = 1000, value = 800)
)
)
),
box(
title = "Analysis Result",
width =9,
tabBox (id = "survivalResultPanel", side = "left", selected = "survivalRes03",
height = "100%", width = "100%",
tabPanel(
title = div(icon("book"), " Dataset"),
value = "survivalRes01",
dataTableOutput("survivalData")
# , includeHTML("dom/survival.html")
),
tabPanel(
title = div(icon("book"), "Plot"),
value = "survivalRes02",
withSpinner(plotOutput("SurvivalPlotRender",height = "100%"), color = "black"),
box(
width = NULL, status = "success",
radioButtons("DownloadSurvivalPlotCheck","Choose file type to download:",
c("png", "pdf", "tiff"),inline = TRUE,selected = "pdf"
),
downloadBttn('DowloadSurvival', 'Download')
# to be added
)
),
tabPanel(
title = div(icon("book"), "Read Me"),
value = "survivalRes03",
includeMarkdown("dom/survival.Rmd")
# , includeHTML("dom/survival.html")
)
)
)
)
)
#-----------
#Main function----
shinyUI(dashboardPage(skin = "black",
dashboardHeader(title = "CrossICC: iterative consensus clustering of cross-platform data",
titleWidth = 600
),
sidebar,
dashboardBody(
tags$head(
tags$style(HTML("
.shiny-output-error-validation {
color: brown;
}
")),
tags$link(rel = "stylesheet", type = "text/css", href = "css/main.css")
),
tabItems(
bodyHome,
bodyCrossICC,
bodyPredict,
bodyCorrelation,
bodySsGSEA,
bodySurival
)
)
))
bioinformatist/CrossICC documentation built on Feb. 3, 2022, 8:58 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
options(spinner.type=4)
#required packages
suppressMessages(library(shiny))
suppressMessages(library(shinydashboard))
suppressMessages(library(shinyWidgets))
suppressMessages(library(shinycssloaders))
suppressMessages(library(DT))
#sider bar----
sidebar <- dashboardSidebar(width = 300,
sidebarMenu(id="sidername",selected='home',
menuItem("Home", tabName = "home", icon = icon("home")),
menuItem("CrossICC result viewer", icon = icon("eye"),tabName = "CrossICC"),
menuItem("Allocate New Sample", icon = icon("location-arrow"),tabName = "predict" ),
menuItem('Correlation analysis', tabName = 'correlation',icon = icon("th",lib = "glyphicon")),
menuItem('ssGSEA analysis', tabName = 'ssgsea',icon = icon("bar-chart")),
menuItem('Survival analysis', tabName = 'Survival',icon = icon("line-chart"))
)
)
#bodyHome ----
bodyHome <- tabItem("home",
fluidRow(
box(
width = 12,
status = "success",
solidHeader = TRUE,
title = strong("Wellcome to the CrossICC reporter"),
includeMarkdown("dom/Readmeshiny.md")
)
),
fluidRow(
box(
width = 4,
status = "info",
solidHeader = TRUE,
title = strong("CrossICC result viewer"),
p("This module provide several plot functions to help inteprate CrossICC result."),
img(src = "images/home_crossICC.png", align = "center", width="100%")
),
box(
width = 4,
status = "info",
solidHeader = TRUE,
title = strong("New sample allocator"),
p("After obtain a cluster system based on trained data, it would be applicable if we are going to allocate new samples.
In this module, users are encoraged uploading expression data of testing samples to figure out which cluster they belong to."),
img(src = "images/workflow.png", align = "center", width="100%")
),
box(
width = 4,
status = "info",
solidHeader = TRUE,
title = strong("Cancer related analysis functions"),
includeMarkdown("dom/home_cancerR.md"),
img(src = "images/cancerRelated.png", align = "center", width="100%")
)
),
fluidRow(
box(
width = 12,
status = "warning",
solidHeader = TRUE,
title = strong("Citation"),
h4("If you use CrossICC, please cite this paper:"),
p("Preparing in process")
)
))
#bodyCrossICC ----
bodyCrossICC <- tabItem("CrossICC",
h2("Visualize CrossICC object"),
fluidRow(
#setting panel
box(
title = div(shiny::icon("gear"), "Data upload & Configuration", inline =TRUE),
width = 3,
tabBox (
height = "100%", width = "100%",
id = "crossICCsettingPanel",
title = "",
side = "left",
selected = "crs01",
tabPanel(
title = div(icon("book"), "Upload"),
value = "crs01",
radioButtons(
"dataset",
strong("Loading CrossICC output"),
inline = TRUE,
c(Default = "default", Upload = "upload"),
selected = 'default'
),
conditionalPanel(
condition = "input.dataset == 'upload'",
fileInput(
'file1','CrossICC output data in RDS format',accept = c('application/rds', '.rds')
)
),
actionBttn("submit", div(
"Click ME to visualize result ",
icon("hand-right", lib = "glyphicon")
)),
div(align = 'center',h4("Your running parameters "), tableOutput("outputArguments"))
),
tabPanel(
title = div(icon("book"), "Setting"),
value = "crs02",
fluidRow(
switchInput(
inputId = "clusterRow",
label = "Cluster by Rows",
value = FALSE
),
switchInput(
inputId = "showRowNames",
label = "show row names",
value = FALSE
)
),
sliderInput("cross_size", "Zoom in/out graph:",min = 500, max = 1000, value = 800)
)
)
),
box(
width = 9,
title = "Visualization",
tabBox (
height = "100%", width = "100%",
id = "crossICCresultPanel",
side = "left",
selected = "cr06",
tabPanel(
title = div(icon("book"), "Summary"),
value = "cr01",
dataTableOutput("OutputResultSignature"),
box(
width = NULL, status = "success",
h4("Download Clustering result"),
downloadButton("OutputClusterResult"),
h4("Gene signature for each cluster"),
downloadButton("geneSignature", label = "Download Matrix")
)
),
tabPanel(
title = div(icon("th", lib = "glyphicon"), "Super Clustering"),
value = "cr02",
withSpinner(plotOutput("superclusterPlot", height = "100%"), color = "black"),
box(
width = NULL, status = "success",
radioButtons("DownloadSuperclusterPlotCheck","Choose file type to download:",
c("png", "pdf", "tiff"),inline = TRUE
),
downloadButton('DownloadSuperclusterPlot', 'Download')
)
),
tabPanel(
title = div(icon("signal", lib = "glyphicon"), "Silhouette Result"),
value = "cr03",
withSpinner(plotOutput("Silhouette",height = "100%"), color = "black")
,
box(
width = NULL, status = "success",
radioButtons("DownloadSilhouetteCheck","Choose file type to download:",
c("png", "pdf", "tiff"),inline = TRUE
),
downloadButton('DownloadSilhouette', 'Download Plot')
)
),
tabPanel(
title = div(icon("book"), "Expression heatmap by signagure"),
value = "cr04",
uiOutput("expressionHeatmapSelectPlatform"),
withSpinner(plotOutput("clusterexpress",height = "100%"), color = "black"),
box(
width = NULL, status = "success",
radioButtons("DownloadClusterexpressPlotCheck","Choose file type to download:",
c("png", "pdf", "tiff"),inline = TRUE
),
downloadButton('DownloadClusterexpressPlot', 'Download Plot'),
downloadButton('DownloadClusterExpressMatrix', 'Download Matrix')
)
),
tabPanel(
title = div(icon("book"), "Iteration Record"),
value = "cr05",
plotOutput("IterationPlot", height = "100%"),
box(
width = NULL, status = "success",
radioButtons("DownloadIterationPlotCheck","Choose file type to download:",
c("png", "pdf", "tiff"),inline = TRUE
)
# to be added
)
),
tabPanel(
title = div(icon("book"), "Readme"),
value = "cr06",
includeMarkdown("dom/CrossICCObject.Rmd")
)
)
)
))
#bodyPredict----
bodyPredict <- tabItem(
"predict",
h2("Allocate new samples with their expression value"),
fluidRow(
#setting panel
box(
title = "Input your data set for prediction",
background = "black",
width = 3,
radioButtons(
"dataset2",
strong("Data to predict"),
inline = TRUE,
c(Default = "default", Upload = "upload"),
selected = 'default'
),
conditionalPanel(
condition = "input.dataset2 == 'upload'",
fileInput(
'file2',
'Input dataset in matrix file',
accept = c('text/txt', c('.rds','.csv','.txt'))
),
downloadLink('DownloadPredictExampleFile', 'See example file ')
),
actionBttn("submit2", "Submit")
),
tabBox (
id = "PredictResultPanel",
title = h3("Analysis"),
width =9,
side = "right",
selected = "pre02",
tabPanel(
title = div(icon("book"), "PredictResult"),
value = "pre01",
downloadLink('DownloadPredictHeatmap', 'Download PDF'),
downloadLink('DownloadPredictClusterResult', 'Download Predicted Cluster Result'),
withSpinner(plotOutput("predictHeatmap", height = "800px"), color = "black")
),
tabPanel(
title = div(icon("book"), "Readme"),
value = "pre02",
includeMarkdown("dom/predict.Rmd")
)
)
)
)
# bodyCorrelation----
bodyCorrelation <- tabItem(
"correlation",
h2("Correlation analysis of the two cluster system"),
fluidRow(
valueBoxOutput("getRAbox", width = 4),
valueBoxOutput("getARIbox", width = 4),
valueBoxOutput("getJaccarddox", width = 4)
),
fluidRow(
box( width = 3,
title = "Analysis",
tabBox (
height = "100%", width = "100%",
selected = "caInput01",
side = "left",
tabPanel(
title = div(icon("table"), "Data Input"),
value = "caInput01",
radioGroupButtons(
"data3",
label = strong("clinical Dataset"),
choices = c(Default = "Default", Upload = "Upload"),
selected = 'Default',
status = "primary"
),
conditionalPanel(
condition = "input.data3 == 'Upload'",
fileInput(
'file3',
'Input dataset in matrix file',
accept =
c('text/txt', '.csv')
)
),
uiOutput("VariableSelectionUI1"),
uiOutput("VariableSelectionUI2"),
actionBttn("submit3", "Submit", style = "unite")
),
tabPanel(
title = div(icon("cog"), "Setting"),
value = "caInput01",
selectInput("cor_theme", "Plot Theme:",
c("default","Tufte","Economist","Solarized","Stata","Excel 2003","Inverse Gray","Fivethirtyeight","Tableau","Stephen","Wall Street","GDocs","Calc","Pander","Highcharts"))
,
sliderInput("corre_size", "Zoom in/out graph:",min = 500, max = 1000, value = 800)
)
)
),
box( width =9,
title = "Analysis",
tabBox (
height = "100%", width = "100%",
id = "clinicalResultPanel",
side = "left",
selected = "ca04",
tabPanel(
title = div(icon("book"), "Data"),
value = "ca01",
h3("Input Data "),
dataTableOutput("summaryCorrelationData")
),
tabPanel(title = div(icon("book"), "Contingency Table "),
value ="ca02",
dataTableOutput("ContingencyTableRender")
),
tabPanel(
title = div(icon("book"), "Plot"),
value = "ca03",
withSpinner(plotOutput("getCorplotRender",height = "100%"), color = "black"),
box(
width = NULL, status = "success",
radioButtons("DownloadCorrelationPlotCheck","Choose file type to download:",
c("png", "pdf", "tiff"),inline = TRUE,selected = "pdf"
),
downloadBttn('DownloadCorrelationPlot', 'Download')
# to be added
)
),
tabPanel(
title = div(icon("book"), "SankeyPlot"),
value = "ca04",
withSpinner(plotOutput("getSankyPlotRender",height = "100%"), color = "black"),
box(
width = NULL, status = "success",
radioButtons("DownloadsankeyPlotCheck","Choose file type to download:",
c("png", "pdf", "tiff"),inline = TRUE,selected = "pdf"
),
downloadBttn('DownloadSankeyPlot', 'Download')
# to be added
)
),
tabPanel(
title = div(icon("book"), "Read Me"),
value = "ca04",
includeMarkdown("dom/correlation.Rmd")
# ,includeHTML("dom/correlation.html")
)
)
)
)
)
# bodySsGSEA ----
bodySsGSEA <- tabItem("ssgsea",
h2("ssGSEA analysis"),
fluidRow(
#setting panel
box(
title = "Input dataset",
width = 3,
tabBox (id = "ssGseaSettingPanel",side = "left", selected = "ssgseaset01",
height = "100%", width = "100%",
tabPanel(
title = div(icon("book"), "Loading"),
value = "ssgseaset01",
# ssgsea data
radioGroupButtons(
"ssGSEAdata",
label = strong("Expression Data"),
choices = c(Example = "Example", Upload = "Upload"),
selected = 'Example',
status = "primary"
),
conditionalPanel(
condition = "input.ssGSEAdata == 'Upload'",
fileInput(
'ssGSEAdatafile',
'Input dataset in matrix file',
accept =
c('text/txt', '.csv')
)
),
radioGroupButtons(
"ssGSEASet",
label = strong("GENE SET"),
choices = c(KEGG = "KEGG",Default= "Default",Upload = "Upload"),
selected = 'Default',
status = "primary"
),
conditionalPanel(
condition = "input.ssGSEASet == 'Upload'",
fileInput(
'ssGSEAgenesetfile',
'Input Geneset file',
accept =
c('text/txt', '.csv')
)
)
),
tabPanel(
title = div(icon("book"), "Setting"),
value = "ssgseaset02",
sliderInput("ssgsea_size", "Zoom in/out graph:",min = 500, max = 1000, value = 800)
)
)
),
box(
title = "Analysis Result",
width =9,
tabBox (
height = "100%", width = "100%",
id = "ssGseaResultPanel", side = "left",selected = "ssgseaRes03",
tabPanel(
title = div(icon("book"), "Out Table"),
value = "ssgseaRes01",
dataTableOutput("ssGSEAmatrix")
),
tabPanel(
title = div(icon("book"), "Plot"),
value = "ssgseaRes02"
),
tabPanel(
title = div(icon("book"), "Read Me"),
value = "ssgseaRes03"
,includeMarkdown("dom/ssGSEA.Rmd")
)
)
)
))
# bodySurvival ----
bodySurival <- tabItem(
"Survival",
h2("Survival evaluation of the clustering system"),
fluidRow(
#setting panel
box(
title = "Input dataset",
width = 3,
tabBox (id = "SurvivalSettingPanel" , side = "left",selected = "survivalset01",
height = "100%", width = "100%",
tabPanel(
title = div(icon("book"), "Loading"),
value = "survivalset01",
radioGroupButtons(
"data5",
label = strong("Survival Dataset"),
choices = c(Default = "Default", Upload = "Upload"),
selected = 'Default',
status = "primary"
),
conditionalPanel(
condition = "input.data5 == 'Upload'",
fileInput(
'survivalFile',
'Input dataset in matrix file',
accept =
c('text/txt', '.csv')
)
),
uiOutput("survivalFeatureSelect1"),
uiOutput("survivalTimeSelect1"),
uiOutput("survivalStatusSelect1"),
actionBttn("submit5", "Submit", style = "unite")
),
tabPanel(
title = div(icon("book"), "Setting"),
value = "survivalset02",
sliderInput("survival_size", "Zoom in/out graph:",min = 500, max = 1000, value = 800)
)
)
),
box(
title = "Analysis Result",
width =9,
tabBox (id = "survivalResultPanel", side = "left", selected = "survivalRes03",
height = "100%", width = "100%",
tabPanel(
title = div(icon("book"), " Dataset"),
value = "survivalRes01",
dataTableOutput("survivalData")
# , includeHTML("dom/survival.html")
),
tabPanel(
title = div(icon("book"), "Plot"),
value = "survivalRes02",
withSpinner(plotOutput("SurvivalPlotRender",height = "100%"), color = "black"),
box(
width = NULL, status = "success",
radioButtons("DownloadSurvivalPlotCheck","Choose file type to download:",
c("png", "pdf", "tiff"),inline = TRUE,selected = "pdf"
),
downloadBttn('DowloadSurvival', 'Download')
# to be added
)
),
tabPanel(
title = div(icon("book"), "Read Me"),
value = "survivalRes03",
includeMarkdown("dom/survival.Rmd")
# , includeHTML("dom/survival.html")
)
)
)
)
)
#-----------
#Main function----
shinyUI(dashboardPage(skin = "black",
dashboardHeader(title = "CrossICC: iterative consensus clustering of cross-platform data",
titleWidth = 600
),
sidebar,
dashboardBody(
tags$head(
tags$style(HTML("
.shiny-output-error-validation {
color: brown;
}
")),
tags$link(rel = "stylesheet", type = "text/css", href = "css/main.css")
),
tabItems(
bodyHome,
bodyCrossICC,
bodyPredict,
bodyCorrelation,
bodySsGSEA,
bodySurival
)
)
))
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