inst/Shiny/ui.R
In sysbioTurin/connector: Fitting and clustering of longitudinal data
library("shiny")
library("shinydashboard")
library("shinyFiles")
library("shinybusy")
library("shinyjs")
library("shinyWidgets")
library("tools")
library("ggplot2")
library("dashboardthemes")
ui <- dashboardPage(
dashboardHeader(
title = "CONNECTOR",
tags$li(class = "dropdown",
tags$style("#mydropdown{cursor: pointer; background-color: #852fb4 ;
color: white;
border: 1px solid #852fb4; height: 50px;left:0;}"),
dropdownButton(inputId = "mydropdown",label = "",
right = T,
circle = FALSE,
icon = icon("download"),
tags$li(shinyjs::useShinyjs(),
downloadButton(outputId = 'download',href = "Connector.RData",
label = "R enviroment",title = "Save the R enviroment",
style = "cursor: pointer; width: 98%;
text-align: center; vertical-align: middle;
border: 1px solid #9809AF;",
download = "Connector.RData",
class="dlButton")),
tags$li(shinyjs::useShinyjs(),
downloadButton(outputId = 'reportGen',
href = "report.html",
download = "report.html",
label = "Report",title = "Report generation",
style = "cursor: pointer; width: 98%;
text-align: center; vertical-align: middle;
border: 1px solid #9809AF;",
class="dlButton")
)
),
block = TRUE),
tags$li(a(onclick = "onclick =window.open('https://github.com/qBioTurin/connector')",
href = NULL,
icon("github"),
title = "GitHub",
style = "cursor: pointer;"),
class = "dropdown")
),
### Sidebar content
dashboardSidebar(div(style="overflow-y: scroll"),
sidebarMenu(
id = "tabs",
menuItem("Home", tabName = "home", icon = icon("home")),
menuItem("Loading data", tabName = "Loading", icon = icon("upload")),
menuItem("Pre processing", tabName = "PreProc", icon = icon("edit")),
menuItem("Model selection", icon = icon("edit"),
menuSubItem("Setting p", tabName = "pSelection", icon = icon("dashboard")),
menuSubItem("Setting G", tabName = "FCM", icon = icon("dashboard") )
),
menuItem("Cluster plot", icon = icon("edit"),
tabName = "ClPlots"
)
)
),
## Body content
dashboardBody(
### changing theme
shinyDashboardThemes(
#theme = "blue_gradient"
theme = "onenote"
),
tags$head(
tags$link(rel = "stylesheet", type = "text/css", href = "custom.css"),
tags$script(src = "message-handler.js")
),
tabItems(
# Loading tab content
tabItem(tabName = "home",
h2("Connector "),
h1(""),
p("Presented by: ",strong("Quantitative Biology")," group of the University of Turin, ",
tags$a(href= "onclick =window.open('http://beta.di.unito.it/index.php/english/research/groups/computational-and-mathematical-methodologies-modelling-multi-omics-systems/about')", "(q-Bio Turin)")
),
p("Authors: S. Pernice, R. Sirovich, M. Beccuti and F. Cordero",
style = "font-family: 'times'; font-si16pt"),
img(src = "groups.png", height = 140, width = 400, style="display: block; margin-left: auto; margin-right: auto"),
img(src = "founds.png", height = 70, width = 200, style="display: block; position: absolute; bottom: 5%; right: 5%")
),
tabItem(tabName = "Loading",
h2("Loading Data"),
tabBox(
# The id lets us use input$tabset1 on the server to find the current tab
id = "tabBoxLoading",width = 12 ,
tabPanel("From files:", "",
fluidRow(
p("Two files are requested to run the data analysis exploiting the CONNECTOR package:"),
p(" - the excel file, namely ", strong("GrowDataFile", style = "font: bold"),", reporting the growth evolution data, "),
p(" - the csv file, namely", strong("AnnotationFile", style = "font: bold"),", containing the annotation information associated with the samples. "),
p("Hence, the growth data associated with an experiment must be stored into GrowDataFile as a table with two columns for each sample. The first column, labeled Time, contains the time points of a sample. The second column, labeled by the sample name, contains the data volume over the time. Instead, the second file (i.e. AnnotationFile) stores the annotated information associated with the samples as a table in csv format so that number of rows is equals to the total number of samples."),
column(width=6,
fileInput("fileGrowth", "GrowDataFile:", placeholder = "Choose a xlsx file",
accept = c(
"application/vnd.ms-excel",
"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet") )
),
column(width=6,
fileInput("fileFeat", "AnnotationFile", placeholder = "Choose a csv file",
accept = c(".csv") )
),
fluidRow(column(width = 10,offset = 1,verbatimTextOutput("LoadingError1"))),
fluidRow(column(width = 10,offset = 1,htmlOutput("SummaryLoading"))),
column(width=2,
actionButton( label = "Load", inputId = "LoadingData", icon = icon("file-upload") )
),
column(width=1,
actionButton( label = "Next", inputId = "FromS1toS2", icon = icon("arrow-circle-right") )
),
# box(title = "Outputs",width = 12,
# background = "black",collapsible = TRUE,
# textOutput(outputId = "console")
# ),
add_busy_spinner(spin = "fading-circle",color = "white",height = 80,width=80)
)
),
tabPanel("From ConnectorList.RData:", "",
fluidRow(
p("The RData could contain the following R objects:"),
p(" - the connector list, namely ", strong("CONNECTORList", style = "font: bold"),"(the name must correspond) obtained from the function DataImport(). This object is mandatory. "),
p(" - the truncated connector list, namely ", strong("CONNECTORList_trunc", style = "font: bold"),"(the name must correspond) obtained from the function DataTruncation()."),
p(" - the clustered connector list, namely ", strong("CONNECTORListFCM_all", style = "font: bold"),"(the name must correspond) obtained from the function ClusterAnalysis()."),
column(width=12,
fileInput("RDataImport1", "RData file:",
placeholder = "Select a Connector.RData",
width = "100%"
),
fluidRow(column(width = 10,offset = 1,verbatimTextOutput("LoadingError2"))),
fluidRow(column(width = 10,offset = 1,htmlOutput("SummaryLoadingRdata")))
),
column(width=2,
actionButton( label = "Load", inputId = "LoadingConnectorList1", icon = icon("file-upload") )
),
add_busy_spinner(spin = "fading-circle",color = "white",height = 80,width=80)
)
),
tabPanel("From RData:", "",
fluidRow(
column(width=12,
p("Select an RDs storing the data.frame with three columns: ID for the identification number of each curve, V for the values and Time for the respective time points"),
fileInput("RDataImportGrowthData", "Growth curves data:",
placeholder = "Select an RDs storing the data.frame for the growth data",
width = "100%"
),
p("Select an RDs storing the data.frame where the first column must be named ID and it stores the identification numbers contained in the GrowDataFrame. Then it is possible to add a column per feature to consider and to associate to the respective sample (depending on the identification number in the first column. If NULL, then in the ConnectorList only the feature ID will be reported. " ),
fileInput("RDataImportFeatureData", "Feature data:",
placeholder = "Select an RDs storing the data.frame for the feature data",
width = "100%"
),
fluidRow(column(width = 10,offset = 1,verbatimTextOutput("LoadingError3"))),
fluidRow(column(width = 10,offset = 1,htmlOutput("SummaryLoadingRdata2")))
),
column(width=2,
actionButton( label = "Load", inputId = "LoadingConnectorList2", icon = icon("file-upload") )
),
column(width=1,
actionButton( label = "Next", inputId = "FromS1toS2_RDs", icon = icon("arrow-circle-right") )
),
add_busy_spinner(spin = "fading-circle",color = "white",height = 80,width=80)
)
)
)
),
tabItem(tabName = "PreProc",
h2("Preprocessing"),
box(width = 12, title = "Data visualization:",
column(width = 9,
selectInput(inputId = "feature", label = "Features:",choices = "ID" )
),
column(width = 3,
checkboxInput(inputId = "GrowthCurvesLegend", label = "Show legend")
),
column(width =12,
h4("Growth curves"),
plotOutput("visualGrowth")
)
),
box(width = 12, title = "Data truncation:",collapsible = TRUE,collapsed = TRUE,
sliderInput(inputId = "truncTime", label = h4("Truncation times"),
min = 0, max = 0, value = c(0,0),step = 1),
h4("Time grid density"),
plotOutput("visualTimes"),
column(width=2,
actionButton( label = "Truncate", inputId = "TruncateData", icon = icon("cut") )
),
column(width=1,
actionButton( label = "Next", inputId = "FromS2toS3", icon = icon("arrow-circle-right") )
),
add_busy_spinner(spin = "fading-circle",color = "white",height = 80,width=80),
fluidRow(column(width = 10,offset = 1,htmlOutput("SummaryCutting")))
),
box(width = 12, title = "Save the plots:",collapsible = TRUE,collapsed = TRUE,
column(width =12,
textInput(inputId = "titleGrowth", label = "Plot title",value = "" )
),
column(width = 6,
textInput(inputId = "xlabGrowth", label = "x-axis label",value = "" )
),
column(width = 6,
textInput(inputId = "ylabGrowth", label = "y-axis label",value = "" )
),
column(width = 2,
actionButton(label="Change the plot", inputId = "ChangeGrowth", icon = icon("palette"))
),
column(width = 1,
downloadButton(label="Download",outputId = "PlotDownloadGrowth",
href = "GrowthCurves.pdf",
download = "GrowthCurves.pdf" ,
title = "Save the GrowthCurves plot",
style = "cursor: pointer;",
class="dlButton"))
)
),
tabItem(tabName = "pSelection",
h2("Setting p:"),h4("Cross-log likelihood"),
fluidRow(
box(width = 12,h4("Spline dimension:"),
column(width = 6,
numericInput("Minp", "Min: ", 2, min = 2)
),
column(width = 6,
numericInput("Maxp", "Max: ", 3, min = 3)
),
actionButton( label = "Run", inputId = "RunForP" ),
fluidRow(column(width = 10,offset = 1,verbatimTextOutput("ErrorInP"))),
add_busy_spinner(spin = "fading-circle",color = "white",height = 80,width=80)
),
box(width = 12, title = "CrossLog-likelihood visualization:",collapsible = TRUE,collapsed = T,
plotOutput("visualCLLik"),
sliderInput(inputId = "pValue", label = h4("Select p value:"),
min = 0,max = 0, value = 0,step = 1),
column(width=2,
actionButton( label = "Select",inputId = "pSelection", icon = icon("check") )
),
column(width=1,
actionButton( label = "Next", inputId = "FromS3toS4", icon = icon("arrow-circle-right") )
)
),
box(width = 12, title = "Knots distribution visualization:",collapsible = TRUE,collapsed = T,
plotOutput("visualKnots")
),
box(width = 12, title = "Save the plots:",collapsible = TRUE,collapsed = T,
column(width =12,
textInput(inputId = "titleCLL", label = "Plot title",value = "" )
),
column(width = 6,
textInput(inputId = "xlabCLL", label = "x-axis label",value = "" )
),
column(width = 6,
textInput(inputId = "ylabCLL", label = "y-axis label",value = "" )
),
column(width = 2,
actionButton(label="Change the plot", inputId = "ChangeCLL", icon = icon("palette"))
),
column(width = 1,
downloadButton(label="Download",outputId = "PlotDownloadCLL",
href = "CLL.pdf",
download = "CLL.pdf" ,
title = "Save the CrossLog-likelihood plot",
style = "cursor: pointer;",
class="dlButton"))
)
)
),
tabItem(tabName = "FCM",
h2("Setting G:"),h4("FCM"),
verbatimTextOutput("FCMallError"),
fluidRow(
column(width = 6,
box(width = 12,
title = "Number of clusters:",
numericInput("MinG", "Min: ", 2, min = 1),
numericInput("MaxG", "Max: ", 2, min = 2)
)
),
column(width = 6,
numericInput("Nruns", "Number of runs: ", 100, min = 1),
numericInput("Cores", "Number of processors: ", 1, min = 1)
),
actionButton( label = "Run", inputId = "RunForG" ),
add_busy_spinner(spin = "fading-circle",color = "white",height = 80,width=80)
),
tabBox(
# The id lets us use input$tabset1 on the server to find the current tab
id = "tabBoxSelectingG",width = 12 ,
tabPanel("Indexes plots:", "",
fluidRow(
column(width=11,
plotOutput("visualIndexes"),
column(width = 1,
downloadButton(label="Download",outputId = "PlotDownloadBoxPlotIndexes",
href = "BoxPlotIndexes.pdf",
download = "BoxPlotIndexes.pdf" ,
title = "Save the BoxPlot Indexes plot",
style = "cursor: pointer;",
class="dlButton")
)
)
)
),
tabPanel("Consensus matrix:", "",
fluidRow(
column(width=11,
sliderInput(inputId = "GConsMat", label = h4("Number of clusters:"),
min = 0,max = 0, value = 0,step = 1),
plotOutput("visualConsMatrix"),
column(width = 1,
downloadButton(label="Download",outputId = "PlotDownloadConsMatrix",
href = "ConsMatrix.pdf",
download = "ConsMatrix.pdf" ,
title = "Save the Consensus Matrix plot",
style = "cursor: pointer;",
class="dlButton")
)
)
)
),
tabPanel("All fDB indexes:", "",
fluidRow(
column(width =6,
h4("Tightness indexes:"),
tableOutput(outputId = "table_tight_all")," ",
h4("fDB1 indexes:"),
tableOutput(outputId = "table_fdb1_all")," "
),
column(width =6,
h4("fDB indexes:"),
tableOutput(outputId = "table_fdb_all")," ",
h4("fDB2 indexes:"),
tableOutput(outputId = "table_fdb2_all")," "
)
)
),
tabPanel("G selection:", "",
fluidRow(
column(width= 11,
numericInput("Gvalue", "Number of clusters: ", 1, min = 1)
),
column(width= 2,offset = 9,
actionButton("GExtrap", "Select"),
add_busy_spinner(spin = "fading-circle",color = "white",height = 80,width=80)
)
)
),
tabPanel("fDB indexes of the selected cluster:", "",
fluidRow(
column(width= 11,
verbatimTextOutput("IndexesClusterError")
),
box(width = 12, title = "Coefficents",collapsible = T,collapsed = T,
column(width =6,
h4("Erre indexes:"),
tableOutput("table_fdb_erre"),
h4("Esse indexes:"),
tableOutput("table_fdb_esse")
),
column(width =6,
h4("Emme indexes:"),
tableOutput("table_fdb_emme")
)
),
box(width = 12, title ="First derivative coefficents",collapsible = T,collapsed = T,
column(width =6,
h4("Erre indexes:"),
tableOutput("table_fdb1_erre"),
h4("Esse indexes:"),
tableOutput("table_fdb1_esse")
),
column(width =6,
h4("Emme indexes:"),
tableOutput("table_fdb1_emme")
)
),
box(width = 12,
title= "Second derivative coefficents",collapsible = T,collapsed = T,
column(width =6,
h4("Erre indexes:"),
tableOutput("table_fdb2_erre"),
h4("Esse indexes:"),
tableOutput("table_fdb2_esse")
),
column(width =6,
h4("Emme indexes:"),
tableOutput("table_fdb2_emme")
)
)
)
)
)
),
tabItem(tabName = "ClPlots",
h2(""),
verbatimTextOutput("IndexesClusterErrorCLplot"),
verbatimTextOutput("G_not_selected"),
tabBox(
id = "tabBoxCLplot",width = 12,
tabPanel("Clusters",
"",
fluidRow(
column(width= 3,
selectInput(inputId = "featureCLplot",
label = "Features:",choices = "ID",
selected = "ID")
),
column(width= 3,
selectInput(inputId = "typeCLplot",
label = "Plot:",
choices = c("All clusters","Cluster means") ,
selected = "All clusters" )
),
column(width = 2,
checkboxInput(inputId = "ClusterPlotLegend", label = "Show legend",value = F)
)
),
plotOutput("visualClplot"),
downloadButton(label="Download",outputId = "PlotDownloadClplot",
href = "Clplot.pdf",
download = "Clplot.pdf" ,
title = "Save the Cluster plot",
style = "cursor: pointer;",
class="dlButton"),
add_busy_spinner(spin = "fading-circle",color = "white",height = 80,width=80)
),
tabPanel("Discriminant", "",
fluidRow(
column(width = 4,
selectInput(inputId = "ColorDiscrPlot",
label = "Curve colors:",choices = c("Clusters", "Features" ),
selected = "Cluster")
),
column(width = 4,
uiOutput("FeatSelection")
)
),
plotOutput("DiscrPlot"),
downloadButton(label="Download",outputId = "PlotDownloadDiscrPlot",
href = "DiscrPlot.pdf",
download = "DiscrPlot.pdf" ,
title = "Save the Discriminant plot",
style = "cursor: pointer;",
class="dlButton")
),
tabPanel("Spline", "",
fluidRow(
column(width= 5,
selectInput(inputId = "SplineID",
label = "Sample:",
choices = "")
)
),
plotOutput("visualSplinePlot"),
downloadButton(label="Download",outputId = "PlotDownloadSpliePlot",
href = "SplinePlot.pdf",
download = "SplinePlot.pdf" ,
title = "Save the Spline plot",
style = "cursor: pointer;",
class="dlButton")
),
tabPanel("Inspection", "",
fluidRow(
column(width= 3,
selectInput(inputId = "FeatInsp",
label = "Feature:",choices = "ID",selected = "ID")
)
),
fluidRow(
column(width = 6,
tableOutput(outputId = "tableClusterNames")
),
column(width = 6,
tableOutput(outputId = "tableCounting")
)
)
)
)
)
# ,
# tabItem(tabName = "Plots",
# h2("Plots obtained through the anaylsys"),
# fluidRow(
# box(width = 12, title = "Data Visualization:",collapsible = TRUE,collapsed = T,
# column(width = 7,h4("Plots"),
# plotOutput("visualGrowthEND")
# ),
# column(width = 5,h4("Plot features"),
# #selectInput(inputId = "feature", label = "Features:",choices = "" ),
# textInput(inputId = "title1", label = "Plot title",value = "" ),
# column(width = 6,
# textInput(inputId = "xlab1", label = "x-axis label",value = "" ),
# actionButton(label="Change", inputId = "Change1")),
# column(width = 6,
# textInput(inputId = "ylab1", label = "y-axis label",value = "" ),
# downloadButton(label="Download",outputId = "PlotDownload1",
# href = "GrowthCurves.pdf",
# download = "GrowthCurves.pdf" ,
# title = "Save the GrowthCurves plot",
# style = "cursor: pointer;",
# class="dlButton"))
# )
# ),
# box(width = 12,
# title = "CrossLog-likelihood visualization:",collapsible = TRUE,collapsed = T,
# column(width = 7,h4("Plots"),
# plotOutput("visualCLLikEND")
# ),
# column(width = 5,h4("Plot features"),
# textInput(inputId = "title2", label = "Plot title",value = "" ),
# column(width = 6,
# textInput(inputId = "xlab2", label = "x-axis label",value = "" ),
# actionButton(label="Change", inputId = "Change2")),
# column(width = 6,
# textInput(inputId = "ylab2", label = "y-axis label",value = "" ),
# downloadButton(label="Download",outputId = "PlotDownload2",
# href = "CrossLogLikelihood.pdf",
# title = "Save the CrossLogLikelihood plot",
# style = "cursor: pointer;",
# class="dlButton")
# )
# )
# )
# )
#)# tabitem
)# tabitems
)
)
sysbioTurin/connector documentation built on April 9, 2024, 12:10 p.m.
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library("shiny")
library("shinydashboard")
library("shinyFiles")
library("shinybusy")
library("shinyjs")
library("shinyWidgets")
library("tools")
library("ggplot2")
library("dashboardthemes")
ui <- dashboardPage(
dashboardHeader(
title = "CONNECTOR",
tags$li(class = "dropdown",
tags$style("#mydropdown{cursor: pointer; background-color: #852fb4 ;
color: white;
border: 1px solid #852fb4; height: 50px;left:0;}"),
dropdownButton(inputId = "mydropdown",label = "",
right = T,
circle = FALSE,
icon = icon("download"),
tags$li(shinyjs::useShinyjs(),
downloadButton(outputId = 'download',href = "Connector.RData",
label = "R enviroment",title = "Save the R enviroment",
style = "cursor: pointer; width: 98%;
text-align: center; vertical-align: middle;
border: 1px solid #9809AF;",
download = "Connector.RData",
class="dlButton")),
tags$li(shinyjs::useShinyjs(),
downloadButton(outputId = 'reportGen',
href = "report.html",
download = "report.html",
label = "Report",title = "Report generation",
style = "cursor: pointer; width: 98%;
text-align: center; vertical-align: middle;
border: 1px solid #9809AF;",
class="dlButton")
)
),
block = TRUE),
tags$li(a(onclick = "onclick =window.open('https://github.com/qBioTurin/connector')",
href = NULL,
icon("github"),
title = "GitHub",
style = "cursor: pointer;"),
class = "dropdown")
),
### Sidebar content
dashboardSidebar(div(style="overflow-y: scroll"),
sidebarMenu(
id = "tabs",
menuItem("Home", tabName = "home", icon = icon("home")),
menuItem("Loading data", tabName = "Loading", icon = icon("upload")),
menuItem("Pre processing", tabName = "PreProc", icon = icon("edit")),
menuItem("Model selection", icon = icon("edit"),
menuSubItem("Setting p", tabName = "pSelection", icon = icon("dashboard")),
menuSubItem("Setting G", tabName = "FCM", icon = icon("dashboard") )
),
menuItem("Cluster plot", icon = icon("edit"),
tabName = "ClPlots"
)
)
),
## Body content
dashboardBody(
### changing theme
shinyDashboardThemes(
#theme = "blue_gradient"
theme = "onenote"
),
tags$head(
tags$link(rel = "stylesheet", type = "text/css", href = "custom.css"),
tags$script(src = "message-handler.js")
),
tabItems(
# Loading tab content
tabItem(tabName = "home",
h2("Connector "),
h1(""),
p("Presented by: ",strong("Quantitative Biology")," group of the University of Turin, ",
tags$a(href= "onclick =window.open('http://beta.di.unito.it/index.php/english/research/groups/computational-and-mathematical-methodologies-modelling-multi-omics-systems/about')", "(q-Bio Turin)")
),
p("Authors: S. Pernice, R. Sirovich, M. Beccuti and F. Cordero",
style = "font-family: 'times'; font-si16pt"),
img(src = "groups.png", height = 140, width = 400, style="display: block; margin-left: auto; margin-right: auto"),
img(src = "founds.png", height = 70, width = 200, style="display: block; position: absolute; bottom: 5%; right: 5%")
),
tabItem(tabName = "Loading",
h2("Loading Data"),
tabBox(
# The id lets us use input$tabset1 on the server to find the current tab
id = "tabBoxLoading",width = 12 ,
tabPanel("From files:", "",
fluidRow(
p("Two files are requested to run the data analysis exploiting the CONNECTOR package:"),
p(" - the excel file, namely ", strong("GrowDataFile", style = "font: bold"),", reporting the growth evolution data, "),
p(" - the csv file, namely", strong("AnnotationFile", style = "font: bold"),", containing the annotation information associated with the samples. "),
p("Hence, the growth data associated with an experiment must be stored into GrowDataFile as a table with two columns for each sample. The first column, labeled Time, contains the time points of a sample. The second column, labeled by the sample name, contains the data volume over the time. Instead, the second file (i.e. AnnotationFile) stores the annotated information associated with the samples as a table in csv format so that number of rows is equals to the total number of samples."),
column(width=6,
fileInput("fileGrowth", "GrowDataFile:", placeholder = "Choose a xlsx file",
accept = c(
"application/vnd.ms-excel",
"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet") )
),
column(width=6,
fileInput("fileFeat", "AnnotationFile", placeholder = "Choose a csv file",
accept = c(".csv") )
),
fluidRow(column(width = 10,offset = 1,verbatimTextOutput("LoadingError1"))),
fluidRow(column(width = 10,offset = 1,htmlOutput("SummaryLoading"))),
column(width=2,
actionButton( label = "Load", inputId = "LoadingData", icon = icon("file-upload") )
),
column(width=1,
actionButton( label = "Next", inputId = "FromS1toS2", icon = icon("arrow-circle-right") )
),
# box(title = "Outputs",width = 12,
# background = "black",collapsible = TRUE,
# textOutput(outputId = "console")
# ),
add_busy_spinner(spin = "fading-circle",color = "white",height = 80,width=80)
)
),
tabPanel("From ConnectorList.RData:", "",
fluidRow(
p("The RData could contain the following R objects:"),
p(" - the connector list, namely ", strong("CONNECTORList", style = "font: bold"),"(the name must correspond) obtained from the function DataImport(). This object is mandatory. "),
p(" - the truncated connector list, namely ", strong("CONNECTORList_trunc", style = "font: bold"),"(the name must correspond) obtained from the function DataTruncation()."),
p(" - the clustered connector list, namely ", strong("CONNECTORListFCM_all", style = "font: bold"),"(the name must correspond) obtained from the function ClusterAnalysis()."),
column(width=12,
fileInput("RDataImport1", "RData file:",
placeholder = "Select a Connector.RData",
width = "100%"
),
fluidRow(column(width = 10,offset = 1,verbatimTextOutput("LoadingError2"))),
fluidRow(column(width = 10,offset = 1,htmlOutput("SummaryLoadingRdata")))
),
column(width=2,
actionButton( label = "Load", inputId = "LoadingConnectorList1", icon = icon("file-upload") )
),
add_busy_spinner(spin = "fading-circle",color = "white",height = 80,width=80)
)
),
tabPanel("From RData:", "",
fluidRow(
column(width=12,
p("Select an RDs storing the data.frame with three columns: ID for the identification number of each curve, V for the values and Time for the respective time points"),
fileInput("RDataImportGrowthData", "Growth curves data:",
placeholder = "Select an RDs storing the data.frame for the growth data",
width = "100%"
),
p("Select an RDs storing the data.frame where the first column must be named ID and it stores the identification numbers contained in the GrowDataFrame. Then it is possible to add a column per feature to consider and to associate to the respective sample (depending on the identification number in the first column. If NULL, then in the ConnectorList only the feature ID will be reported. " ),
fileInput("RDataImportFeatureData", "Feature data:",
placeholder = "Select an RDs storing the data.frame for the feature data",
width = "100%"
),
fluidRow(column(width = 10,offset = 1,verbatimTextOutput("LoadingError3"))),
fluidRow(column(width = 10,offset = 1,htmlOutput("SummaryLoadingRdata2")))
),
column(width=2,
actionButton( label = "Load", inputId = "LoadingConnectorList2", icon = icon("file-upload") )
),
column(width=1,
actionButton( label = "Next", inputId = "FromS1toS2_RDs", icon = icon("arrow-circle-right") )
),
add_busy_spinner(spin = "fading-circle",color = "white",height = 80,width=80)
)
)
)
),
tabItem(tabName = "PreProc",
h2("Preprocessing"),
box(width = 12, title = "Data visualization:",
column(width = 9,
selectInput(inputId = "feature", label = "Features:",choices = "ID" )
),
column(width = 3,
checkboxInput(inputId = "GrowthCurvesLegend", label = "Show legend")
),
column(width =12,
h4("Growth curves"),
plotOutput("visualGrowth")
)
),
box(width = 12, title = "Data truncation:",collapsible = TRUE,collapsed = TRUE,
sliderInput(inputId = "truncTime", label = h4("Truncation times"),
min = 0, max = 0, value = c(0,0),step = 1),
h4("Time grid density"),
plotOutput("visualTimes"),
column(width=2,
actionButton( label = "Truncate", inputId = "TruncateData", icon = icon("cut") )
),
column(width=1,
actionButton( label = "Next", inputId = "FromS2toS3", icon = icon("arrow-circle-right") )
),
add_busy_spinner(spin = "fading-circle",color = "white",height = 80,width=80),
fluidRow(column(width = 10,offset = 1,htmlOutput("SummaryCutting")))
),
box(width = 12, title = "Save the plots:",collapsible = TRUE,collapsed = TRUE,
column(width =12,
textInput(inputId = "titleGrowth", label = "Plot title",value = "" )
),
column(width = 6,
textInput(inputId = "xlabGrowth", label = "x-axis label",value = "" )
),
column(width = 6,
textInput(inputId = "ylabGrowth", label = "y-axis label",value = "" )
),
column(width = 2,
actionButton(label="Change the plot", inputId = "ChangeGrowth", icon = icon("palette"))
),
column(width = 1,
downloadButton(label="Download",outputId = "PlotDownloadGrowth",
href = "GrowthCurves.pdf",
download = "GrowthCurves.pdf" ,
title = "Save the GrowthCurves plot",
style = "cursor: pointer;",
class="dlButton"))
)
),
tabItem(tabName = "pSelection",
h2("Setting p:"),h4("Cross-log likelihood"),
fluidRow(
box(width = 12,h4("Spline dimension:"),
column(width = 6,
numericInput("Minp", "Min: ", 2, min = 2)
),
column(width = 6,
numericInput("Maxp", "Max: ", 3, min = 3)
),
actionButton( label = "Run", inputId = "RunForP" ),
fluidRow(column(width = 10,offset = 1,verbatimTextOutput("ErrorInP"))),
add_busy_spinner(spin = "fading-circle",color = "white",height = 80,width=80)
),
box(width = 12, title = "CrossLog-likelihood visualization:",collapsible = TRUE,collapsed = T,
plotOutput("visualCLLik"),
sliderInput(inputId = "pValue", label = h4("Select p value:"),
min = 0,max = 0, value = 0,step = 1),
column(width=2,
actionButton( label = "Select",inputId = "pSelection", icon = icon("check") )
),
column(width=1,
actionButton( label = "Next", inputId = "FromS3toS4", icon = icon("arrow-circle-right") )
)
),
box(width = 12, title = "Knots distribution visualization:",collapsible = TRUE,collapsed = T,
plotOutput("visualKnots")
),
box(width = 12, title = "Save the plots:",collapsible = TRUE,collapsed = T,
column(width =12,
textInput(inputId = "titleCLL", label = "Plot title",value = "" )
),
column(width = 6,
textInput(inputId = "xlabCLL", label = "x-axis label",value = "" )
),
column(width = 6,
textInput(inputId = "ylabCLL", label = "y-axis label",value = "" )
),
column(width = 2,
actionButton(label="Change the plot", inputId = "ChangeCLL", icon = icon("palette"))
),
column(width = 1,
downloadButton(label="Download",outputId = "PlotDownloadCLL",
href = "CLL.pdf",
download = "CLL.pdf" ,
title = "Save the CrossLog-likelihood plot",
style = "cursor: pointer;",
class="dlButton"))
)
)
),
tabItem(tabName = "FCM",
h2("Setting G:"),h4("FCM"),
verbatimTextOutput("FCMallError"),
fluidRow(
column(width = 6,
box(width = 12,
title = "Number of clusters:",
numericInput("MinG", "Min: ", 2, min = 1),
numericInput("MaxG", "Max: ", 2, min = 2)
)
),
column(width = 6,
numericInput("Nruns", "Number of runs: ", 100, min = 1),
numericInput("Cores", "Number of processors: ", 1, min = 1)
),
actionButton( label = "Run", inputId = "RunForG" ),
add_busy_spinner(spin = "fading-circle",color = "white",height = 80,width=80)
),
tabBox(
# The id lets us use input$tabset1 on the server to find the current tab
id = "tabBoxSelectingG",width = 12 ,
tabPanel("Indexes plots:", "",
fluidRow(
column(width=11,
plotOutput("visualIndexes"),
column(width = 1,
downloadButton(label="Download",outputId = "PlotDownloadBoxPlotIndexes",
href = "BoxPlotIndexes.pdf",
download = "BoxPlotIndexes.pdf" ,
title = "Save the BoxPlot Indexes plot",
style = "cursor: pointer;",
class="dlButton")
)
)
)
),
tabPanel("Consensus matrix:", "",
fluidRow(
column(width=11,
sliderInput(inputId = "GConsMat", label = h4("Number of clusters:"),
min = 0,max = 0, value = 0,step = 1),
plotOutput("visualConsMatrix"),
column(width = 1,
downloadButton(label="Download",outputId = "PlotDownloadConsMatrix",
href = "ConsMatrix.pdf",
download = "ConsMatrix.pdf" ,
title = "Save the Consensus Matrix plot",
style = "cursor: pointer;",
class="dlButton")
)
)
)
),
tabPanel("All fDB indexes:", "",
fluidRow(
column(width =6,
h4("Tightness indexes:"),
tableOutput(outputId = "table_tight_all")," ",
h4("fDB1 indexes:"),
tableOutput(outputId = "table_fdb1_all")," "
),
column(width =6,
h4("fDB indexes:"),
tableOutput(outputId = "table_fdb_all")," ",
h4("fDB2 indexes:"),
tableOutput(outputId = "table_fdb2_all")," "
)
)
),
tabPanel("G selection:", "",
fluidRow(
column(width= 11,
numericInput("Gvalue", "Number of clusters: ", 1, min = 1)
),
column(width= 2,offset = 9,
actionButton("GExtrap", "Select"),
add_busy_spinner(spin = "fading-circle",color = "white",height = 80,width=80)
)
)
),
tabPanel("fDB indexes of the selected cluster:", "",
fluidRow(
column(width= 11,
verbatimTextOutput("IndexesClusterError")
),
box(width = 12, title = "Coefficents",collapsible = T,collapsed = T,
column(width =6,
h4("Erre indexes:"),
tableOutput("table_fdb_erre"),
h4("Esse indexes:"),
tableOutput("table_fdb_esse")
),
column(width =6,
h4("Emme indexes:"),
tableOutput("table_fdb_emme")
)
),
box(width = 12, title ="First derivative coefficents",collapsible = T,collapsed = T,
column(width =6,
h4("Erre indexes:"),
tableOutput("table_fdb1_erre"),
h4("Esse indexes:"),
tableOutput("table_fdb1_esse")
),
column(width =6,
h4("Emme indexes:"),
tableOutput("table_fdb1_emme")
)
),
box(width = 12,
title= "Second derivative coefficents",collapsible = T,collapsed = T,
column(width =6,
h4("Erre indexes:"),
tableOutput("table_fdb2_erre"),
h4("Esse indexes:"),
tableOutput("table_fdb2_esse")
),
column(width =6,
h4("Emme indexes:"),
tableOutput("table_fdb2_emme")
)
)
)
)
)
),
tabItem(tabName = "ClPlots",
h2(""),
verbatimTextOutput("IndexesClusterErrorCLplot"),
verbatimTextOutput("G_not_selected"),
tabBox(
id = "tabBoxCLplot",width = 12,
tabPanel("Clusters",
"",
fluidRow(
column(width= 3,
selectInput(inputId = "featureCLplot",
label = "Features:",choices = "ID",
selected = "ID")
),
column(width= 3,
selectInput(inputId = "typeCLplot",
label = "Plot:",
choices = c("All clusters","Cluster means") ,
selected = "All clusters" )
),
column(width = 2,
checkboxInput(inputId = "ClusterPlotLegend", label = "Show legend",value = F)
)
),
plotOutput("visualClplot"),
downloadButton(label="Download",outputId = "PlotDownloadClplot",
href = "Clplot.pdf",
download = "Clplot.pdf" ,
title = "Save the Cluster plot",
style = "cursor: pointer;",
class="dlButton"),
add_busy_spinner(spin = "fading-circle",color = "white",height = 80,width=80)
),
tabPanel("Discriminant", "",
fluidRow(
column(width = 4,
selectInput(inputId = "ColorDiscrPlot",
label = "Curve colors:",choices = c("Clusters", "Features" ),
selected = "Cluster")
),
column(width = 4,
uiOutput("FeatSelection")
)
),
plotOutput("DiscrPlot"),
downloadButton(label="Download",outputId = "PlotDownloadDiscrPlot",
href = "DiscrPlot.pdf",
download = "DiscrPlot.pdf" ,
title = "Save the Discriminant plot",
style = "cursor: pointer;",
class="dlButton")
),
tabPanel("Spline", "",
fluidRow(
column(width= 5,
selectInput(inputId = "SplineID",
label = "Sample:",
choices = "")
)
),
plotOutput("visualSplinePlot"),
downloadButton(label="Download",outputId = "PlotDownloadSpliePlot",
href = "SplinePlot.pdf",
download = "SplinePlot.pdf" ,
title = "Save the Spline plot",
style = "cursor: pointer;",
class="dlButton")
),
tabPanel("Inspection", "",
fluidRow(
column(width= 3,
selectInput(inputId = "FeatInsp",
label = "Feature:",choices = "ID",selected = "ID")
)
),
fluidRow(
column(width = 6,
tableOutput(outputId = "tableClusterNames")
),
column(width = 6,
tableOutput(outputId = "tableCounting")
)
)
)
)
)
# ,
# tabItem(tabName = "Plots",
# h2("Plots obtained through the anaylsys"),
# fluidRow(
# box(width = 12, title = "Data Visualization:",collapsible = TRUE,collapsed = T,
# column(width = 7,h4("Plots"),
# plotOutput("visualGrowthEND")
# ),
# column(width = 5,h4("Plot features"),
# #selectInput(inputId = "feature", label = "Features:",choices = "" ),
# textInput(inputId = "title1", label = "Plot title",value = "" ),
# column(width = 6,
# textInput(inputId = "xlab1", label = "x-axis label",value = "" ),
# actionButton(label="Change", inputId = "Change1")),
# column(width = 6,
# textInput(inputId = "ylab1", label = "y-axis label",value = "" ),
# downloadButton(label="Download",outputId = "PlotDownload1",
# href = "GrowthCurves.pdf",
# download = "GrowthCurves.pdf" ,
# title = "Save the GrowthCurves plot",
# style = "cursor: pointer;",
# class="dlButton"))
# )
# ),
# box(width = 12,
# title = "CrossLog-likelihood visualization:",collapsible = TRUE,collapsed = T,
# column(width = 7,h4("Plots"),
# plotOutput("visualCLLikEND")
# ),
# column(width = 5,h4("Plot features"),
# textInput(inputId = "title2", label = "Plot title",value = "" ),
# column(width = 6,
# textInput(inputId = "xlab2", label = "x-axis label",value = "" ),
# actionButton(label="Change", inputId = "Change2")),
# column(width = 6,
# textInput(inputId = "ylab2", label = "y-axis label",value = "" ),
# downloadButton(label="Download",outputId = "PlotDownload2",
# href = "CrossLogLikelihood.pdf",
# title = "Save the CrossLogLikelihood plot",
# style = "cursor: pointer;",
# class="dlButton")
# )
# )
# )
# )
#)# tabitem
)# tabitems
)
)
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