R/ui.R
In lizc07/iDA: Interactive Data Analysis for scRNA-Seq using tag-based UMI data
#' @include global.R
############
# ui
#########
#' @import shinydashboard
# header ---------------------------------------------------------------------------------------------------------------------
header <- dashboardHeader(title = "iDA", disable = F)
# sidebar ---------------------------------------------------------------------------------------------------------------------
sidebar <- dashboardSidebar(
#sidebarSearchForm(label = "Enter a number", "searchText", "searchButton"),
sidebarMenu(
# Setting id makes input$tabs give the tabName of currently-selected tab
id = "tabs",
menuItem("Load Data", tabName = "fileInput", icon = icon("dashboard"),badgeLabel = "Step1"),
menuItem("Process Data", icon = icon("th"), tabName = "dataProcess", badgeLabel = "Step2",
badgeColor = "green"),
menuItem("Advanced Options", icon = icon("bar-chart-o"),badgeLabel = "Step3",
badgeColor = "green"),
fluidRow(column(12,
uiOutput("showCategory"),
uiOutput("showPlotOption.color"),
uiOutput("showPlotOption.shape"),
sliderInput(inputId = "sliderInput.plot.height", label = "Plot Height",
min = 0, max = 5000, value = 500, step = 10, round = T, width = "100%")),
column(12, align = "center", hr(),downloadButton("pbmc.save", "Save Workspace"))
)
))
# body ---------------------------------------------------------------------------------------------------------------------
body <- dashboardBody(
tabItems(
tabItem(tabName = "fileInput",
tabBox(title = "Loading Files", id = "tabBox.fileInput", width = 12,
tabPanel(title = "CSV Files",
fluidRow(
column(12,
column(10,
fileInput("fileInput.csv.umi", "Expression Data (UMI count prefered, Gene x Cell) - Required!", width = "100%",
accept = c(
"text/csv",
"text/comma-separated-values,text/plain",
".csv")
)
),
br(),column(2, checkboxInput(inputId = "fileInput.csv.umi.transpose", "Do Transpose", value = F))
),
column(12,
column(10,
fileInput("fileInput.csv.annot", "Cell Annotation (Cell x Category)", width = "100%",
accept = c(
"text/csv",
"text/comma-separated-values,text/plain",
".csv")
)
),
br(),column(2, checkboxInput(inputId = "fileInput.csv.annot.transpose", "Do Transpose", value = F))
)
)
),
tabPanel(title = "RData File",
fileInput("fileInput.rdata", "Saved RData, including Expression and Annotation Data (Saved by iDA)", width = "100%",
accept = c(".RData")
)
)
),
box(actionButton(inputId = "fileInput.action", width = "100%", label = "Submit"), status = "success", width = 12),
infoBoxOutput("infoBox.umi", width = 6),
infoBoxOutput("infoBox.annot", width = 6),
uiOutput("fileInput.error"),
uiOutput("fileInput.submitted")
),
tabItem(tabName = "dataProcess",
tabBox(title = "Start Analysis", width = 12,
#footer = "Produced by Zongcheng Li, using shiny", status = "primary", solidHeader = T, collapsible = F, collapsed = F,
# QC -------------------------------------------------------------------------
tabPanel(title = "Quality Control",
fluidRow(
column(6,
h4("Gene Number in each Cell"),
column(6,numericInput(inputId = "numericInput.seurat.gene.min",
label = "Minimum", value = 500, width = "100%")),
column(6,numericInput(inputId = "numericInput.seurat.gene.max",
label = "Maximum", value = "Inf", width = "100%"))
),
column(6,
h4("UMI Number in each Cell"),
column(6,numericInput(inputId = "numericInput.seurat.umi.min",
label = "Minimum", value = 10000,width = "100%")),
column(6,numericInput(inputId = "numericInput.seurat.umi.max",
label = "Maximum", value = "Inf",width = "100%"))
),
column(12,
actionButton(inputId = "dataProcess.qc.action", width = "100%", label = "Apply QC"),
column(9, uiOutput("showPlot.qc"))
)
)),
# HVGs -------------------------------------------------------------------------
tabPanel(title = "Identify variable genes",
fluidRow(
column(6,
h4("Expression Cutoff"),
column(6,numericInput(inputId = "numericInput.seurat.hvg.x.min",
label = "Minimum", value = 1, width = "100%")),
column(6,numericInput(inputId = "numericInput.seurat.hvg.x.max",
label = "Maximum", value = "Inf", width = "100%"))
),
column(6,
h4("Dispersion Cutoff"),
column(6,numericInput(inputId = "numericInput.seurat.hvg.y.min",
label = "Minimum", value = 1,width = "100%")),
column(6,numericInput(inputId = "numericInput.seurat.hvg.y.max",
label = "Maximum", value = "Inf",width = "100%"))
),
column(12,
actionButton(inputId = "dataProcess.hvg.action", width = "100%", label = "Get Variable Genes"),
uiOutput("showPlot.hvg")
)
)),
# PCA tSNE ------------------------------------------------------------------------
tabPanel(title = "Dimension Reduction",
fluidRow(
box(width = 6, title = "PCA Analysis",
column(6,
selectInput(inputId = "selectInput.seurat.pca", label = "Genes to be used", width = "100%",
choices = c("All Genes", "HVGs", "Selected Genes"), selected = "HVGs")),
column(6,
textInput(inputId = "textInput.seurat.pca", label = "Selected Genes (If Applicable)",
width = "100%", placeholder = "Input selected genes")),
actionButton(inputId = "dataProcess.pca.action", width = "100%", label = "Get PCA Plot"),
uiOutput("showPlot.pca")
),
box(width = 6, title = "tSNE Analysis",
column(4,
selectInput(inputId = "selectInput.seurat.tsne.method", label = "tSNE Method",width = "100%",
choices = c("Seurat", "Rtsne"), selected = "Seurat")),
column(4,
selectInput(inputId = "selectInput.seurat.tsne", label = "Features to be used",width = "100%",
choices = c("Selected PCs", "HVGs", "Selected Genes"), selected = "HVGs")),
column(4,
textInput(inputId = "textInput.seurat.tsne", label = "Select Features:",width = "100%",
placeholder = "Input selected genes or PCs (such as 1,2,4 or 1-3)")),
column(4,
sliderInput(inputId = "sliderInput.seurat.tsne.perplexity", label = "perplexity",
min = 0, max = 150, value = 30, round = T, width = "100%")),
column(4,
sliderInput(inputId = "sliderInput.seurat.tsne.theta", label = "theta",
min = 0, max = 1, value = 0.5, round = F, width = "100%")),
column(4,
sliderInput(inputId = "sliderInput.seurat.tsne.max_iter", label = "iterations",
min = 100, max = 2500, value = 1000, round = T, width = "100%")),
actionButton(inputId = "dataProcess.tsne.action", width = "100%", label = "Get tSNE Plot"),
uiOutput("showPlot.tsne")
)
)),
# Clustering -------------------------------------------------------------------------
tabPanel(title = "Clustering",
fluidRow(
box(width = 6, title = "Find Clusters",
column(6,
selectInput(inputId = "selectInput.seurat.cluster", label = "Features to be used",width = "100%",
choices = c("Selected PCs", "tSNEs", "HVGs", "Selected Genes"), selected = "HVGs")),
column(6,
textInput(inputId = "textInput.seurat.cluster.feature", label = "Select Features:",width = "100%",
placeholder = "Input selected genes or PCs (such as 1,2,4 or 1-3)")),
column(4,
sliderInput(inputId = "sliderInput.seurat.cluster.resolution", label = "resolution",
min = 0, max = 10, value = 0.8, step = 0.1, round = F, width = "100%")),
column(4,
sliderInput(inputId = "sliderInput.seurat.cluster.k.param", label = "k.param",
min = 0, max = 150, value = 30, round = T, width = "100%")),
column(4,
sliderInput(inputId = "sliderInput.seurat.cluster.k.scale", label = "k.scale",
min = 0, max = 150, value = 30, round = T, width = "100%")),
actionButton(inputId = "dataProcess.cluster.action", width = "100%", label = "Get Clusters"),
uiOutput("showPlot.cluster.tsne")
),
tabBox(width = 6,
tabPanel(title = "Differential Expression Genes",
column(6,
uiOutput("showCluster.deg.cat")),
# column(6,
# checkboxInput(inputId = "checkboxInput.seurat.deg.scale", label = "Do Scale",
# width = "100%", value =F)),
column(6,
sliderInput(inputId = "sliderInput.seurat.deg.pct", label = "min.pct",
min = 0, max = 1, value = 0.1, step = 0.01, round = F, width = "100%")),
column(6,
sliderInput(inputId = "sliderInput.seurat.deg.th", label = "thresh.use",
min = 0, max = 10, value = 1, step = 0.01, round = F, width = "100%")),
column(6,
sliderInput(inputId = "sliderInput.seurat.deg.num", label = "DEGs Num per Group",
min = 1, max = 100, value = 10, round = T, width = "100%")),
actionButton(inputId = "dataProcess.cluster.deg.action", width = "100%", label = "Get Heatmap"),
uiOutput("showPlot.cluster.heatmap")
),
tabPanel(title = "Lightening Plot",
column(6,
textInput(inputId = "textInput.seurat.light.gene", label = "Input gene(s)",
width = "100%", placeholder = "Input gene")),
actionButton(inputId = "dataProcess.cluster.light.action", width = "100%", label = "Get LighteningPlot"),
uiOutput("showPlot.cluster.light")
)
)
))
)
),
# Cluster -------------------------------------------------------------------------
tabItem(tabName = "tSNE and Clustering"
),
tabItem(tabName = "pointPlot"
# DEG
)
)
)
# page ---------------------------------------------------------------------------------------------------------------------
ui <- dashboardPage(title = "Interactive Data Analysis", skin = "purple",
header = header, sidebar = sidebar, body = body)
lizc07/iDA documentation built on May 29, 2019, 3:42 a.m.
R Package Documentation
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#' @include global.R
############
# ui
#########
#' @import shinydashboard
# header ---------------------------------------------------------------------------------------------------------------------
header <- dashboardHeader(title = "iDA", disable = F)
# sidebar ---------------------------------------------------------------------------------------------------------------------
sidebar <- dashboardSidebar(
#sidebarSearchForm(label = "Enter a number", "searchText", "searchButton"),
sidebarMenu(
# Setting id makes input$tabs give the tabName of currently-selected tab
id = "tabs",
menuItem("Load Data", tabName = "fileInput", icon = icon("dashboard"),badgeLabel = "Step1"),
menuItem("Process Data", icon = icon("th"), tabName = "dataProcess", badgeLabel = "Step2",
badgeColor = "green"),
menuItem("Advanced Options", icon = icon("bar-chart-o"),badgeLabel = "Step3",
badgeColor = "green"),
fluidRow(column(12,
uiOutput("showCategory"),
uiOutput("showPlotOption.color"),
uiOutput("showPlotOption.shape"),
sliderInput(inputId = "sliderInput.plot.height", label = "Plot Height",
min = 0, max = 5000, value = 500, step = 10, round = T, width = "100%")),
column(12, align = "center", hr(),downloadButton("pbmc.save", "Save Workspace"))
)
))
# body ---------------------------------------------------------------------------------------------------------------------
body <- dashboardBody(
tabItems(
tabItem(tabName = "fileInput",
tabBox(title = "Loading Files", id = "tabBox.fileInput", width = 12,
tabPanel(title = "CSV Files",
fluidRow(
column(12,
column(10,
fileInput("fileInput.csv.umi", "Expression Data (UMI count prefered, Gene x Cell) - Required!", width = "100%",
accept = c(
"text/csv",
"text/comma-separated-values,text/plain",
".csv")
)
),
br(),column(2, checkboxInput(inputId = "fileInput.csv.umi.transpose", "Do Transpose", value = F))
),
column(12,
column(10,
fileInput("fileInput.csv.annot", "Cell Annotation (Cell x Category)", width = "100%",
accept = c(
"text/csv",
"text/comma-separated-values,text/plain",
".csv")
)
),
br(),column(2, checkboxInput(inputId = "fileInput.csv.annot.transpose", "Do Transpose", value = F))
)
)
),
tabPanel(title = "RData File",
fileInput("fileInput.rdata", "Saved RData, including Expression and Annotation Data (Saved by iDA)", width = "100%",
accept = c(".RData")
)
)
),
box(actionButton(inputId = "fileInput.action", width = "100%", label = "Submit"), status = "success", width = 12),
infoBoxOutput("infoBox.umi", width = 6),
infoBoxOutput("infoBox.annot", width = 6),
uiOutput("fileInput.error"),
uiOutput("fileInput.submitted")
),
tabItem(tabName = "dataProcess",
tabBox(title = "Start Analysis", width = 12,
#footer = "Produced by Zongcheng Li, using shiny", status = "primary", solidHeader = T, collapsible = F, collapsed = F,
# QC -------------------------------------------------------------------------
tabPanel(title = "Quality Control",
fluidRow(
column(6,
h4("Gene Number in each Cell"),
column(6,numericInput(inputId = "numericInput.seurat.gene.min",
label = "Minimum", value = 500, width = "100%")),
column(6,numericInput(inputId = "numericInput.seurat.gene.max",
label = "Maximum", value = "Inf", width = "100%"))
),
column(6,
h4("UMI Number in each Cell"),
column(6,numericInput(inputId = "numericInput.seurat.umi.min",
label = "Minimum", value = 10000,width = "100%")),
column(6,numericInput(inputId = "numericInput.seurat.umi.max",
label = "Maximum", value = "Inf",width = "100%"))
),
column(12,
actionButton(inputId = "dataProcess.qc.action", width = "100%", label = "Apply QC"),
column(9, uiOutput("showPlot.qc"))
)
)),
# HVGs -------------------------------------------------------------------------
tabPanel(title = "Identify variable genes",
fluidRow(
column(6,
h4("Expression Cutoff"),
column(6,numericInput(inputId = "numericInput.seurat.hvg.x.min",
label = "Minimum", value = 1, width = "100%")),
column(6,numericInput(inputId = "numericInput.seurat.hvg.x.max",
label = "Maximum", value = "Inf", width = "100%"))
),
column(6,
h4("Dispersion Cutoff"),
column(6,numericInput(inputId = "numericInput.seurat.hvg.y.min",
label = "Minimum", value = 1,width = "100%")),
column(6,numericInput(inputId = "numericInput.seurat.hvg.y.max",
label = "Maximum", value = "Inf",width = "100%"))
),
column(12,
actionButton(inputId = "dataProcess.hvg.action", width = "100%", label = "Get Variable Genes"),
uiOutput("showPlot.hvg")
)
)),
# PCA tSNE ------------------------------------------------------------------------
tabPanel(title = "Dimension Reduction",
fluidRow(
box(width = 6, title = "PCA Analysis",
column(6,
selectInput(inputId = "selectInput.seurat.pca", label = "Genes to be used", width = "100%",
choices = c("All Genes", "HVGs", "Selected Genes"), selected = "HVGs")),
column(6,
textInput(inputId = "textInput.seurat.pca", label = "Selected Genes (If Applicable)",
width = "100%", placeholder = "Input selected genes")),
actionButton(inputId = "dataProcess.pca.action", width = "100%", label = "Get PCA Plot"),
uiOutput("showPlot.pca")
),
box(width = 6, title = "tSNE Analysis",
column(4,
selectInput(inputId = "selectInput.seurat.tsne.method", label = "tSNE Method",width = "100%",
choices = c("Seurat", "Rtsne"), selected = "Seurat")),
column(4,
selectInput(inputId = "selectInput.seurat.tsne", label = "Features to be used",width = "100%",
choices = c("Selected PCs", "HVGs", "Selected Genes"), selected = "HVGs")),
column(4,
textInput(inputId = "textInput.seurat.tsne", label = "Select Features:",width = "100%",
placeholder = "Input selected genes or PCs (such as 1,2,4 or 1-3)")),
column(4,
sliderInput(inputId = "sliderInput.seurat.tsne.perplexity", label = "perplexity",
min = 0, max = 150, value = 30, round = T, width = "100%")),
column(4,
sliderInput(inputId = "sliderInput.seurat.tsne.theta", label = "theta",
min = 0, max = 1, value = 0.5, round = F, width = "100%")),
column(4,
sliderInput(inputId = "sliderInput.seurat.tsne.max_iter", label = "iterations",
min = 100, max = 2500, value = 1000, round = T, width = "100%")),
actionButton(inputId = "dataProcess.tsne.action", width = "100%", label = "Get tSNE Plot"),
uiOutput("showPlot.tsne")
)
)),
# Clustering -------------------------------------------------------------------------
tabPanel(title = "Clustering",
fluidRow(
box(width = 6, title = "Find Clusters",
column(6,
selectInput(inputId = "selectInput.seurat.cluster", label = "Features to be used",width = "100%",
choices = c("Selected PCs", "tSNEs", "HVGs", "Selected Genes"), selected = "HVGs")),
column(6,
textInput(inputId = "textInput.seurat.cluster.feature", label = "Select Features:",width = "100%",
placeholder = "Input selected genes or PCs (such as 1,2,4 or 1-3)")),
column(4,
sliderInput(inputId = "sliderInput.seurat.cluster.resolution", label = "resolution",
min = 0, max = 10, value = 0.8, step = 0.1, round = F, width = "100%")),
column(4,
sliderInput(inputId = "sliderInput.seurat.cluster.k.param", label = "k.param",
min = 0, max = 150, value = 30, round = T, width = "100%")),
column(4,
sliderInput(inputId = "sliderInput.seurat.cluster.k.scale", label = "k.scale",
min = 0, max = 150, value = 30, round = T, width = "100%")),
actionButton(inputId = "dataProcess.cluster.action", width = "100%", label = "Get Clusters"),
uiOutput("showPlot.cluster.tsne")
),
tabBox(width = 6,
tabPanel(title = "Differential Expression Genes",
column(6,
uiOutput("showCluster.deg.cat")),
# column(6,
# checkboxInput(inputId = "checkboxInput.seurat.deg.scale", label = "Do Scale",
# width = "100%", value =F)),
column(6,
sliderInput(inputId = "sliderInput.seurat.deg.pct", label = "min.pct",
min = 0, max = 1, value = 0.1, step = 0.01, round = F, width = "100%")),
column(6,
sliderInput(inputId = "sliderInput.seurat.deg.th", label = "thresh.use",
min = 0, max = 10, value = 1, step = 0.01, round = F, width = "100%")),
column(6,
sliderInput(inputId = "sliderInput.seurat.deg.num", label = "DEGs Num per Group",
min = 1, max = 100, value = 10, round = T, width = "100%")),
actionButton(inputId = "dataProcess.cluster.deg.action", width = "100%", label = "Get Heatmap"),
uiOutput("showPlot.cluster.heatmap")
),
tabPanel(title = "Lightening Plot",
column(6,
textInput(inputId = "textInput.seurat.light.gene", label = "Input gene(s)",
width = "100%", placeholder = "Input gene")),
actionButton(inputId = "dataProcess.cluster.light.action", width = "100%", label = "Get LighteningPlot"),
uiOutput("showPlot.cluster.light")
)
)
))
)
),
# Cluster -------------------------------------------------------------------------
tabItem(tabName = "tSNE and Clustering"
),
tabItem(tabName = "pointPlot"
# DEG
)
)
)
# page ---------------------------------------------------------------------------------------------------------------------
ui <- dashboardPage(title = "Interactive Data Analysis", skin = "purple",
header = header, sidebar = sidebar, body = body)
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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