inst/shiny/ui.R
In JinmiaoChenLab/cytofkit2: cytofkit2: an integrated mass cytometry data analysis pipeline. Cytofkit provides functions for data pre-processing, fast clustering, data visualization through linear or non-linear dimensionality reduction, automatic identification of cell subsets, and inference of the relatedness between cell subsets
library(shiny)
library(plotly)
library(ggplot2)
library(shinyjs)
library(DT)
library(shinydashboard)
library(shinyalert)
library(shinyFiles)
library(shinyWidgets)
shiny_one_panel = fluidPage(
titlePanel("Interactive Exploration of cytofkit Analysis Results"),
hr(),
fluidRow(
## side panel--take 1/4 space
column(3,
h4('Load cytofkit RData:'),
wellPanel(
fileInput(inputId = 'cytofkitObj',
label = NULL,
multiple = FALSE,
accept = c('text/RData', '.RData')),
shinyFilesButton('serverObj', label = "Server File Select", title = "Please select your RData", multiple = FALSE),
textOutput("queryText"),
textOutput("rdata_desc"),
fluidRow(
column(6,
actionButton("goButton", "Submit", icon = icon("hand-o-right"))
),
column(6,
actionButton("reset", "Reset Data", icon = icon("repeat"))
)
)
),
hr(),
conditionalPanel(" input.main_panel == 'C_panel' && input.C_clusterTabs == 'C_tab1' ",
h4("Plot Control:"),
wellPanel(
checkboxInput(inputId = "C_addLabel", label = "Add Cluster Labels", value = TRUE),
checkboxInput(inputId = "C_labelRepel", label = "Repel Cluster Labels", value = FALSE),
checkboxInput(inputId = "C_facetPlot", label = "Separate Plot by:", value = FALSE),
# fluidRow(column(5, checkboxInput(inputId = "C_facetPlot", label = "Separate Plot by:", value = FALSE))
# ,
# column(7, selectInput("sample_info_selection", label = NULL, choices = NULL,
# selected = NULL)))
selectInput("sample_info_selection", label = NULL, choices = NULL,
selected = NULL)
),
downloadButton("PDFClusterPlot", "Download Cluster Plot in PDF")
# actionButton("PDFClusterPlot", "Download Cluster Plot in PDF", icon = icon("download"))
),
conditionalPanel(" input.main_panel == 'M_panel' && input.M_markerTabs == 'M_tab1' ",
h4("Plot Control:"),
wellPanel(
selectInput('M_heatmap_dendrogram', strong('Heatmap Dendrogram:'),
choices = c("both","row","column","none"),
selected = "both", width = "100%"),
selectInput('M_heatmap_colorPalette', strong('Color Palette:'),
choices = c("bluered", "greenred", "spectral1", "spectral2"),
selected = "bluered", width = "100%")
),
downloadButton("PDFHeatmap", "Download Marker Heatmap in PDF")
# actionButton("PDFHeatmap", "Download Marker Heatmap in PDF", icon = icon("download"))
),
conditionalPanel(" input.main_panel == 'M_panel' && input.M_markerTabs == 'M_tab2' ",
h4("Plot Control:"),
wellPanel(
# actionButton("PDFExpPlot", "Download Exp Plot in PDF", icon = icon("download"))
downloadButton("PDFExpPlot", "Download Exp Plot in PDF")
)),
conditionalPanel(" input.main_panel == 'M_panel' && input.M_markerTabs == 'M_tab3' ",
h4("Plot Control:"),
wellPanel(
# actionButton("PDFHistogram", "Download Histogram in PDF", icon = icon("download"))
downloadButton("PDFHistogram", "Download Histogram in PDF")
)),
conditionalPanel(" input.main_panel == 'S_panel' && input.S_sampleTabs == 'S_tab1' ",
h4("Plot Control:"),
wellPanel(
selectInput('S_heatmap_dendrogram', strong('Heatmap Dendrogram:'),
choices = c("both","row","column","none"),
selected = "both", width = "100%"),
selectInput('S_heatmap_colorPalette', strong('Color Palette:'),
choices = c("bluered", "greenred", "spectral1", "spectral2"),
selected = "bluered", width = "100%")
),
# actionButton("PDFSamHeat", "Download Sample Heatmap in PDF", icon = icon("download"))
downloadButton("PDFSamHeat", "Download Sample Heatmap in PDF")
),
conditionalPanel(" input.main_panel == 'S_panel' && input.S_sampleTabs == 'S_tab2' ",
h4("Plot Control:"),
# actionButton("PDFrateChange", "Download Rate Change Plot in PDF", icon = icon("download"))
downloadButton("PDFrateChange", "Download Rate Change Plot in PDF")
),
conditionalPanel(" input.main_panel == 'P_panel' && input.P_progressionTabs == 'P_tab1' ",
h4("Plot Control:"),
wellPanel(
checkboxInput(inputId = "P_addLabel", label = "Add Cluster Labels", value = TRUE),
checkboxInput(inputId = "P_labelRepel", label = "Repel Cluster Labels", value = FALSE),
checkboxInput(inputId = "P_facetPlot", label = "Separate Plot by Samples", value = FALSE)
),
# actionButton("PDFScatter", "Download Scatterplot in PDF", icon = icon("download"))
downloadButton("PDFScatter", "Download Scatterplot in PDF")
),
conditionalPanel(" input.main_panel == 'P_panel' && input.P_progressionTabs == 'P_tab2' ",
h4("Plot Control:"),
wellPanel(
checkboxInput(inputId = "P_addLabel2", label = "Add Cluster Labels", value = TRUE)
),
# actionButton("PDFmarkerPlot", "Download Marker Plot in PDF", icon = icon("download"))
downloadButton("PDFmarkerPlot", "Download Marker Plot in PDF")
),
br(),
fluidRow(
column(6,
sliderInput(inputId="tab_w", label = "PDF width(in):",
min=3, max=20, value=8, width=100, ticks=FALSE)
),
column(6,
sliderInput(inputId="tab_h", label = "PDF height(in):",
min=3, max=20, value=8, width=100, ticks=FALSE)
)),
# actionButton("OpenDir", "Open download folder", icon = icon("folder")),
hr(),
h4("Sample Filter:"),
wellPanel(uiOutput("selectAll"),
uiOutput("sampleSelect")),
hr(),
h4("Data Summary:"),
wellPanel(
h5("Expression Data:"),
textOutput("summaryText1"),
h5("Markers used for dimension reduction and clustering:"),
textOutput("summaryText5"),
h5("Cluster Method(s):"),
textOutput("summaryText2"),
h5("Visualization Method(s):"),
textOutput("summaryText3"),
h5("Progression Method(s):"),
textOutput("summaryText4")
),
hr(),
h4("Save results:"),
h5("Outputs to save"),
fluidRow(
# column(4,
# checkboxInput(inputId = "saveFCS", label = "FCS", value = TRUE)
# ),
column(6,
checkboxInput(inputId = "saveRData", label = "RData", value = TRUE)
),
column(6,
checkboxInput(inputId = "saveCsv", label = "csv", value = FALSE)
)
),
# actionButton("saveButton", "Save Data", icon = icon("download")),
downloadButton("saveButton", "Save Data"),
downloadButton("reportButton", "Generate Report"),
hr(),
h4(tags$a(href="mailto:jinmiao@gmail.com,a0124008@u.nus.edu?subject=[cytofkit-question]",
"Contact Us")),
imageOutput("logo", height = "60px")
),
## main panel--take 3/4 space
column(9,
tabsetPanel(id="main_panel", type = "pills",
tabPanel(title="Cluster Panel", value="C_panel", fluidPage(
hr(),
tabsetPanel(id="C_clusterTabs", type = "tabs",
tabPanel(title="Cluster Plot", value="C_tab1",
br(),
fluidRow(
column(3,
uiOutput("C_PlotMethod")
),
column(3,
uiOutput("C_PlotFunction")
),
column(3,
numericInput("C_PointSize", "Point Size:", value = 1)
),
column(3,
numericInput("C_LabelSize", "Label Size:", value = 12)
)
),
uiOutput("C_clusterSelect"),
hr(),
plotOutput("C_ScatterPlot", width = "100%")
),
tabPanel(title="Change Cluster Color", value="C_tab2",
br(),
wellPanel(
uiOutput("C_colourCluster")
),
hr(),
lapply(1:100, function(i) {
uiOutput(paste0('Cluster_', i, '_col'))
}),
hr(),
fluidRow(
column(3,
actionButton("C_updateClusterColor", "Update Cluster Color",
icon = icon("hand-o-right"), width = "100%")
),
column(3,
actionButton("C_revertClusterColor", "Revert to default",
icon = icon("hand-o-right"), width = "100%")
),
column(6)
),
hr()),
tabPanel(title="Annotate Clusters", value="C_tab3",
br(),
wellPanel(
uiOutput("C_labelCluster"),
uiOutput("C_labelCluster_name")
),
hr(),
lapply(1:100, function(i) {
uiOutput(paste0('Cluster', i))
}),
hr(),
actionButton("updatelabel", "Submit Cluster Label", icon = icon("hand-o-right")),
hr()),
tabPanel(title="Run FlowSOM", value="C_tab4",
br(),
h4("FlowSOM Clustering Setup:"),
hr(),
wellPanel(
numericInput("C_FlowSOM_k", "Cluster k", value = 10, width = "30%"),
uiOutput("C_markerSelect")
),
hr(),
actionButton("C_runFlowSOM", "Run FlowSOM", icon = icon("hand-pointer-o")))
)
)),
tabPanel(title = "Marker Panel", value = "M_panel", fluidPage(
hr(),
tabsetPanel(id="M_markerTabs", type = "tabs",
tabPanel(title="Expression Heat Map", value="M_tab1",
br(),
fluidRow(
column(4,
uiOutput("M_plotCluster")
),
column(2,
selectInput('M_plotMethod', strong('Heatmap Type:'),
choices = c("mean", "median"),
selected = "mean", width = "100%")
),
column(2,
selectInput('M_scaleMethod', strong('Scale Data:'),
choices = c("none", "row", "column"),
selected = "none", width = "100%")
),
column(2,
numericInput("M_rowLabelSize", "Row Label Size:", value = 1, step = 0.5)
),
column(2,
numericInput("M_colLabelSize", "Col Label Size:", value = 1, step = 0.5)
)
),
fluidRow(
column(10,
uiOutput("M_heatmapmarkerSelect")
),
column(2,
actionButton("M_heatmapSelectAll", "All Markers"),
actionButton("M_updateHeatmap", "Update Plot")
)
),
hr(),
plotOutput("M_heatmapPlot", width = "100%")),
tabPanel(title="Expression Level Plot", value="M_tab2",
br(),
fluidRow(
column(3,
uiOutput("M_PlotMethod")
),
column(3,
numericInput("M_PointSize", "Point Size:", value = 1),
sliderInput("M_Alpha", "Transparency:", value = 1, min = 0, max = 1, step = 0.1)
),
column(3,
selectInput('M_colorPalette', label = "Color Palette:",
choices = c("bluered", "spectral1", "spectral2", "heat"),
selected = "bluered", width = "100%")
),
column(3,
selectInput('M_ScaleOptions', label = "Scaling Range:",
choices = c("Local", "Global"),
selected = "Local", width = "100%"),
selectInput('M_scaledData', label = "Centering:",
choices = c("Un-centered", "Centered"),
selected = "Un-centered", width = "100%")
)
),
fluidRow(
column(10,
uiOutput("M_PlotMarker")
),
column(2,
actionButton("M_chooseAllMarker", "All Markers"),
actionButton("M_updateExPlot", "Update Plot")
)
),
hr(),
plotOutput("M_markerExpressionPlot", width = "100%")),
tabPanel(title="Expression Histogram", value="M_tab3",
br(),
fluidRow(
column(4,
uiOutput("M_stackFactor")
),
column(2,
numericInput("M_markerTextSize", "Marker Text Size:",
value = 12, step = 1, min=1, max=15)
),
column(2,
numericInput("M_xlab_size", "x Label Size:",
value = 2, step = 1, min=1, max=10)
),
column(2,
numericInput("M_legendTextSize", "Legend Size:",
value = 1, step = 0.5, min=1, max=10)
),
column(2,
numericInput("M_legendRow", "Legend Row:",
value = 2, step = 1, min=1, max=10)
)
),
fluidRow(
column(10,
uiOutput("M_markerSelect")
),
column(2,
actionButton("M_histSelectAll", "All Markers")
)
),
hr(),
actionButton("M_updateDensityPlot", "Update Plot", icon = icon("hand-pointer-o")),
plotOutput("M_stackDensityPlot", width = "100%")),
tabPanel(title="Update Marker Names", value="M_tab4",
h5('Type in Your New Name for Each Marker:'),
hr(),
lapply(1:100, function(i) {
uiOutput(paste0('Marker_', i, "_name"))
}),
hr(),
actionButton("C_updateMarkerNames", "Update Marker Name", icon = icon("hand-pointer-o")))
)
)),
tabPanel(title = "Sample Panel", value = "S_panel", fluidPage(
hr(),
tabsetPanel(id="S_sampleTabs", type = "tabs",
tabPanel(title="Cell Percentage Heatmap", value="S_tab1",
br(),
fluidRow(
column(4,
uiOutput("S_plotCluster")
),
column(2,
selectInput('S_plotMethod', strong('Heatmap Type:'),
choices = c("percentage"),
selected = "percentage", width = "100%")
),
column(2,
selectInput('S_scaleMethod', strong('Scale Data:'),
choices = c("none", "row", "column"),
selected = "none", width = "100%")
),
column(2,
numericInput("S_rowLabelSize", "Row Label Size:", value = 1, step = 0.5)
),
column(2,
numericInput("S_colLabelSize", "Col Label Size:", value = 1, step = 0.5)
)
),
hr(),
plotOutput("S_heatmapPlot", width = "100%")
),
tabPanel(title="Cell Percentage Line Chart", value="S_tab2",
br(),
uiOutput("S_clusterMethod2"),
uiOutput("S_clusterFilter"),
hr(),
plotOutput("S_rateChangePlot", width = "100%")
),
tabPanel(title="Regroup Samples", value="S_tab3",
br(),
h4("Type in the Group Name for Each Sample:"),
lapply(1:100, function(i) {
uiOutput(paste0('S_sample', i))
}),
hr(),
textInput("sampleGroupLevels", "Group Name Levels: (to order the group names)",
value = "", width = "100%",
placeholder = "Type in group names in order, seperated by semicolon(;)"),
hr(),
fluidRow(
column(3,
actionButton("updateSampleGroups", "Submit New Sample Groups", icon = icon("hand-o-right"))
),
column(3,
actionButton("revertSampleNames", "Revert to Old Sample Names", icon = icon("hand-o-right"))
),
column(6)
),
hr())
)
)),
tabPanel(title="Progression Panel", value = "P_panel", fluidPage(
hr(),
tabsetPanel(id="P_progressionTabs", type = "tabs",
tabPanel(title="Subset Relationship Plot", value="P_tab1",
br(),
fluidRow(
column(3,
uiOutput("P_xlab")
),
column(3,
uiOutput("P_ylab")
),
column(3,
numericInput("P_PointSize", "Point Size:", value = 3)
),
column(3,
numericInput("P_LabelSize", "Label Size:", value = 8)
)
),
plotOutput("P_scatterPlot", width = "80%")),
tabPanel(title="Marker Expression Profile", value="P_tab2",
br(),
fluidRow(
column(3,
uiOutput("P_orderBy")
),
column(2,
numericInput("P_LabelSize2", "Label Size:", value = 5)
),
column(7,
uiOutput("P_clusterSelect")
)
),
hr(),
uiOutput("P_markerSelect"),
hr(),
fluidRow(
column(3,
actionButton("P_updateRegressionPlot", "Update Plot", icon = icon("hand-pointer-o"))
),
column(2,
checkboxInput("P_reverseOrder", label = "Reverse Order", value = FALSE)
),
column(3,
checkboxInput("P_combineTrends", label = "Combine Trend Lines", value = FALSE)
),
column(4)
),
plotOutput("P_markerPlot", width = "100%")),
tabPanel(title="Run Diffusion Map", value="P_tab3",
br(),
h4("Diffusionmap Setup:"),
wellPanel(
h5("Cluster-based down-sampling to remove subset aboundance heterogeneity"),
fluidRow(
column(4,
uiOutput("P_clusterMethod")
),
column(4,
numericInput("P_clusterSampleSize", "Cluster Sample Size", value = 500,
min = 10, max = 1000, step = 5, width = "100%")
),
column(4,
selectInput('P_sampleMethod', 'Downsample Method:', choices = c("ceil", "all", "fixed", "min"),
selected = "ceil", width = "100%")
)
),
tableOutput('P_clusterTable'),
uiOutput("P_clusterFilter"),
hr(),
h5("Diffusionmap Parameters"),
fluidRow(
column(6,
selectInput('P_distMethod', 'Distance calculation Method:', choices = c("euclidean"),
selected = "euclidean", width = "100%")
),
column(6,
numericInput("P_outDim", "Output Dimensionality:", value = 4,
min = 1, max = 6, step = 1, width = "100%")
)
)
),
hr(),
actionButton("P_runDiffusionmap", "Run Diffusionmap", icon = icon("hand-pointer-o")))
)
))
)
)
)
)
load_data_panel = fluidPage(
tags$div(title='The fcs files to be analyzed. One or multiple fcs files are allowed. When multiple fcs files are selected, cells from each fcs file are combined for analysis.'
, fileInput("rawfcs", "Raw FCS files", multiple = TRUE
, accept = c("FCSfile/fcs", '.fcs'))
, fileInput("sample_anno", "Meta data", multiple = FALSE, accept = c("Txtfile/txt", '.txt'))
)
, tags$div(title="Select the list of makers to be used for analysis."
, selectInput('markers', 'Markers', choices = NULL, selected = NULL
, selectize = TRUE
, multiple = TRUE)
# , pickerInput('pickermarker', label = "Picker Markers", choices = NULL, multiple = T
# , options = list(
# `actions-box` = TRUE
# , `live-search` = TRUE
# , `live-search-style` = 'contains'
# , `show-tick` = TRUE
# )
# )
)
, tags$div(title="A prefix that will be added to the names of result files."
, textInput('project_name', 'Project name', value = 'cytofkit')
)
, tags$div(title="When multiple fcs files are selected, cell expression data can be merged using one of the four different methods including \"ceil\",\"all\", \"min\",\"fixed\". \n\n\"ceil\" (the default option): up to a fixed number (specified by fixedNum) of cells are sampled without replacement from each fcs file and combined for analysis. \n\n\"all\": all cells from each fcs file are combined for analysis. \n\n\"min\": The minimum number of cells among all the selected fcs files are sampled from each fcs file and combined for analysis. \n\n\"fixed\": a fixed num (specified by fixedNum) of cells are sampled (with replacement when the total number of cell is less than fixedNum) from each fcs file and combined for analysis."
, selectInput('merge_method', 'Merge method', choices = c('all', 'min', 'ceil', 'fixed')
, selected = "ceil")
)
, tags$div(title="Up to fixedNum of cells from each fcs file are used for analysis."
, numericInput('fix_number', 'Fixed Number', value = 5000)
)
, tags$div(title="Data Transformation method, including \"cytofAsinh\"(Customized Asinh transformation for CyTOF data), \"autoLgcl\"(automatic logicle transformation for CyTOF data), \"logicle\"(customize your own parameters for logicle transformation) and \"none\"(if your data is already transformed)."
, selectInput('transform_method', 'Tranformation Method'
, choices = c('autoLgcl', 'cytofAsinh', 'logicle', 'arcsinh', 'none'))
)
, fluidRow(
tags$div(title=''
, downloadButton('download_analysis_res', 'Save result'))
)
, br()
, fluidRow(actionButton('reset', 'Reset')
, actionButton('submit', 'Submit')
, actionButton('quit', 'Quit'))
)
dr_panel = fluidPage(
tags$div(title="The method(s) used for visualizing the clustering results, multiple selections are allowed. Including \"pca\", \"isomap\", \"tsne\". \n\nWARNING: \"tsne\" is the default selection, \"isomap\" may take long time."
, selectInput('dr_method', 'Dimensionality reduction methods'
, choices = c('PCA', 'isoMAP', 'tSNE', 'UMAP')
, multiple = TRUE
, selected = 'tSNE')
)
, tags$div(title=''
, numericInput('tsne_perplexity', 'tSNE perplexity', value = 30)
)
, tags$div(title=''
, numericInput('tsne_interation', 'tSNE Max Iterations', value = 1000)
)
, tags$div(title=''
, numericInput('seed', 'Seed', value = 42))
)
cluster_panel = fluidPage(
tags$div(title="The method(s) for clustering, including \"DensVM\", \"ClusterX\", \"Rphenograph\", and \"FlowSOM\". "
, selectInput('cluster_method', 'Cluster Method(s)'
, choices = c('Rphenograph', 'ClusterX', 'DensVM', 'FlowSOM')
, multiple = TRUE
, selected = c('Rphenograph'))
)
, tags$div(title="Number of nearest neighbours to pass to Rphenograph."
, numericInput('rphenograph_k', 'Rphenograph_k', value = 30)
)
, tags$div(title="Number of clusters for meta clustering in FlowSOM."
, numericInput('flowsom_k', 'FlowSOM_k', value = 40))
)
pseudotime_panel = fluidPage(
tags$div(title="The method used for cellular progression analysis including \"diffusion map\" and \"isomap\"\n\nIf \"NULL\" was selected, no progression estimation will be performed."
, selectInput('progressionMethods', 'Cellular Progression'
, choices = c('NULL', 'diffusionmap', 'isomap')))
)
data_analysis_panel = fluidPage(fluidRow(
h2('Data analysis')
, box(
title = "Load data",
status = "primary",
width = 3,
# background = "orange",
solidHeader = TRUE,
collapsible = FALSE,
collapsed = FALSE
, load_data_panel
)# end of box
, box(
title = "Dimensionality Reduction",
status = "primary",
width = 3,
height = 630,
# background = "orange",
solidHeader = TRUE,
collapsible = FALSE,
collapsed = FALSE
, dr_panel
)# end of box
, box(
title = "Clustering",
status = "primary",
width = 3,
height = 630,
# background = "orange",
solidHeader = TRUE,
collapsible = FALSE,
collapsed = FALSE
, cluster_panel
)# end of box
, box(
title = "Pseudo-time",
status = "primary",
width = 3,
height = 630,
# background = "orange",
solidHeader = TRUE,
collapsible = FALSE,
collapsed = FALSE
, pseudotime_panel
)# end of box
)
)
res_panel = fluidPage()
########################################
dbHeader <- dashboardHeader(title = "cytofkit2")
dbHeader$children[[2]]$children <- tags$a(href='https://github.com/JinmiaoChenLab',
tags$img(src='https://avatars1.githubusercontent.com/u/8896007?s=400&u=b0029c2e64f405ea0a46d311239b674a430ec77c&v=4'
,height='60',width='60', align='left')
, tags$div('cytofkit2', style='color:white;font-family:arial rounded MT bold'))
dashboardPage(skin = "yellow",
dbHeader,
dashboardSidebar(
sidebarMenu(id = "sbm",
menuItem(tags$p(style = "display:inline;font-size: 20px;", "Data analysis"), tabName = "data_analysis", icon = icon('cog'))
, menuItem(tags$p(style = "display:inline;font-size: 20px;", "Results visualization"), tabName = "res_visualize", icon = icon('area-chart'))
)# end of sidebarMenu
),#end of dashboardSidebar
dashboardBody(
includeCSS("www/custom.css")
, useShinyalert()
, shinyjs::useShinyjs()
, tabItems(
tabItem(
tabName = "data_analysis"
, data_analysis_panel
) # End of tabItem
, tabItem(
tabName = "res_visualize"
, shiny_one_panel
) # End of tabItem
) # End of tabItems
)# end of dashboard body
)# end of dashboard page
JinmiaoChenLab/cytofkit2 documentation built on May 12, 2022, 8:09 a.m.
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library(shiny)
library(plotly)
library(ggplot2)
library(shinyjs)
library(DT)
library(shinydashboard)
library(shinyalert)
library(shinyFiles)
library(shinyWidgets)
shiny_one_panel = fluidPage(
titlePanel("Interactive Exploration of cytofkit Analysis Results"),
hr(),
fluidRow(
## side panel--take 1/4 space
column(3,
h4('Load cytofkit RData:'),
wellPanel(
fileInput(inputId = 'cytofkitObj',
label = NULL,
multiple = FALSE,
accept = c('text/RData', '.RData')),
shinyFilesButton('serverObj', label = "Server File Select", title = "Please select your RData", multiple = FALSE),
textOutput("queryText"),
textOutput("rdata_desc"),
fluidRow(
column(6,
actionButton("goButton", "Submit", icon = icon("hand-o-right"))
),
column(6,
actionButton("reset", "Reset Data", icon = icon("repeat"))
)
)
),
hr(),
conditionalPanel(" input.main_panel == 'C_panel' && input.C_clusterTabs == 'C_tab1' ",
h4("Plot Control:"),
wellPanel(
checkboxInput(inputId = "C_addLabel", label = "Add Cluster Labels", value = TRUE),
checkboxInput(inputId = "C_labelRepel", label = "Repel Cluster Labels", value = FALSE),
checkboxInput(inputId = "C_facetPlot", label = "Separate Plot by:", value = FALSE),
# fluidRow(column(5, checkboxInput(inputId = "C_facetPlot", label = "Separate Plot by:", value = FALSE))
# ,
# column(7, selectInput("sample_info_selection", label = NULL, choices = NULL,
# selected = NULL)))
selectInput("sample_info_selection", label = NULL, choices = NULL,
selected = NULL)
),
downloadButton("PDFClusterPlot", "Download Cluster Plot in PDF")
# actionButton("PDFClusterPlot", "Download Cluster Plot in PDF", icon = icon("download"))
),
conditionalPanel(" input.main_panel == 'M_panel' && input.M_markerTabs == 'M_tab1' ",
h4("Plot Control:"),
wellPanel(
selectInput('M_heatmap_dendrogram', strong('Heatmap Dendrogram:'),
choices = c("both","row","column","none"),
selected = "both", width = "100%"),
selectInput('M_heatmap_colorPalette', strong('Color Palette:'),
choices = c("bluered", "greenred", "spectral1", "spectral2"),
selected = "bluered", width = "100%")
),
downloadButton("PDFHeatmap", "Download Marker Heatmap in PDF")
# actionButton("PDFHeatmap", "Download Marker Heatmap in PDF", icon = icon("download"))
),
conditionalPanel(" input.main_panel == 'M_panel' && input.M_markerTabs == 'M_tab2' ",
h4("Plot Control:"),
wellPanel(
# actionButton("PDFExpPlot", "Download Exp Plot in PDF", icon = icon("download"))
downloadButton("PDFExpPlot", "Download Exp Plot in PDF")
)),
conditionalPanel(" input.main_panel == 'M_panel' && input.M_markerTabs == 'M_tab3' ",
h4("Plot Control:"),
wellPanel(
# actionButton("PDFHistogram", "Download Histogram in PDF", icon = icon("download"))
downloadButton("PDFHistogram", "Download Histogram in PDF")
)),
conditionalPanel(" input.main_panel == 'S_panel' && input.S_sampleTabs == 'S_tab1' ",
h4("Plot Control:"),
wellPanel(
selectInput('S_heatmap_dendrogram', strong('Heatmap Dendrogram:'),
choices = c("both","row","column","none"),
selected = "both", width = "100%"),
selectInput('S_heatmap_colorPalette', strong('Color Palette:'),
choices = c("bluered", "greenred", "spectral1", "spectral2"),
selected = "bluered", width = "100%")
),
# actionButton("PDFSamHeat", "Download Sample Heatmap in PDF", icon = icon("download"))
downloadButton("PDFSamHeat", "Download Sample Heatmap in PDF")
),
conditionalPanel(" input.main_panel == 'S_panel' && input.S_sampleTabs == 'S_tab2' ",
h4("Plot Control:"),
# actionButton("PDFrateChange", "Download Rate Change Plot in PDF", icon = icon("download"))
downloadButton("PDFrateChange", "Download Rate Change Plot in PDF")
),
conditionalPanel(" input.main_panel == 'P_panel' && input.P_progressionTabs == 'P_tab1' ",
h4("Plot Control:"),
wellPanel(
checkboxInput(inputId = "P_addLabel", label = "Add Cluster Labels", value = TRUE),
checkboxInput(inputId = "P_labelRepel", label = "Repel Cluster Labels", value = FALSE),
checkboxInput(inputId = "P_facetPlot", label = "Separate Plot by Samples", value = FALSE)
),
# actionButton("PDFScatter", "Download Scatterplot in PDF", icon = icon("download"))
downloadButton("PDFScatter", "Download Scatterplot in PDF")
),
conditionalPanel(" input.main_panel == 'P_panel' && input.P_progressionTabs == 'P_tab2' ",
h4("Plot Control:"),
wellPanel(
checkboxInput(inputId = "P_addLabel2", label = "Add Cluster Labels", value = TRUE)
),
# actionButton("PDFmarkerPlot", "Download Marker Plot in PDF", icon = icon("download"))
downloadButton("PDFmarkerPlot", "Download Marker Plot in PDF")
),
br(),
fluidRow(
column(6,
sliderInput(inputId="tab_w", label = "PDF width(in):",
min=3, max=20, value=8, width=100, ticks=FALSE)
),
column(6,
sliderInput(inputId="tab_h", label = "PDF height(in):",
min=3, max=20, value=8, width=100, ticks=FALSE)
)),
# actionButton("OpenDir", "Open download folder", icon = icon("folder")),
hr(),
h4("Sample Filter:"),
wellPanel(uiOutput("selectAll"),
uiOutput("sampleSelect")),
hr(),
h4("Data Summary:"),
wellPanel(
h5("Expression Data:"),
textOutput("summaryText1"),
h5("Markers used for dimension reduction and clustering:"),
textOutput("summaryText5"),
h5("Cluster Method(s):"),
textOutput("summaryText2"),
h5("Visualization Method(s):"),
textOutput("summaryText3"),
h5("Progression Method(s):"),
textOutput("summaryText4")
),
hr(),
h4("Save results:"),
h5("Outputs to save"),
fluidRow(
# column(4,
# checkboxInput(inputId = "saveFCS", label = "FCS", value = TRUE)
# ),
column(6,
checkboxInput(inputId = "saveRData", label = "RData", value = TRUE)
),
column(6,
checkboxInput(inputId = "saveCsv", label = "csv", value = FALSE)
)
),
# actionButton("saveButton", "Save Data", icon = icon("download")),
downloadButton("saveButton", "Save Data"),
downloadButton("reportButton", "Generate Report"),
hr(),
h4(tags$a(href="mailto:jinmiao@gmail.com,a0124008@u.nus.edu?subject=[cytofkit-question]",
"Contact Us")),
imageOutput("logo", height = "60px")
),
## main panel--take 3/4 space
column(9,
tabsetPanel(id="main_panel", type = "pills",
tabPanel(title="Cluster Panel", value="C_panel", fluidPage(
hr(),
tabsetPanel(id="C_clusterTabs", type = "tabs",
tabPanel(title="Cluster Plot", value="C_tab1",
br(),
fluidRow(
column(3,
uiOutput("C_PlotMethod")
),
column(3,
uiOutput("C_PlotFunction")
),
column(3,
numericInput("C_PointSize", "Point Size:", value = 1)
),
column(3,
numericInput("C_LabelSize", "Label Size:", value = 12)
)
),
uiOutput("C_clusterSelect"),
hr(),
plotOutput("C_ScatterPlot", width = "100%")
),
tabPanel(title="Change Cluster Color", value="C_tab2",
br(),
wellPanel(
uiOutput("C_colourCluster")
),
hr(),
lapply(1:100, function(i) {
uiOutput(paste0('Cluster_', i, '_col'))
}),
hr(),
fluidRow(
column(3,
actionButton("C_updateClusterColor", "Update Cluster Color",
icon = icon("hand-o-right"), width = "100%")
),
column(3,
actionButton("C_revertClusterColor", "Revert to default",
icon = icon("hand-o-right"), width = "100%")
),
column(6)
),
hr()),
tabPanel(title="Annotate Clusters", value="C_tab3",
br(),
wellPanel(
uiOutput("C_labelCluster"),
uiOutput("C_labelCluster_name")
),
hr(),
lapply(1:100, function(i) {
uiOutput(paste0('Cluster', i))
}),
hr(),
actionButton("updatelabel", "Submit Cluster Label", icon = icon("hand-o-right")),
hr()),
tabPanel(title="Run FlowSOM", value="C_tab4",
br(),
h4("FlowSOM Clustering Setup:"),
hr(),
wellPanel(
numericInput("C_FlowSOM_k", "Cluster k", value = 10, width = "30%"),
uiOutput("C_markerSelect")
),
hr(),
actionButton("C_runFlowSOM", "Run FlowSOM", icon = icon("hand-pointer-o")))
)
)),
tabPanel(title = "Marker Panel", value = "M_panel", fluidPage(
hr(),
tabsetPanel(id="M_markerTabs", type = "tabs",
tabPanel(title="Expression Heat Map", value="M_tab1",
br(),
fluidRow(
column(4,
uiOutput("M_plotCluster")
),
column(2,
selectInput('M_plotMethod', strong('Heatmap Type:'),
choices = c("mean", "median"),
selected = "mean", width = "100%")
),
column(2,
selectInput('M_scaleMethod', strong('Scale Data:'),
choices = c("none", "row", "column"),
selected = "none", width = "100%")
),
column(2,
numericInput("M_rowLabelSize", "Row Label Size:", value = 1, step = 0.5)
),
column(2,
numericInput("M_colLabelSize", "Col Label Size:", value = 1, step = 0.5)
)
),
fluidRow(
column(10,
uiOutput("M_heatmapmarkerSelect")
),
column(2,
actionButton("M_heatmapSelectAll", "All Markers"),
actionButton("M_updateHeatmap", "Update Plot")
)
),
hr(),
plotOutput("M_heatmapPlot", width = "100%")),
tabPanel(title="Expression Level Plot", value="M_tab2",
br(),
fluidRow(
column(3,
uiOutput("M_PlotMethod")
),
column(3,
numericInput("M_PointSize", "Point Size:", value = 1),
sliderInput("M_Alpha", "Transparency:", value = 1, min = 0, max = 1, step = 0.1)
),
column(3,
selectInput('M_colorPalette', label = "Color Palette:",
choices = c("bluered", "spectral1", "spectral2", "heat"),
selected = "bluered", width = "100%")
),
column(3,
selectInput('M_ScaleOptions', label = "Scaling Range:",
choices = c("Local", "Global"),
selected = "Local", width = "100%"),
selectInput('M_scaledData', label = "Centering:",
choices = c("Un-centered", "Centered"),
selected = "Un-centered", width = "100%")
)
),
fluidRow(
column(10,
uiOutput("M_PlotMarker")
),
column(2,
actionButton("M_chooseAllMarker", "All Markers"),
actionButton("M_updateExPlot", "Update Plot")
)
),
hr(),
plotOutput("M_markerExpressionPlot", width = "100%")),
tabPanel(title="Expression Histogram", value="M_tab3",
br(),
fluidRow(
column(4,
uiOutput("M_stackFactor")
),
column(2,
numericInput("M_markerTextSize", "Marker Text Size:",
value = 12, step = 1, min=1, max=15)
),
column(2,
numericInput("M_xlab_size", "x Label Size:",
value = 2, step = 1, min=1, max=10)
),
column(2,
numericInput("M_legendTextSize", "Legend Size:",
value = 1, step = 0.5, min=1, max=10)
),
column(2,
numericInput("M_legendRow", "Legend Row:",
value = 2, step = 1, min=1, max=10)
)
),
fluidRow(
column(10,
uiOutput("M_markerSelect")
),
column(2,
actionButton("M_histSelectAll", "All Markers")
)
),
hr(),
actionButton("M_updateDensityPlot", "Update Plot", icon = icon("hand-pointer-o")),
plotOutput("M_stackDensityPlot", width = "100%")),
tabPanel(title="Update Marker Names", value="M_tab4",
h5('Type in Your New Name for Each Marker:'),
hr(),
lapply(1:100, function(i) {
uiOutput(paste0('Marker_', i, "_name"))
}),
hr(),
actionButton("C_updateMarkerNames", "Update Marker Name", icon = icon("hand-pointer-o")))
)
)),
tabPanel(title = "Sample Panel", value = "S_panel", fluidPage(
hr(),
tabsetPanel(id="S_sampleTabs", type = "tabs",
tabPanel(title="Cell Percentage Heatmap", value="S_tab1",
br(),
fluidRow(
column(4,
uiOutput("S_plotCluster")
),
column(2,
selectInput('S_plotMethod', strong('Heatmap Type:'),
choices = c("percentage"),
selected = "percentage", width = "100%")
),
column(2,
selectInput('S_scaleMethod', strong('Scale Data:'),
choices = c("none", "row", "column"),
selected = "none", width = "100%")
),
column(2,
numericInput("S_rowLabelSize", "Row Label Size:", value = 1, step = 0.5)
),
column(2,
numericInput("S_colLabelSize", "Col Label Size:", value = 1, step = 0.5)
)
),
hr(),
plotOutput("S_heatmapPlot", width = "100%")
),
tabPanel(title="Cell Percentage Line Chart", value="S_tab2",
br(),
uiOutput("S_clusterMethod2"),
uiOutput("S_clusterFilter"),
hr(),
plotOutput("S_rateChangePlot", width = "100%")
),
tabPanel(title="Regroup Samples", value="S_tab3",
br(),
h4("Type in the Group Name for Each Sample:"),
lapply(1:100, function(i) {
uiOutput(paste0('S_sample', i))
}),
hr(),
textInput("sampleGroupLevels", "Group Name Levels: (to order the group names)",
value = "", width = "100%",
placeholder = "Type in group names in order, seperated by semicolon(;)"),
hr(),
fluidRow(
column(3,
actionButton("updateSampleGroups", "Submit New Sample Groups", icon = icon("hand-o-right"))
),
column(3,
actionButton("revertSampleNames", "Revert to Old Sample Names", icon = icon("hand-o-right"))
),
column(6)
),
hr())
)
)),
tabPanel(title="Progression Panel", value = "P_panel", fluidPage(
hr(),
tabsetPanel(id="P_progressionTabs", type = "tabs",
tabPanel(title="Subset Relationship Plot", value="P_tab1",
br(),
fluidRow(
column(3,
uiOutput("P_xlab")
),
column(3,
uiOutput("P_ylab")
),
column(3,
numericInput("P_PointSize", "Point Size:", value = 3)
),
column(3,
numericInput("P_LabelSize", "Label Size:", value = 8)
)
),
plotOutput("P_scatterPlot", width = "80%")),
tabPanel(title="Marker Expression Profile", value="P_tab2",
br(),
fluidRow(
column(3,
uiOutput("P_orderBy")
),
column(2,
numericInput("P_LabelSize2", "Label Size:", value = 5)
),
column(7,
uiOutput("P_clusterSelect")
)
),
hr(),
uiOutput("P_markerSelect"),
hr(),
fluidRow(
column(3,
actionButton("P_updateRegressionPlot", "Update Plot", icon = icon("hand-pointer-o"))
),
column(2,
checkboxInput("P_reverseOrder", label = "Reverse Order", value = FALSE)
),
column(3,
checkboxInput("P_combineTrends", label = "Combine Trend Lines", value = FALSE)
),
column(4)
),
plotOutput("P_markerPlot", width = "100%")),
tabPanel(title="Run Diffusion Map", value="P_tab3",
br(),
h4("Diffusionmap Setup:"),
wellPanel(
h5("Cluster-based down-sampling to remove subset aboundance heterogeneity"),
fluidRow(
column(4,
uiOutput("P_clusterMethod")
),
column(4,
numericInput("P_clusterSampleSize", "Cluster Sample Size", value = 500,
min = 10, max = 1000, step = 5, width = "100%")
),
column(4,
selectInput('P_sampleMethod', 'Downsample Method:', choices = c("ceil", "all", "fixed", "min"),
selected = "ceil", width = "100%")
)
),
tableOutput('P_clusterTable'),
uiOutput("P_clusterFilter"),
hr(),
h5("Diffusionmap Parameters"),
fluidRow(
column(6,
selectInput('P_distMethod', 'Distance calculation Method:', choices = c("euclidean"),
selected = "euclidean", width = "100%")
),
column(6,
numericInput("P_outDim", "Output Dimensionality:", value = 4,
min = 1, max = 6, step = 1, width = "100%")
)
)
),
hr(),
actionButton("P_runDiffusionmap", "Run Diffusionmap", icon = icon("hand-pointer-o")))
)
))
)
)
)
)
load_data_panel = fluidPage(
tags$div(title='The fcs files to be analyzed. One or multiple fcs files are allowed. When multiple fcs files are selected, cells from each fcs file are combined for analysis.'
, fileInput("rawfcs", "Raw FCS files", multiple = TRUE
, accept = c("FCSfile/fcs", '.fcs'))
, fileInput("sample_anno", "Meta data", multiple = FALSE, accept = c("Txtfile/txt", '.txt'))
)
, tags$div(title="Select the list of makers to be used for analysis."
, selectInput('markers', 'Markers', choices = NULL, selected = NULL
, selectize = TRUE
, multiple = TRUE)
# , pickerInput('pickermarker', label = "Picker Markers", choices = NULL, multiple = T
# , options = list(
# `actions-box` = TRUE
# , `live-search` = TRUE
# , `live-search-style` = 'contains'
# , `show-tick` = TRUE
# )
# )
)
, tags$div(title="A prefix that will be added to the names of result files."
, textInput('project_name', 'Project name', value = 'cytofkit')
)
, tags$div(title="When multiple fcs files are selected, cell expression data can be merged using one of the four different methods including \"ceil\",\"all\", \"min\",\"fixed\". \n\n\"ceil\" (the default option): up to a fixed number (specified by fixedNum) of cells are sampled without replacement from each fcs file and combined for analysis. \n\n\"all\": all cells from each fcs file are combined for analysis. \n\n\"min\": The minimum number of cells among all the selected fcs files are sampled from each fcs file and combined for analysis. \n\n\"fixed\": a fixed num (specified by fixedNum) of cells are sampled (with replacement when the total number of cell is less than fixedNum) from each fcs file and combined for analysis."
, selectInput('merge_method', 'Merge method', choices = c('all', 'min', 'ceil', 'fixed')
, selected = "ceil")
)
, tags$div(title="Up to fixedNum of cells from each fcs file are used for analysis."
, numericInput('fix_number', 'Fixed Number', value = 5000)
)
, tags$div(title="Data Transformation method, including \"cytofAsinh\"(Customized Asinh transformation for CyTOF data), \"autoLgcl\"(automatic logicle transformation for CyTOF data), \"logicle\"(customize your own parameters for logicle transformation) and \"none\"(if your data is already transformed)."
, selectInput('transform_method', 'Tranformation Method'
, choices = c('autoLgcl', 'cytofAsinh', 'logicle', 'arcsinh', 'none'))
)
, fluidRow(
tags$div(title=''
, downloadButton('download_analysis_res', 'Save result'))
)
, br()
, fluidRow(actionButton('reset', 'Reset')
, actionButton('submit', 'Submit')
, actionButton('quit', 'Quit'))
)
dr_panel = fluidPage(
tags$div(title="The method(s) used for visualizing the clustering results, multiple selections are allowed. Including \"pca\", \"isomap\", \"tsne\". \n\nWARNING: \"tsne\" is the default selection, \"isomap\" may take long time."
, selectInput('dr_method', 'Dimensionality reduction methods'
, choices = c('PCA', 'isoMAP', 'tSNE', 'UMAP')
, multiple = TRUE
, selected = 'tSNE')
)
, tags$div(title=''
, numericInput('tsne_perplexity', 'tSNE perplexity', value = 30)
)
, tags$div(title=''
, numericInput('tsne_interation', 'tSNE Max Iterations', value = 1000)
)
, tags$div(title=''
, numericInput('seed', 'Seed', value = 42))
)
cluster_panel = fluidPage(
tags$div(title="The method(s) for clustering, including \"DensVM\", \"ClusterX\", \"Rphenograph\", and \"FlowSOM\". "
, selectInput('cluster_method', 'Cluster Method(s)'
, choices = c('Rphenograph', 'ClusterX', 'DensVM', 'FlowSOM')
, multiple = TRUE
, selected = c('Rphenograph'))
)
, tags$div(title="Number of nearest neighbours to pass to Rphenograph."
, numericInput('rphenograph_k', 'Rphenograph_k', value = 30)
)
, tags$div(title="Number of clusters for meta clustering in FlowSOM."
, numericInput('flowsom_k', 'FlowSOM_k', value = 40))
)
pseudotime_panel = fluidPage(
tags$div(title="The method used for cellular progression analysis including \"diffusion map\" and \"isomap\"\n\nIf \"NULL\" was selected, no progression estimation will be performed."
, selectInput('progressionMethods', 'Cellular Progression'
, choices = c('NULL', 'diffusionmap', 'isomap')))
)
data_analysis_panel = fluidPage(fluidRow(
h2('Data analysis')
, box(
title = "Load data",
status = "primary",
width = 3,
# background = "orange",
solidHeader = TRUE,
collapsible = FALSE,
collapsed = FALSE
, load_data_panel
)# end of box
, box(
title = "Dimensionality Reduction",
status = "primary",
width = 3,
height = 630,
# background = "orange",
solidHeader = TRUE,
collapsible = FALSE,
collapsed = FALSE
, dr_panel
)# end of box
, box(
title = "Clustering",
status = "primary",
width = 3,
height = 630,
# background = "orange",
solidHeader = TRUE,
collapsible = FALSE,
collapsed = FALSE
, cluster_panel
)# end of box
, box(
title = "Pseudo-time",
status = "primary",
width = 3,
height = 630,
# background = "orange",
solidHeader = TRUE,
collapsible = FALSE,
collapsed = FALSE
, pseudotime_panel
)# end of box
)
)
res_panel = fluidPage()
########################################
dbHeader <- dashboardHeader(title = "cytofkit2")
dbHeader$children[[2]]$children <- tags$a(href='https://github.com/JinmiaoChenLab',
tags$img(src='https://avatars1.githubusercontent.com/u/8896007?s=400&u=b0029c2e64f405ea0a46d311239b674a430ec77c&v=4'
,height='60',width='60', align='left')
, tags$div('cytofkit2', style='color:white;font-family:arial rounded MT bold'))
dashboardPage(skin = "yellow",
dbHeader,
dashboardSidebar(
sidebarMenu(id = "sbm",
menuItem(tags$p(style = "display:inline;font-size: 20px;", "Data analysis"), tabName = "data_analysis", icon = icon('cog'))
, menuItem(tags$p(style = "display:inline;font-size: 20px;", "Results visualization"), tabName = "res_visualize", icon = icon('area-chart'))
)# end of sidebarMenu
),#end of dashboardSidebar
dashboardBody(
includeCSS("www/custom.css")
, useShinyalert()
, shinyjs::useShinyjs()
, tabItems(
tabItem(
tabName = "data_analysis"
, data_analysis_panel
) # End of tabItem
, tabItem(
tabName = "res_visualize"
, shiny_one_panel
) # End of tabItem
) # End of tabItems
)# end of dashboard body
)# end of dashboard page
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