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ui.R
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# Close the window and shut down app----
jscode <- "shinyjs.closeWindow = function() { window.close(); }"
choice.palette <- list("ColorBrewer.seq"=c("Blues","BuGn","BuPu","GnBu","Greens",
"Greys","Oranges","OrRd","PuBu","PuBuGn",
"PuRd","Purples", "RdPu", "Reds","YlGn",
"YlGnBu","YlOrBr","YlOrRd"),
"colorBrewer.div"=c("BrBG","PiYG","PRGn",
"PuOr","RdBu","RdGy",
"RdYlBu","RdYlGn","Spectral"),
"viridis"=c("magma","inferno","plasma",
"viridis","cividis"))
# Shiny UI----
# Shiny header----
header <- dashboardHeader(
title = span(
"ScRNA-seq Data Portal for T cell in Pan-Cancer"
# span("s", style = "color: #F3746C; font-size: 24px; font-weight: bold"),
# span("ingle "),
# span("c", style = "color: #F3746C; font-size: 24px; font-weight: bold"),
# span("ell RNA-seq "),
# span("D", style = "color: #F3746C; font-size: 24px; font-weight: bold"),
# span("ata "),
# span("V", style = "color: #F3746C; font-size: 24px; font-weight: bold"),
# span("isualization and "),
# span("A", style = "color: #F3746C; font-size: 24px; font-weight: bold"),
# span("nalysis")
),
titleWidth = 550,
tags$li(
class = "dropdown",
extendShinyjs(text = jscode, functions = c("closeWindow")),
shiny::actionButton(
inputId = "close",
label = "Shut down",
width = "120px",
icon = icon("window-close"),
style = "color: #fff; background-color: #337ab7; border-color: #2e6da4"
)
)
)
# Shiny sidebar----
sidebar <- dashboardSidebar(
tags$head(
includeScript("./www/google-analytics.js"),
tags$style(
type = 'text/css',
".nav-tabs {font-size: 14px} ",
".main-sidebar {font-size: 16px}"
)
),
sidebarMenu(
menuItem("Embedding", tabName = "Embedding", icon = icon("spinner")),
menuItem(
"Distribution",
tabName = "Distribution",
icon = icon("bar-chart-o")
),
menuItem(
"SignatureGene",
tabName = "SignatureGene",
icon = icon("align-left")
),
menuItem("Heatmap", tabName = "Heatmap", icon = icon("delicious")),
menuItem("DotPlot", tabName = "DotPlot", icon = icon("braille")),
# menuItem(
# "In-silico FACS",
# tabName = "FACS",
# icon = icon("fas fa-fingerprint")
# ),
# menuItem(
# "Metadata",
# tabName = "Metadata",
# icon = icon("stats", lib = "glyphicon")
# ),
#menuItem("DataTable", tabName = "DataTable", icon = icon("table")),
menuItem("Instructions", tabName = "Instructions", icon = icon("file-alt")),
menuItem("About", tabName = "About", icon = icon("envelope"))
)
)
# Shiny body----
body <- dashboardBody(
useShinyjs(),
# *Login page----
shinyauthr::loginUI("login"),
# *Working page----
conditionalPanel(condition = "output.Login_logged",
fluidRow(
column(
width = 9,
# **Head panel----
box(
title = "Gene input",
width = 12,
status = "warning",
collapsible = T,
collapsed = F,
tabBox(
id = "GeneInput_panel",
side = "left",
selected = "Genes",
width = 12,
tabPanel(
"Genes",
# textAreaInput(
# inputId = "GeneInput_text",
# label = "Type a gene or geneset:",
# value = "CXCL13"
# )
selectInput("GeneInput_text",label = NULL,choices = NULL,multiple = T)
),
tabPanel(
"Saved",
textAreaInput(
inputId = "GeneInput_saved_text",
label = NULL,
value = NULL
),
selectizeInput(
inputId = "GeneInput_saved",
label = "Select from the saved geneset:",
multiple = TRUE,
choice = NULL,
selected = NULL
)
),
tabPanel(
"Upload",
textAreaInput(
inputId = "GeneInput_file_text",
label = NULL,
value = NULL
),
fileInput(
inputId = "GeneInput_file",
label = "Choose a csv file:",
multiple = FALSE
) %>%
shinyInput_label_embed(
shiny_iconlink() %>%
bs_embed_popover(
title = "Note:",
placement = "left",
content = "There should be a column named as 'Symbol'."
)
)
)
),
shiny::actionButton(
inputId = "GeneInput_submit",
label = "Submit",
width = "120px",
icon = icon("paper-plane"),
style = "color: #fff; background-color: #337ab7; border-color: #2e6da4"
)
),
# **Plot region----
box(
status = "warning",
width = 12,
tabItems(
# ****Embedding Plot----
tabItem(
tabName = "Embedding",
box(
status = NULL,
width = 12,
dropdownButton(
selectInput(
inputId = "Embedding_gene_splitBy",
label = "Split by",
choices = c("None"),
selected = "None"
),
selectInput(
inputId = "Embedding_used1",
label = "Embedding used",
choices = NULL,
selected = NULL
),
selectInput(
inputId = "Embedding_GenePar",
label = "Multi gene",
##choices = c("Seperate" = TRUE, "Mean" = FALSE),
choices = c("Seperate", "Mean"),
selected = "Seperate"
),
numericInput(
inputId = "PlotSize_width",
label = "Plot width (px)",
value = 600,
step = 10
),
numericInput(
inputId = "PlotSize_height",
label = "Plot height (px)",
value = 360,
step = 10
),
numericInput(
inputId = "PlotPar_ncol",
label = "Col number",
value = 1
),
selectInput(
inputId = "Embedding_do_scale",
label = "Scale the data?",
choices = c("Yes","No"),
selected = "No"
),
selectInput(
inputId = "Embedding_free_scale",
label = "Free the scale?",
choices = c("Yes","No"),
selected = "No"
),
##
sliderInput(
inputId = "Embedding_exp_bLo",
label = "Exp low boundary",
value = -0.5,
min = -4,
max = 0,
step = 0.5),
sliderInput(
inputId = "Embedding_exp_bHi",
label = "Exp high boundary",
value = 1.5,
min = 0,
max = 12,
step = 0.5),
sliderInput(
inputId = "Embedding_exp_bStep",
label = "Exp boundary step",
value = 0.5,
min = 0.1,
max = 2,
step = 0.1),
##
sliderInput(
inputId = "Embedding_dotsize1",
label = "Dot size",
value = 2,
min = 0,
max = 3,
step = 0.1
),
sliderInput(
inputId = "Embedding_gene_raster_scale",
label = "Raster scale",
value = 1,
min = 0,
max = 1,
step = 0.05
),
selectInput(
inputId = "Embedding_gene_download_type",
label = "Figure Type",
choices = c("pdf","png"),
selected = "pdf"
),
selectInput(
inputId = "Embedding_gene_scatter_function",
label = "scatter function",
choices = c("geom_point","geom_point_rast","geom_scattermore"),
selected = "geom_point"
),
####h5("Vector friendly?",style="font-weight: bold"),
#checkboxInput(inputId="Embedding_gene_download_vf",
# label="Vector friendly",
# value = F, width = NULL),
selectInput(
inputId = "Embedding_colorpanel",
label = "Color profile",
choices = choice.palette,
selected = "YlOrRd"
),
circle = TRUE,
status = "danger",
icon = icon("spinner"),
width = "250px",
tooltip = tooltipOptions(title = "Click to see inputs!")
),
uiOutput("Embedding_geneplot.ui"),
downloadButton(
outputId = 'Embedding_gene_download',
label = 'Download',
width = "120px",
style = "color: #fff; background-color: #337ab7; border-color: #2e6da4"
)
),
box(
status = NULL,
width = 12,
dropdownButton(
selectInput(
inputId = "Embedding_colorby",
label = "Color by",
choices = NULL,
selected = NULL,
multiple = T
),
selectInput(
inputId = "Embedding_metaInfo_splitBy",
label = "Split by",
choices = c("None"),
selected = "None"
),
numericInput(
inputId = "PlotSize_width2",
label = "Plot width (px)",
value = 650,
step = 10
),
numericInput(
inputId = "PlotSize_height2",
label = "Plot height (px)",
value = 360,
step = 10
),
numericInput(
inputId = "PlotPar_ncol2",
label = "Col number",
value = 1
),
sliderInput(
inputId = "Embedding_metaInfo_labelSize",
label = "Label size",
value = 3.5,
min = 0,
max = 10,
step = 0.5
),
sliderInput(
inputId = "Embedding_dotsize2",
label = "Dot size",
value = 1.4,
min = 0,
max = 3,
step = 0.1
),
sliderInput(
inputId = "Embedding_metaInfo_raster_scale",
label = "Raster scale",
value = 1,
min = 0,
max = 1,
step = 0.05
),
selectInput(
inputId = "Embedding_metaInfo_download_type",
label = "Figure Type",
choices = c("pdf","png"),
selected = "pdf"
),
selectInput(
inputId = "Embedding_metaInfo_scatter_function",
label = "scatter function",
choices = c("geom_point","geom_point_rast","geom_scattermore"),
selected = "geom_point"
),
#checkboxInput(inputId="Embedding_metaInfo_download_vf",
# label="Vector friendly",
# value = F, width = NULL),
circle = TRUE,
status = "danger",
icon = icon("spinner"),
width = "250px",
tooltip = tooltipOptions(title = "Click to see inputs!")
),
uiOutput("Embedding_metaplot.ui"),
downloadButton(
outputId = 'Embedding_metaInfo_download',
label = 'Download',
width = "120px",
style = "color: #fff; background-color: #337ab7; border-color: #2e6da4"
)
)
#verbatimTextOutput("EnvirementAA"),
#verbatimTextOutput("EnvirementBB"),
#verbatimTextOutput("EnvirementCC")
),
# ****Distribution Plot----
tabItem(
tabName = "Distribution",
dropdownButton(
selectInput(
inputId = "Distribution_groupby",
label = "Group by",
choices = NULL,
selected = NULL
),
selectInput(
inputId = "Distribution_splitBy",
label = "Split by",
choices = c("None"),
selected = "None"
),
selectInput(
inputId = "Distribution_GenePar",
label = "Multi gene",
##choices = c("Seperate" = TRUE, "Mean" = FALSE),
choices = c("Seperate", "Mean"),
selected = "Seperate"
),
# pickerInput(
# inputId = "Distribution_groupIn",
# label = "Only show groups in",
# choices = NULL,
# multiple = TRUE,
# options = list(
# `actions-box` = TRUE,
# `live-search` = TRUE
# )
# ),
numericInput(
inputId = "Distribution_PlotWidth",
label = "Plot width (px)",
value = 650,
step = 10
),
numericInput(
inputId = "Distribution_PlotHeight",
label = "Plot height (px)",
value = 300,
step = 10
),
numericInput(
inputId = "Distribution_PlotNCol",
label = "Col number",
value = 1
),
selectInput(
inputId = "Distribution_do_scale",
label = "Scale the data?",
choices = c("Yes","No"),
selected = "No"
),
##
sliderInput(
inputId = "Distribution_exp_bLo",
label = "Exp low boundary",
value = -1.5,
min = -4,
max = 0,
step = 0.5
),
sliderInput(
inputId = "Distribution_exp_bHi",
label = "Exp high boundary",
value = 3,
min = 0,
max = 12,
step = 0.5
),
sliderInput(
inputId = "Distribution_exp_bStep",
label = "Exp boundary step",
value = 0.5,
min = 0.1,
max = 2,
step = 0.1
),
##
selectInput(
inputId = "Distribution_colorpanel",
label = "Color profile",
choices = choice.palette,
selected = "YlOrRd"
),
# sliderInput(
# inputId = "Distribution_dotsize",
# label = "Dot size",
# value = 0.6,
# min = 0,
# max = 1,
# step = 0.1
# ),
circle = TRUE,
status = "danger",
icon = icon("bar-chart-o"),
width = "250px",
tooltip = tooltipOptions(title = "Click to see inputs!")
),
uiOutput("Distribution_plot.ui"),
downloadButton(
outputId = 'Distribution_download',
label = 'Download',
width = "120px",
style = "color: #fff; background-color: #337ab7; border-color: #2e6da4"
)
),
# ****Significance Plot----
tabItem(
tabName = "SignatureGene",
h3("Full talbe of the signature gene detection"),
DT::dataTableOutput("Significance_group"),
tags$br(),
# h4("Significance"),
# verbatimTextOutput("Significance_statistic"),
h3("Selected genes and meta.cluster visulized here:"),
tags$br(),
dropdownButton(
selectInput(
inputId = "SignatureGene_meta.cluster",
label = "Meta-Cluster",
choices = NULL,
multiple = F,
selected = NULL
),
selectInput(
inputId = "SignatureGene_groupBy",
label = "Group by",
#choices = c("cancerType","study"),
choices = c("cancerType"),
multiple = F,
selected = "cancerType"
),
numericInput(
inputId = "SignatureGene_PlotWidth",
label = "Plot width (px)",
value = 350,
step = 10
),
numericInput(
inputId = "SignatureGene_PlotHeight",
label = "Plot height (px)",
value = 500,
step = 10
),
numericInput(
inputId = "SignatureGene_PlotNCol",
label = "Col number",
value = 1
),
# selectInput(
# inputId = "Significance_groupby",
# label = "Group by",
# choices = c(
# "Global_Cluster",
# "Sub_Cluster",
# "Tissue",
# "Treatment",
# "Day",
# "Sample"
# ),
# selected = "Sub_Cluster"
# ),
# numericInput(
# inputId = "Significance_percutoff",
# label = "Expression cutoff",
# value = 0
# ),
# numericInput(
# inputId = "Significance_siglevel",
# label = "Significant level",
# value = 0.05
# ),
circle = TRUE,
status = "danger",
icon = icon("chart-bar"),
width = "250px",
tooltip = tooltipOptions(title = "Click to see inputs!")
),
uiOutput("Significance_plot.ui"),
downloadButton(
outputId = 'Significance_download',
label = 'Download',
width = "120px",
style = "color: #fff; background-color: #337ab7; border-color: #2e6da4"
)
),
# ****Heatmap Plot----
tabItem(
tabName = "Heatmap",
dropdownButton(
selectInput(
inputId = "Heatmap_aveBy",
label = "Average by",
#choices = c("meta.cluster","cellType","cellSubType","cancerType","dataset"),
choices = c("meta.cluster","cancerType","dataset"),
selected = "meta.cluster"
),
# checkboxGroupInput(inputId = "Heatmap_colorBy",
# label = "Color by",
# choices=NULL,
# selected = NULL,
# inline = FALSE,
# width = NULL),
# h5("Average the genes"),
# checkboxInput(inputId="Heatmap_aveby",
# label="by study",
# value = T, width = NULL),
# selectInput(
# inputId = "Heatmap_splitBy",
# label = "Split by",
# choices = c("None"),
# selected = "None"
# ),
selectInput(
inputId = "Heatmap_do_scale",
label = "Scale the data?",
choices = c("Yes","No"),
selected = "No"
),
h5("Clustering",style="font-weight: bold"),
checkboxInput(inputId="Heatmap_clustering_row",
label="by row",
value = T, width = NULL),
checkboxInput(inputId="Heatmap_clustering_col",
label="by column",
value = T, width = NULL),
# checkboxInput(inputId="Heatmap_dendro_row",
# label="Dendrogram rows",
# value = T, width = NULL),
# checkboxInput(inputId="Heatmap_dendro_col",
# label="Dendrogram columns",
# value = T, width = NULL),
numericInput(
inputId = "Heatmap_PlotWidth",
label = "Plot width (px)",
value = 1000,
step = 10
),
numericInput(
inputId = "Heatmap_PlotHeight",
label = "Plot height (px)",
value = 300,
step = 10
),
# numericInput(
# inputId = "Heatmap_PlotNCol",
# label = "Col number",
# value = 1
# ),
###sliderInput(
### inputId = "Heatmap_zMax",
### label = "Exp limits",
### value = 1.5,
### min = 0.5,
### max = 2,
### step = 0.1
###),
##
sliderInput(
inputId = "Heatmap_exp_bLo",
label = "Exp low boundary",
value = -1.5,
min = -4,
max = 0,
step = 0.5),
sliderInput(
inputId = "Heatmap_exp_bHi",
label = "Exp high boundary",
value = 1.5,
min = 0,
max = 12,
step = 0.5),
sliderInput(
inputId = "Heatmap_exp_bStep",
label = "Exp boundary step",
value = 0.5,
min = 0.1,
max = 2,
step = 0.1),
##
selectInput(
inputId = "Heatmap_colorpanel",
label = "Color profile",
choices = choice.palette,
selected = "RdBu"
),
circle = TRUE,
status = "danger",
icon = icon("delicious"),
width = "250px",
tooltip = tooltipOptions(title = "Click to see inputs!")
),
uiOutput("Heatmap_plot.ui"),
downloadButton(
outputId = 'Heatmap_download',
label = 'Download',
width = "120px",
style = "color: #fff; background-color: #337ab7; border-color: #2e6da4"
)
),
# **** DotPlot showing effect size of genes----
tabItem(
tabName = "DotPlot",
dropdownButton(
numericInput(
inputId = "DotPlot_Width",
label = "Plot width (px)",
value = 1000,
step = 10
),
numericInput(
inputId = "DotPlot_Height",
label = "Plot height (px)",
value = 300,
step = 10
),
sliderInput(
inputId = "DotPlot_esMin",
label = "Min of Effect Size",
value = -0.25,
min = -0.5,
max = 0,
step = 0.05
),
sliderInput(
inputId = "DotPlot_esMax",
label = "Max of Effet Size",
value = 0.5,
min = 0,
max = 1.5,
step = 0.1
),
selectInput(
inputId = "DotPlot_colorpanel",
label = "Color profile",
choices = choice.palette,
selected = "RdYlBu"
),
circle = TRUE,
status = "danger",
icon = icon("braille"),
width = "250px",
tooltip = tooltipOptions(title = "Click to see inputs!")
),
uiOutput("DotPlot.ui"),
downloadButton(
outputId = 'DotPlot_download',
label = 'Download',
width = "120px",
style = "color: #fff; background-color: #337ab7; border-color: #2e6da4"
)
),
# ****In-silico FACS Plot----
tabItem(
tabName = "FACS",
tabBox(
id = "FACS",
side = "left",
selected = "FACS",
width = 12,
tabPanel("FACS",
dropdownButton(
numericInput(
inputId = "FACS_xcutoff",
label = "x cutoff",
value = 1
),
numericInput(
inputId = "FACS_ycutoff",
label = "y cutoff",
value = 1
),
selectInput(
inputId = "FACS_colorpanel",
label = "Color profile",
choices = c(
"YlOrRd",
"BrBG",
"RdYlBu",
"RdYlGn",
"Spectral",
"YlOrBr",
"YlGnBu",
"Reds",
"Blues",
"OrRd",
"RdBu"
),
selected = "RdBu"
),
selectInput(
inputId = "FACS_colorby",
label = "Color by",
choices = c(
"None",
"Global_Cluster",
"Sub_Cluster",
"Tissue",
"Treatment",
"Day",
"Sample"
),
selected = "None"
),
sliderTextInput(
inputId = "FACS_dotsize",
label = "Dot size",
choices = c(-1, seq(0, 3, 0.5)),
grid = TRUE,
selected = -1
),
circle = TRUE,
status = "danger",
icon = icon("fas fa-fingerprint"),
width = "250px",
tooltip = tooltipOptions(title = "Click to see inputs!")
),
uiOutput("FACS_plot.ui"),
downloadButton(
outputId = 'FACS_download',
label = 'Download',
width = "120px",
style = "color: #fff; background-color: #337ab7; border-color: #2e6da4")
),
tabPanel("DEG",
box(width = 12,
column(width = 4,
selectInput(
inputId = "FACS_DEG_group1",
label = "The 1st group",
choices = c("Group1", "Group2", "Group3", "Group4"),
selected = "Group1"
),
selectInput(
inputId = "FACS_DEG_group2",
label = "The 2nd group",
choices = c("Group1", "Group2", "Group3", "Group4"),
selected = "Group2"
),
p(
class = "text-muted",
paste(
"Note: The number of cells in each group will be downsampled to 1000 randomly."
)
)
),
column(width = 4,
numericInput(
inputId = "FACS_Volcano_Pvalue_cutoff",
label = "adj.P.Val cutoff",
value = 0.05
),
numericInput(
inputId = "FACS_Volcano_logFC_cutoff",
label = "logFC cutoff",
value = 0.5
),
numericInput(
inputId = "FACS_Volcano_ngenes_labeled",
label = "Labeled genes",
value = 25
)
),
column(width = 4,
numericInput(
inputId = "FACS_Volcano_fontsize",
label = "Font size",
value = 15
),
sliderTextInput(
inputId = "FACS_Volcano_dotsize",
label = "Dot size",
choices = seq(0, 10, 0.5),
grid = TRUE,
selected = 2
),
shiny::actionButton(
inputId = "FACS_DEG_submit",
label = "Calculate",
width = "120px",
icon = icon("calculator"),
style = "color: #fff; background-color: #337ab7; border-color: #2e6da4"
)
)
),
box(width = 12,
uiOutput("FACS_volcano_plot.ui"),
downloadButton(
outputId = 'FACS_volcano_download',
label = 'Download',
width = "120px",
style = "color: #fff; background-color: #337ab7; border-color: #2e6da4"
)
),
box(width = 12,
h3("Differentially expressed genes"),
p(
class = "text-muted",
paste(
"Note: Here only shows 2000 genes with the smallest adj.P.Val. If you want the full gene list, you can download it."
)
),
DT::dataTableOutput("FACS_DEGDataTable_output"),
downloadButton(
'FACS_DEGDataTable_download',
label = 'Download',
width = "120px",
style = "color: #fff; background-color: #337ab7; border-color: #2e6da4"
)
)
)
)
),
# ****Metadata Plot----
tabItem(
tabName = "Metadata",
dropdownButton(
selectInput(
inputId = "Metadata_plottype",
label = "Plot type",
choices = c("barplot","boxplot","boxplot2"),
selected = "barplot"
),
selectInput(
inputId = "Metadata_groupby1",
label = "Group by",
choices = c(
"meta.cluster",
"cancerType",
"dataset",
"loc",
"treatment",
"tech"
),
selected = "meta.cluster"
),
selectInput(
inputId = "Metadata_cmp",
label = "Comparison",
choices = c(
"meta.cluster",
"cancerType",
"dataset",
"loc",
"treatment",
"tech"
),
selected = "cancerType"
),
numericInput(
inputId = "Metadata_PlotWidth",
label = "Plot height (px)",
value = 600,
step = 10
),
numericInput(
inputId = "Metadata_PlotHeight",
label = "Plot height (px)",
value = 300,
step = 10
),
numericInput(
inputId = "Metadata_PlotNCol",
label = "Col number",
value = 1
),
# selectInput(
# inputId = "Metadata_quantify",
# label = "Quantified by",
# choices = c("Proportion", "Count"),
# selected = "Proportion"
# ),
# materialSwitch(
# inputId = "Metadata_flip",
# label = "Coordinates flipped",
# value = TRUE,
# status = "primary",
# right = TRUE
# ),
# numericInput(
# inputId = "Metadata_cutoff",
# label = "Proportion shown in pie plot >",
# value = 10
# ),
circle = TRUE,
status = "danger",
icon = icon("stats", lib = "glyphicon"),
width = "250px",
tooltip = tooltipOptions(title = "Click to see inputs!")
),
uiOutput("Metadata_plot.ui"),
downloadButton(
outputId = 'Metadata_download',
label = 'Download',
width = "120px",
style = "color: #fff; background-color: #337ab7; border-color: #2e6da4"
)
),
# ****DataTable Output----
# tabItem(
# tabName = "DataTable",
# DT::dataTableOutput("DataTable_output"),
# downloadButton(
# 'DataTable_download',
# label = 'Download',
# width = "120px",
# style = "color: #fff; background-color: #337ab7; border-color: #2e6da4"
# )
# ),