Nothing
shinyPanelCelda2 <- fluidPage(
useShinyalert(),
tags$div(
class = "container",
h1("celda: CEllular Latent Dirichlet Allocation"),
h5(tags$a(href = "https://github.com/campbio/celda",
"(help)", target = "_blank")),
tabsetPanel(
tabPanel(
"Celda Clustering",
wellPanel(
br(),
fluidRow(
sidebarLayout(
sidebarPanel(
# SHINYJS ACCORDION --------------------------
# Section 1 - Basic Settings
actionButton("celdaBasicSet", "Basic Settings"),
# open by default
tags$div(id = "celdaCollapse1",
wellPanel(
selectInput("celdaAssay", "Select Assay:",
currassays),
selectInput("celdaModel",
"Select Celda Model:",
c("celda_C", "celda_G", "celda_CG"),
selected = "celda_CG"),
# c("celda_C"),
# selected = "celda_C"),
conditionalPanel(
condition = sprintf("input['%s'] == 'celda_C'",
"celdaModel"),
numericInput("cellClusterC",
label = "Number of Cell Clusters (K):",
value = 15,
min = 1,
max = 100,
step = 1)
),
conditionalPanel(
condition = sprintf("input['%s'] == 'celda_G'",
"celdaModel"),
numericInput("geneModuleG",
label = "Number of Gene Modules (L):",
value = 50,
min = 1,
max = 200,
step = 1)
),
conditionalPanel(
condition = sprintf("input['%s'] == 'celda_CG'",
"celdaModel"),
numericInput("cellClusterCG",
label = "Number of Cell Clusters (K):",
value = 15,
min = 1,
max = 100,
step = 1),
numericInput("geneModuleCG",
label = "Number of Gene Modules (L):",
value = 50,
min = 1,
max = 200,
step = 1))
)
),
# Section 2 - Advanced Settings
actionButton("celdaAdvSet", "Advanced Settings"),
shinyjs::hidden(
tags$div(id = "celdaCollapse2",
wellPanel(
conditionalPanel(
condition = sprintf("input['%s'] == 'celda_C' ||
input['%s'] == 'celda_CG'", "celdaModel", "celdaModel"),
selectInput("celdaAlgorithm",
"Select Algorithm:",
list("Expectation Maximization" = "EM",
"Gibbs Sampling" = "Gibbs"),
selected = "Expectation Maximization")
),
conditionalPanel(
condition = sprintf("input['%s'] == 'celda_C' ||
input['%s'] == 'celda_CG'", "celdaModel", "celdaModel"),
numericInput("celdaAlpha",
label = "Alpha",
value = 1,
min = 0.00000001,
max = 100000)
),
numericInput("celdaBeta",
label = "Beta",
value = 1,
min = 0.00000001,
max = 100000),
conditionalPanel(
condition = sprintf("input['%s'] == 'celda_G' ||
input['%s'] == 'celda_CG'", "celdaModel", "celdaModel"),
numericInput("celdaDelta",
label = "Delta:",
value = 1,
min = 0.00000001,
max = 100000),
numericInput("celdaGamma",
label = "Gamma:",
value = 1,
min = 0.00000001,
max = 100000)
),
numericInput("celdaMaxIter",
label = "Maximum Number of Iterations:",
value = 200,
min = 1,
max = 100000,
step = 1),
numericInput("celdaStopIter",
label = "Number of Converging Iterations for Gibbs
sampler to stop:",
value = 10,
min = 1,
max = 100000,
step = 1),
numericInput("celdaSplitIter",
label = "Split on Every This Number of Iteration:",
value = 10,
min = 1,
max = 100000,
step = 1),
numericInput("celdaNChains",
label = "Number of random cluster initializations
for every K/L combination:",
value = 3,
min = 1,
max = 100000,
step = 1),
# numericInput("celdaCores",
# label = "Number of Cores used for parallel computing:",
# value = 1,
# min = 1,
# max = 100000,
# step = 1),
numericInput("celdaSeed",
label = "Base Seed For Random Number Generation:",
value = 12345,
min = 1,
max = 100000,
step = 1)
)
)
),
tags$hr(),
withBusyIndicatorUI(actionButton(inputId = "runCelda",
label = "Run Celda")),
withBusyIndicatorUI(actionButton(inputId = "renderHeatmap",
label = "Render Heatmap")),
tags$hr(),
downloadButton("downloadSCECelda", "Download SingleCellExperiment object (.rds)")
),
mainPanel(
conditionalPanel(
condition = sprintf("input['%s'] ==
'celda_C' || input['%s'] ==
'celda_G' || input['%s'] == 'celda_CG'",
"celdaModel",
"celdaModel",
"celdaModel"),
plotOutput("celdaHeatmap", height = "600px")
)
)
)
)
)
),
tabPanel(
"Celda Grid Search",
wellPanel(
br(),
fluidRow(
sidebarLayout(
sidebarPanel(
# SHINYJS ACCORDION --------------------------
# Section 1 - Basic Settings
actionButton("celdaBasicSetGS", "Basic Settings"),
# open by default
tags$div(id = "celdaCollapseGS1",
wellPanel(
selectInput("celdaAssayGS", "Select Assay:",
currassays),
selectInput("celdaModelGS",
"Select Celda Model:",
c("celda_C", "celda_G", "celda_CG"),
selected = "celda_CG"),
conditionalPanel(
condition = sprintf("input['%s'] == 'celda_C'",
"celdaModelGS"),
h4("Range of Cell Clusters (K):"),
numericInput("GSRangeKlow",
"Lower bound:",
value = 2,
min = 2,
step = 1),
numericInput("GSRangeKup",
"Upper bound:",
value = 4,
min = 2,
step = 1),
numericInput("interK",
label = "Cell Cluster Increment Step Size:",
value = 1,
min = 1,
step = 1)
),
conditionalPanel(
condition = sprintf("input['%s'] == 'celda_G'",
"celdaModelGS"),
h4("Range of Gene Modules (L):"),
numericInput("GSRangeLlow",
"Lower bound:",
value = 2,
min = 2,
step = 1),
numericInput("GSRangeLup",
"Upper bound:",
value = 4,
min = 2,
step = 1),
numericInput("interL",
label = "Gene Module Search Increment Step Size:",
value = 1,
min = 1,
step = 1)
),
conditionalPanel(
condition = sprintf("input['%s'] == 'celda_CG'",
"celdaModelGS"),
h4("Range of Cell Clusters (K):"),
numericInput("GSRangeKCGlow",
"Lower bound:",
value = 2,
min = 2,
step = 1),
numericInput("GSRangeKCGup",
"Upper bound:",
value = 4,
min = 2,
step = 1),
numericInput("interKCG",
label = "Cell Cluster Search Increment Step Size:",
value = 1,
min = 1,
step = 1),
h4("Range of Gene Modules (L):"),
numericInput("GSRangeLCGlow",
"Lower bound:",
value = 2,
min = 2,
step = 1),
numericInput("GSRangeLCGup",
"Upper bound:",
value = 4,
min = 2,
step = 1),
numericInput("interLCG",
label = "Gene module Search Increment Step Size:",
value = 1,
min = 1,
step = 1)
)
# selectInput("celdaGSVerbose", "Verbose:",
# c(TRUE, FALSE),
# selected = FALSE
# )
)
),
# Section 2 - Advanced Settings
actionButton("celdaAdvSetGS", "Advanced Settings"),
shinyjs::hidden(
tags$div(id = "celdaCollapseGS2",
wellPanel(
numericInput("celdaMaxIterGS",
label = "Maximum Number of Iterations:",
value = 200,
min = 1,
max = 100000,
step = 1),
numericInput("celdaNChainsGS",
label = "Number of Random Cluster Initializations
For Every K/L Combination:",
value = 3,
min = 1,
max = 100000,
step = 1),
numericInput("celdaCoresGS",
label = "Number of Cores To Use For
Parallel Estimation of Chains:",
value = 1,
min = 1,
max = 100000,
step = 1),
numericInput("celdaSeedGS",
label = "Base Seed For Random Number Generation:",
value = 12345,
min = 1,
max = 100000,
step = 1)
)
)
),
tags$hr(),
withBusyIndicatorUI(actionButton(inputId = "runCeldaGS",
label = "Run Celda Grid Search")),
withBusyIndicatorUI(actionButton(
inputId = "renderPerplexityPlot",
label = "Render Perplexity Plot")),
tags$hr(),
selectInput("celdaSelectGSList",
"Select Celda Grid Search List:",
NULL),
selectInput("celdaSelectGSMod",
"Select Celda Model:",
NULL),
withBusyIndicatorUI(actionButton(
inputId = "confirmCeldaModel",
label = "Confirm Selection")),
tags$hr(),
downloadButton("downloadAllCeldaLists",
"Download All Celda Lists")
),
mainPanel(
conditionalPanel(
condition = sprintf("input['%s'] ==
'celda_C' || input['%s'] ==
'celda_G' || input['%s'] == 'celda_CG'",
"celdaModel",
"celdaModel",
"celdaModel"),
plotOutput("celdaPerplexityPlot", height = "600px")
)
)
)
)
)
),
tabPanel(
"Visualize",
wellPanel(style="background-color: white",
fluidRow(
tabsetPanel(
tabPanel("t-SNE",
wellPanel(
fluidRow(
sidebarLayout(
sidebarPanel(
# SHINYJS ACCORDION --------------------------
# Settings
#actionButton("celdatSNESet", "Settings"),
# closed by default
#shinyjs::hidden(
#tags$div(id = "celdaCollapsetSNE",
#wellPanel(
selectInput("celdaAssaytSNE", "Select Assay:",
currassays),
numericInput("celdatSNEmaxCells",
label =
"Max.cells: Maximum number of cells to
plot",
value = 25000,
min = 1,
step = 1),
numericInput("celdatSNEminClusterSize",
label =
"Min.cluster.size: Do not subsample cell
clusters below this threshold",
value = 100,
min = 1,
step = 1),
numericInput("celdatSNEPerplexity",
label =
"Perplexity: ",
value = 20),
numericInput("celdatSNEmaxIter",
label =
"Max.iter: Maximum number of iterations in
tSNE generation",
value = 2500),
numericInput("celdatSNESeed",
label =
"Seed: ",
value = 12345),
#)
#),
#)
tags$hr(),
withBusyIndicatorUI(actionButton(
inputId = "runCeldatSNE",
label = "Run Celda t-SNE")),
withBusyIndicatorUI(actionButton(
inputId = "renderCeldatSNEByCellCluster",
label = "Render cell cluster t-SNE plot")),
withBusyIndicatorUI(actionButton(
inputId = "renderCeldatSNEModule",
label = "Render module probability t-SNE plot")),
br(),
selectInput("celdatSNEFeature", "Select Feature:",
NULL, multiple = TRUE),
withBusyIndicatorUI(actionButton(
inputId = "renderCeldatSNEFeature",
label = "Render Gene expression t-SNE plot"))
), mainPanel(
plotOutput("celdatSNECellClusterPlot",
height = "600px"),
plotOutput("celdatSNEModulePlot",
height = "600px"),
plotOutput("celdatSNEFeaturePlot",
height = "600px")
)
)
)
)
), tabPanel("Probability Map",
wellPanel(
fluidRow(
sidebarLayout(
sidebarPanel(
selectInput("celdaAssayProbabilityMap",
"Select Assay:",
currassays),
tags$hr(),
withBusyIndicatorUI(actionButton(
inputId = "renderCeldaProbabilityMap",
label = "Render Celda Probability Map"))
), mainPanel(
plotOutput("celdaProbabilityMapPlot",
height = "600px")
)
)
)
)
),
tabPanel("Module Heatmap",
wellPanel(
fluidRow(
sidebarLayout(
sidebarPanel(
selectInput("celdaAssayModuleHeatmap",
"Select Assay:",
currassays),
selectInput("celdaFeatureModule",
"Select Feature Modules:",
NULL,
multiple = TRUE),
numericInput("celdaModuleTopCells",
"top.cells: Number of cells with the highest and
lowest probabilities for modules to include in
the heatmap",
value = 100,
min = 1,
step = 1),
# selectInput("celdaFeatureModuleNormalize",
# "Normalize: Whether to normalize the columns of
# 'counts'",
# choices = c(TRUE, FALSE),
# selected = TRUE),
selectInput("celdaModuleFeatureNames",
"Show Feature Names:",
choices = c(TRUE, FALSE),
selected = TRUE),
tags$hr(),
withBusyIndicatorUI(actionButton(
inputId = "renderCeldaModuleHeatmap",
label = "Render Celda Module Heatmap"))
), mainPanel(
plotOutput("celdaModuleHeatmapPlot",
height = "600px")
)
)
)
)
)
)
)
)
)
)
)
)
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.