tabItem(tabName = "umapTab",
fluidRow(
column(12,
h3(strong("Non-linear dimensional reduction (UMAP)")),
hr(),
tags$div(class = "BoxArea2",
column(12,
tags$div(class = "",
h4(strong("Parameters")),
p("This uses SCTransform, an R package for normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression"),
p("Uniform Manifold Approximation and Projection (UMAP) is a dimension reduction technique that can be used for visualisation similarly to t-SNE, but also for general non-linear dimension reduction. "),
# column(6,numericInput("umapPCDim1", "Dimensions(PC) To Use (1):", value = 1)),
# column(6,numericInput("umapPCDim2", "Dimensions(PC) To Use (2):", value = 10)),
p("Once running the reduction is complete, you can also view/download cells in each cluster"),
tags$div(class = "clearBoth")
)
),
hr(),
column(12,
conditionalPanel("output.umapPlotAvailable",
tabsetPanel(type = "tabs",
tabPanel("UMAP Plot",
column(8,
h4(strong("UMAP Plot")),
column(12,
withSpinner(plotOutput(outputId = "umapPlot"))
)
),
column(4,
radioButtons("umapGroupBy", label = "Color by:",
choices = list("Clusters" = "ident", "Samples" = "orig.ident"),
selected = "ident"),
hr(),
h4(strong("Plot Download Options")),
numericInput("UmapDownloadHeight", "Plot height (in cm):", value = 30),
numericInput("UmapDownloadWidth", "Plot width (in cm):", value = 30),
radioButtons("UmapDownloadAs", "Download File Type:", choices = list("PDF" = ".pdf", "SVG" = ".svg", "PNG" = ".png", "JPEG" = ".jpeg"), selected = ".pdf"),
downloadButton("downloadUmap", "Download Plot"),
br(),br(),
p(
actionButton(
"nextClusterMarkersUmap",
"Next Step: Find Cluster Markers",
class = "button button-3d button-pill button-caution"
),
hr(),
actionButton(
"nextDownloadUmap",
"Download Seurat Object",
class = "button button-3d button-pill",
icon = icon("download")
)
)
),
tags$div(class = "clearBoth")
)
# ,
# tabPanel("Find Cells in Clusters",
# column(12,
# wellPanel(
# h4("Find Cells in Clusters:"),
# column(6,selectInput("clusterNumCells", "Cluster Num",
# choices = NULL, selected = 1)),
# div(style = "clear:both;"),
# actionButton("findCellsInCluster","Find Cells in Clusters",class = "button button-3d button-block button-primary")
# )
# ,
# conditionalPanel("output.clustercellsavailable",
# downloadButton('downloadClusterCells','Save Results as CSV File', class = "btn btn-primary"),
# withSpinner(dataTableOutput('cellsInClusters'))
# )
#
# ),
# tags$div(class = "clearBoth")
# )
),
hr()
)
)
,
tags$div(class = "clearBoth")
),
column(12,
actionButton("runUmap","Run UMAP Reduction",class = "button button-3d button-block button-pill button-primary button-large", style = "width: 100%")
)
,
tags$div(class = "clearBoth")
)
)
)
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