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Create custom panels

Source: R/createCustomPanels.R
createCustomPanels.Rd

Helper functions for quick-and-dirty creation of custom panels, usually in the context of a one-off application. This creates a new class with specialized methods for showing content based on a user-specified function.

Usage

createCustomTable(
  FUN,
  restrict = NULL,
  className = "CustomTable",
  fullName = "Custom table",
  FUN.selection.details = NULL,
  where = topenv(parent.frame())
)

createCustomPlot(
  FUN,
  restrict = NULL,
  className = "CustomPlot",
  fullName = "Custom plot",
  where = topenv(parent.frame())
)

Arguments

FUN

A function that generates a data.frame or a ggplot, for createCustomTable and createCustomPlot respectively. See Details for the expected arguments.

restrict

Character vector of names of optional arguments in FUN to which the UI is restricted. If specified, only the listed arguments receive UI elements in the interface.

className

String containing the name of the new Panel class.

fullName

String containing the full name of the new class.

FUN.selection.details

Function generating a UI element that displays details about the current selection, if any.

where

An environment indicating where the class and method definitions should be stored.

Value

A new class and its methods are defined in the global environment. A generator function for creating new instances of the class is returned.

Details

FUN is expected to have the following first 3 arguments:

  • se, a SummarizedExperiment object for the current dataset of interest.

  • rows, a list of row selections received from the transmitting panel. This contains one or more character vectors of row names in active and saved selections. Alternatively, this may be NULL if no selection has been made in the transmitter.

  • columns, a list of column selections received from the transmitting panel. This contains one or more character vectors of column names in active and saved selections. Alternatively, this may be NULL if no selection has been made in the transmitter.

Any number of additional named arguments may also be present in FUN. All such arguments should have default values, as these are used to automatically generate UI elements in the panel:

Arguments with other types of default values are ignored. If restrict is specified, arguments will only have corresponding UI elements if they are listed in restrict. All user interactions with these elements will automatically trigger regeneration of the panel contents.

Classes created via these functions are extremely limited. Only scalar inputs are supported via the UI and all panels cannot transmit to the rest of the app. We recommend only using these functions for one-off applications to quickly prototype concepts; serious Panel extensions should be done explicitly.

Author

Aaron Lun

Examples

library(scater)
CUSTOM_DIMRED <- function(se, rows, columns, ntop=500, scale=TRUE,
    mode=c("PCA", "TSNE", "UMAP"))
{
    if (is.null(columns)) {
        return(
            ggplot() + theme_void() + geom_text(
                aes(x, y, label=label),
                data.frame(x=0, y=0, label="No column data selected."),
                size=5)
            )
    }

    mode <- match.arg(mode)
    if (mode=="PCA") {
        calcFUN <- runPCA
    } else if (mode=="TSNE") {
        calcFUN <- runTSNE
    } else if (mode=="UMAP") {
        calcFUN <- runUMAP
    }

    kept <- se[, unique(unlist(columns))]
    kept <- calcFUN(kept, ncomponents=2, ntop=ntop,
        scale=scale, subset_row=unique(unlist(rows)))
    plotReducedDim(kept, mode)
}

GEN <- createCustomPlot(CUSTOM_DIMRED)
GEN()
#> Panel object of class CustomPlot
#>   Get or set individual parameters with '[[' 
#>   Available parameters:
#>     ColumnSelectionDynamicSource: FALSE
#>     ColumnSelectionRestrict: FALSE
#>     ColumnSelectionSource: ---
#>     DataBoxOpen: FALSE
#>     PanelHeight: 500
#>     PanelId: NA
#>     PanelWidth: 4
#>     RowSelectionDynamicSource: FALSE
#>     RowSelectionRestrict: FALSE
#>     RowSelectionSource: ---
#>     SelectionBoxOpen: FALSE
#>     SelectionHistory: 
#>     VersionInfo: list of length 1
#>     mode: PCA
#>     ntop: 500
#>     scale: TRUE

if (interactive()) {
    library(scRNAseq)
    sce <- ReprocessedAllenData("tophat_counts")
    library(scater)
    sce <- logNormCounts(sce, exprs_values="tophat_counts")

    iSEE(sce, initial=list(
        ColumnDataPlot(PanelId=1L),
        GEN(ColumnSelectionSource="ColumnDataPlot1")
    ))
}