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Feature set table

Source: R/FeatureSetTable.R
FeatureSetTable-class.Rd

A table where each row is itself a feature set and can be clicked to transmit a multiple feature selection to another panel. This relies on feature set collections that have been registered in the input SummarizedExperiment, see registerFeatureSetCollections for more details. If no collections have been registered, we default to the GO and KEGG collections from createGeneSetCommands.

Slot overview

The following slots control the feature sets in use:

  • Collection, string specifying the type of feature set collection to show. Defaults to the first registered collection in the SummarizedExperiment.

The following slots control the table selections:

  • Selected, a string containing the name of the currently selected gene set. Defaults to "", i.e., no selection.

  • Search, a string containing the regular expression for the global search. Defaults to "", i.e., no search.

  • SearchColumns, a character vector where each entry contains the search string for each column. Defaults to an empty character vector, i.e., no search.

In addition, this class inherits all slots from its parent Panel class.

Constructor

FeatureSetTable(...) creates an instance of a FeatureSetTable class, where any slot and its value can be passed to ... as a named argument.

Supported methods

In the following code snippets, x is an instance of a FeatureSetTable class. Refer to the documentation for each method for more details on the remaining arguments.

For setting up data values:

  • .cacheCommonInfo(x) adds a "FeatureSetTable" entry containing available.sets, a named list of DataFrames containing information about the individual gene sets for each collection. This will also call the equivalent Panel method.

  • .refineParameters(x, se) replaces NA values in Collection with the first valid collection. It also replaces NA values for Selected with the first valid set in the chosen collection. This will also call the equivalent Panel method.

For defining the interface:

  • .defineDataInterface(x, se, select_info) returns a list of interface elements for manipulating all slots described above.

  • .panelColor(x) will return the specified default color for this panel class.

  • .fullName(x) will return "Gene set table".

  • .hideInterface(x) will return TRUE for UI elements related to multiple selections, otherwise calling the method for Panel.

  • .defineOutput(x) will return a HTML element containing a datatable widget.

For monitoring reactive expressions:

  • .createObservers(x, se, input, session, pObjects, rObjects) sets up observers for all new slots described above, as well as in the parent classes via the Panel method.

For creating the table:

  • .generateOutput(x, envir) will create a data.frame of gene set descriptions in envir. It will also return the commands required to do so and the name of the variable corresponding to said data.frame.

  • .renderOutput(x, se, ..., output, pObjects, rObjects) will add a datatable widget to the output, which is used to render the aforementioned data.frame.

For controlling the multiple selections:

  • .multiSelectionDimension(x) returns "row".

  • .multiSelectionCommands(x, index) returns a string specifying the commands to be used to extract the identities of the genes in the currently selected set. index is ignored.

  • .multiSelectionActive(x) returns the name of the currently selected gene set, unless no selection is made, in which case NULL is returned.

  • .multiSelectionClear(x) returns x but with the Selected slot replaced by an empty string.

  • .multiSelectionAvailable(x, contents) returns contents$available, which is set to the number of features in se.

For documentation:

  • .definePanelTour(x) returns an data.frame containing the steps of a panel-specific tour.

Author

Aaron Lun

Examples

library(scRNAseq)
sce <- LunSpikeInData(location=FALSE)

library(scater)
sce <- logNormCounts(sce)

library(scran)
rowData(sce) <- cbind(rowData(sce), modelGeneVarWithSpikes(sce, "ERCC"))

cmds <- createGeneSetCommands(collections="GO",
    organism="org.Mm.eg.db", identifier="ENSEMBL")
sce <- registerFeatureSetCommands(sce, cmds)

# Setting up the application.
gst <- FeatureSetTable(PanelId=1L)

rdp <- RowDataPlot(RowSelectionSource="FeatureSetTable1",
    ColorBy="Row selection",
    XAxis="Row data", XAxisRowData="mean", YAxis="total")

rdt <- RowDataTable(RowSelectionSource="FeatureSetTable1")

if (interactive()) {
    iSEE(sce, initial=list(gst, rdp, rdt))
}