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The server function of the selectmatrix module

Source: R/selectmatrix.R
selectmatrix.Rd

This module forms the core of many operations in shinyngs. To use the matrix data stored in an ExploratorySummarizedExperimentList object, selection must be made on the basis of experiment (which ExploratorySummarizedExperiment) to use), the specific assay of the experiment, and the rows and columns of the selected assay matrix. This module provides customisable controls for selection at each of these levels, and parses those inputs to produce matrices used in the various plots.

Usage

selectmatrix(
  id,
  eselist,
  var_n = 50,
  var_max = NULL,
  select_assays = TRUE,
  select_samples = TRUE,
  select_genes = TRUE,
  provide_all_genes = FALSE,
  default_gene_select = NULL,
  require_contrast_stats = FALSE,
  rounding = 2,
  select_meta = TRUE,
  allow_summarise = TRUE
)

Arguments

id

Module namespace

eselist

ExploratorySummarizedExperimentList object containing ExploratorySummarizedExperiment objects

var_n

The number of rows to select when doing so by variance. Default = 50

var_max

The maximum umber of rows to select when doing so by variance. Default = 500

select_assays

Provide UI and functions for assay selection?

select_samples

Provide UI and functions for sample selection? (Default: TRUE)

select_genes

Provide UI and functions for gene (row) selection? (Default: TRUE)

provide_all_genes

Allow the 'all rows' selection in the UI? Means we don't have to calculate variance so the display is quicker, but it's a bad idea for e.g. heatmaps where the visual scales by the numbre of rows.

default_gene_select

The default method to use for selecting genes

require_contrast_stats

Only use elements of eselist that have a populated contrast_stats slot. For plots using p value data etc, this is used to hide experiments that don't have the necessary data.

rounding

Number of decimal places to show in results (Default 2)

select_meta

Boolean- add metadata controls?

allow_summarise

Boolean, show controls for matrix summarisation?

Value

output A list of reactive functions for fetching the derived matrix and making a title based on its properties.

Details

The geneselect and sampleselect modules provide row- and column- selection, respectively. This will generally not be called directly, but by other modules such as the heatmap module.

This function is called directly, using the same id as its UI counterpart, and wraps its logic in moduleServer() (see example).

Examples

selectSamples <- sampleselect("selectmatrix", eselist)
#> Error in sampleselect("selectmatrix", eselist): could not find function "sampleselect"