Teal Module for PCA Analysis

This module provides an interactive principal components plot and an interactive heatmap with correlation of principal components with sample variables.

Usage

tm_g_pca(
  label,
  mae_name,
  exclude_assays = character(),
  pre_output = NULL,
  post_output = NULL
)

ui_g_pca(id, data, mae_name, pre_output, post_output)

srv_g_pca(id, data, filter_panel_api, reporter, mae_name, exclude_assays)

sample_tm_g_pca()

Arguments

label

(string)
menu item label of the module in the teal app.

mae_name

(string)
name of the MAE data used in the teal module.

exclude_assays

(character)
names of the assays which should not be included in choices in the teal module.

pre_output

(shiny.tag or NULL)
placed before the output to put the output into context (for example a title).

post_output

(shiny.tag or NULL)
placed after the output to put the output into context (for example the shiny::helpText() elements can be useful).

id

(string) the shiny module id.

data

(tdata)
tdata object which is automatically passed to the UI and server functions, holding all the data sets provided in the app initialization.

filter_panel_api

(FilterPanelAPI)
object describing the actual filter panel API.

reporter

(Reporter) object

Value

Shiny module to be used in the teal app.

Functions

• ui_g_pca(): sets up the user interface.

• srv_g_pca(): sets up the server with reactive graph.

• sample_tm_g_pca(): sample module function.

Examples

mae <- hermes::multi_assay_experiment
mae_data <- dataset("MAE", mae)
data <- teal_data(mae_data)
app <- init(
  data = data,
  modules = modules(
    tm_g_pca(
      label = "PCA plot",
      mae_name = "MAE"
    )
  )
)
#> [INFO] 2023-08-14 14:03:25.9636 pid:1125 token:[] teal.modules.hermes Initializing tm_g_pca
if (interactive()) {
  shinyApp(app$ui, app$server)
}

# Alternatively you can run the sample module with this function call:
if (interactive()) {
  sample_tm_g_pca()
}