teal module: Principal component analysis

Usage

tm_a_pca(
  label = "Principal Component Analysis",
  dat,
  plot_height = c(600, 200, 2000),
  plot_width = NULL,
  ggtheme = c("gray", "bw", "linedraw", "light", "dark", "minimal", "classic", "void"),
  ggplot2_args = teal.widgets::ggplot2_args(),
  rotate_xaxis_labels = FALSE,
  font_size = c(12, 8, 20),
  alpha = c(1, 0, 1),
  size = c(2, 1, 8),
  pre_output = NULL,
  post_output = NULL,
  decorators = NULL
)

Arguments

label

(character(1)) Label shown in the navigation item for the module or module group. For modules() defaults to "root". See Details.

dat

(data_extract_spec or list of multiple data_extract_spec) specifying columns used to compute PCA.

plot_height

(numeric) optional, specifies the plot height as a three-element vector of value, min, and max intended for use with a slider UI element.

plot_width

(numeric) optional, specifies the plot width as a three-element vector of value, min, and max for a slider encoding the plot width.

ggtheme

(character) optional, ggplot2 theme to be used by default. Defaults to "gray".

ggplot2_args

(ggplot2_args) optional, object created by teal.widgets::ggplot2_args() with settings for all the plots or named list of ggplot2_args objects for plot-specific settings. The argument is merged with options variable teal.ggplot2_args and default module setup.

List names should match the following: c("default", "Elbow plot", "Circle plot", "Biplot", "Eigenvector plot").

For more details see the vignette: vignette("custom-ggplot2-arguments", package = "teal.widgets").

rotate_xaxis_labels

(logical) optional, whether to rotate plot X axis labels. Does not rotate by default (FALSE).

font_size

(numeric) optional, specifies font size. It controls the font size for plot titles, axis labels, and legends.

• If vector of length == 1 then the font sizes will have a fixed size.

• while vector of value, min, and max allows dynamic adjustment.

alpha

(integer(1) or integer(3)) optional, specifies point opacity.

• When the length of alpha is one: the plot points will have a fixed opacity.

• When the length of alpha is three: the plot points opacity are dynamically adjusted based on vector of value, min, and max.

size

(integer(1) or integer(3)) optional, specifies point size.

• When the length of size is one: the plot point sizes will have a fixed size.

• When the length of size is three: the plot points size are dynamically adjusted based on vector of value, min, and max.

pre_output

(shiny.tag) optional, text or UI element to be displayed before the module's output, providing context or a title. with text placed before the output to put the output into context. For example a title.

post_output

(shiny.tag) optional, text or UI element to be displayed after the module's output, adding context or further instructions. Elements like shiny::helpText() are useful.

decorators

(list of teal_transform_module, named list of teal_transform_module or NULL) optional, if not NULL, decorator for tables or plots included in the module. When a named list of teal_transform_module, the decorators are applied to the respective output objects.

Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.

See section "Decorating tm_a_pca" below for more details.

Value

Object of class teal_module to be used in teal applications.

Decorating tm_a_pca

This module generates the following objects, which can be modified in place using decorators:

• elbow_plot (ggplot2)

• circle_plot (ggplot2)

• biplot (ggplot2)

• eigenvector_plot (ggplot2)

Decorators can be applied to all outputs or only to specific objects using a named list of teal_transform_module objects. The "default" name is reserved for decorators that are applied to all outputs. See code snippet below:

tm_a_pca(
   ..., # arguments for module
   decorators = list(
     default = list(teal_transform_module(...)), # applied to all outputs
     elbow_plot = list(teal_transform_module(...)), # applied only to `elbow_plot` output
     circle_plot = list(teal_transform_module(...)) # applied only to `circle_plot` output
     biplot = list(teal_transform_module(...)) # applied only to `biplot` output
     eigenvector_plot = list(teal_transform_module(...)) # applied only to `eigenvector_plot` output
   )
)

For additional details and examples of decorators, refer to the vignette vignette("decorate-modules-output", package = "teal") or the teal::teal_transform_module() documentation.

Examples in Shinylive

example-1

Open in Shinylive

example-2

Open in Shinylive

Examples

# general data example
data <- teal_data()
data <- within(data, {
  require(nestcolor)
  USArrests <- USArrests
})

app <- init(
  data = data,
  modules = modules(
    tm_a_pca(
      "PCA",
      dat = data_extract_spec(
        dataname = "USArrests",
        select = select_spec(
          choices = variable_choices(
            data = data[["USArrests"]], c("Murder", "Assault", "UrbanPop", "Rape")
          ),
          selected = c("Murder", "Assault"),
          multiple = TRUE
        ),
        filter = NULL
      )
    )
  )
)
#> Initializing tm_a_pca
#> Initializing reporter_previewer_module
if (interactive()) {
  shinyApp(app$ui, app$server)
}


# CDISC data example
data <- teal_data()
data <- within(data, {
  require(nestcolor)
  ADSL <- teal.data::rADSL
})
join_keys(data) <- default_cdisc_join_keys[names(data)]

app <- init(
  data = data,
  modules = modules(
    tm_a_pca(
      "PCA",
      dat = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          choices = variable_choices(
            data = data[["ADSL"]], c("BMRKR1", "AGE", "EOSDY")
          ),
          selected = c("BMRKR1", "AGE"),
          multiple = TRUE
        ),
        filter = NULL
      )
    )
  )
)
#> Initializing tm_a_pca
#> Initializing reporter_previewer_module
if (interactive()) {
  shinyApp(app$ui, app$server)
}