Package 'forestly' reference manual

Title:	Interactive Forest Plot
Description:	Interactive forest plot for clinical trial safety analysis using 'metalite', 'reactable', 'plotly', and Analysis Data Model (ADaM) datasets. Includes functionality for adverse event filtering, incidence-based group filtering, hover-over reveals, and search and sort operations. The workflow allows for metadata construction, data preparation, output formatting, and interactive plot generation.
Authors:	Yilong Zhang [aut], Benjamin Wang [aut, cre], Yujie Zhao [aut], Nan Xiao [ctb], Hiroaki Fukuda [aut], Yulia Sidi [ctb], Xuan Deng [ctb], Jeetener Chauhan [ctb], Li Ma [ctb], Chen Wang [ctb], Madhusudhan Ginnaram [ctb], Merck & Co., Inc., Rahway, NJ, USA and its affiliates [cph]
Maintainer:	Benjamin Wang <[email protected]>
License:	GPL (>= 3)
Version:	0.1.4
Built:	2026-05-27 20:12:23 UTC
Source:	https://github.com/merck/forestly

Display interactive forest plot

Description

Display interactive forest plot

Usage

ae_forestly(
  outdata,
  display_soc_toggle = TRUE,
  display_diff_toggle = FALSE,
  filter = c("prop", "n"),
  filter_label = NULL,
  filter_range = NULL,
  ae_label = NULL,
  width = 1400,
  max_page = NULL,
  dowload_button = FALSE
)
ae_forestly(
  outdata,
  display_soc_toggle = TRUE,
  display_diff_toggle = FALSE,
  filter = c("prop", "n"),
  filter_label = NULL,
  filter_range = NULL,
  ae_label = NULL,
  width = 1400,
  max_page = NULL,
  dowload_button = FALSE
)

Arguments

outdata

An outdata object created by format_ae_forestly().

display_soc_toggle

A boolean value to display SOC toggle button.

display_diff_toggle

A boolean value to display risk difference toggle button.

filter

A character value of the filter variable. If NULL, the slider bar will not be displayed.

A character value of the label for slider bar.

filter_range

A numeric vector of length 2 for the range of the slider bar.

ae_label

A character value of the label for criteria. If NULL (default), the range is automatically calculated from the data. If only one value is provided, it will be used as the maximum and minimum will be 0.

width

A numeric value of width of the table in pixels.

max_page

A numeric value of max page number shown in the table.

dowload_button

A logical value to display download button.

Value

An AE forest plot saved as a shiny.tag.list object.

Examples

adsl <- forestly_adsl[1:100, ]
adae <- forestly_adae[1:100, ]
if (interactive()) {
  meta_forestly(
    dataset_adsl = adsl,
    dataset_adae = adae,
  ) |>
    prepare_ae_forestly() |>
    format_ae_forestly() |>
    ae_forestly()
}
adsl <- forestly_adsl[1:100, ]
adae <- forestly_adae[1:100, ]
if (interactive()) {
  meta_forestly(
    dataset_adsl = adsl,
    dataset_adae = adae,
  ) |>
    prepare_ae_forestly() |>
    format_ae_forestly() |>
    ae_forestly()
}

Add background for creating plot with customized color

Description

Creates colored background for panels of rainfall or forest plot.

Usage

background_panel(
  g,
  background_color = c("#69B8F7", "#FFFFFF"),
  background_alpha = 0.3
)
background_panel(
  g,
  background_color = c("#69B8F7", "#FFFFFF"),
  background_alpha = 0.3
)

Arguments

g

A ggplot object for adding colored background.

background_color

A vector of colors that defines the color for the plot background. Default is c("#69B8F7", "#FFFFFF"), which are pastel blue and white. The colors will be recycled.

background_alpha

Opacity of a geom. Default is 0.3.

Value

Plot as a colored background to add panels for rainfall or forest plot.

Examples

library(ggplot2)

df <- data.frame(
  study = c("S1", "S2", "S3", "S4", "S5", "S6", "S7"),
  item = as.factor(1:7),
  effect = c(-.4, -.25, -.1, .1, .15, .2, .3),
  lower = c(-.43, -.29, -.17, -.02, .04, .17, .27),
  upper = c(-.37, -.21, -.03, .22, .24, .23, .33)
)

ggplot(data = df) |>
  background_panel(background_color = c("grey", "white"), background_alpha = 0.4) +
  geom_point(aes(y = item, x = effect)) +
  geom_errorbar(aes(y = item, x = effect, xmin = lower, xmax = upper), width = 0.4) +
  scale_y_discrete(name = "", breaks = 1:nrow(df), labels = df$study)
library(ggplot2)

df <- data.frame(
  study = c("S1", "S2", "S3", "S4", "S5", "S6", "S7"),
  item = as.factor(1:7),
  effect = c(-.4, -.25, -.1, .1, .15, .2, .3),
  lower = c(-.43, -.29, -.17, -.02, .04, .17, .27),
  upper = c(-.37, -.21, -.03, .22, .24, .23, .33)
)

ggplot(data = df) |>
  background_panel(background_color = c("grey", "white"), background_alpha = 0.4) +
  geom_point(aes(y = item, x = effect)) +
  geom_errorbar(aes(y = item, x = effect, xmin = lower, xmax = upper), width = 0.4) +
  scale_y_discrete(name = "", breaks = 1:nrow(df), labels = df$study)

An adverse event dataset

Description

A dataset containing the adverse event information of a clinical trial following the CDISC ADaM standard.

Usage

forestly_adae
forestly_adae

Format

A data frame with 736 rows and 56 variables.

Details

Definition of each variable can be found at https://github.com/phuse-org/phuse-scripts/tree/master/data/adam/cdisc.

Source

https://github.com/phuse-org/phuse-scripts/tree/master/data/adam/cdisc

An adverse event dataset

Description

A dataset containing the adverse event information of a clinical trial following the CDISC ADaM standard.

Usage

forestly_adae_3grp
forestly_adae_3grp

Format

A data frame with 1191 rows and 56 variables.

Details

Definition of each variable can be found at https://github.com/phuse-org/phuse-scripts/tree/master/data/adam/cdisc.

Source

https://github.com/phuse-org/phuse-scripts/tree/master/data/adam/cdisc

A subject level demographic dataset

Description

A dataset containing the demographic information of a clinical trial following the CDISC ADaM standard.

Usage

forestly_adsl
forestly_adsl

Format

A data frame with 170 rows and 49 variables.

Details

Definition of each variable can be found at https://github.com/phuse-org/phuse-scripts/tree/master/data/adam/cdisc.

Source

https://github.com/phuse-org/phuse-scripts/tree/master/data/adam/cdisc

A subject level demographic dataset

Description

A dataset containing the demographic information of a clinical trial following the CDISC ADaM standard.

Usage

forestly_adsl_3grp
forestly_adsl_3grp

Format

A data frame with 254 rows and 49 variables.

Details

Definition of each variable can be found at https://github.com/phuse-org/phuse-scripts/tree/master/data/adam/cdisc.

Source

https://github.com/phuse-org/phuse-scripts/tree/master/data/adam/cdisc

Format outdata for interactive forest plot

Description

Format outdata for interactive forest plot

Usage

format_ae_forestly(
  outdata,
  display = c("n", "prop", "fig_prop", "fig_diff"),
  digits = 1,
  width_term = 200,
  width_fig = 320,
  width_n = 40,
  width_prop = 60,
  width_diff = 80,
  footer_space = 90,
  prop_range = NULL,
  diff_range = NULL,
  color = NULL,
  ae_col_header = NULL,
  diff_label = "Treatment <- Favor -> Placebo",
  diff_col_header = NULL,
  diff_fig_header = NULL
)
format_ae_forestly(
  outdata,
  display = c("n", "prop", "fig_prop", "fig_diff"),
  digits = 1,
  width_term = 200,
  width_fig = 320,
  width_n = 40,
  width_prop = 60,
  width_diff = 80,
  footer_space = 90,
  prop_range = NULL,
  diff_range = NULL,
  color = NULL,
  ae_col_header = NULL,
  diff_label = "Treatment <- Favor -> Placebo",
  diff_col_header = NULL,
  diff_fig_header = NULL
)

Arguments

outdata

An outdata object created by prepare_ae_forestly().

display

A character vector of measurement to be displayed.

n: Number of subjects with AE.
prop: Proportion of subjects with AE.
total: Total columns.
diff: Risk difference.

digits

A number of digits after decimal point to be displayed for proportion and risk difference.

width_term

Width in px for AE term column.

width_fig

Width in px for proportion and risk difference figure.

width_n

Width in px for "N" columns.

width_prop

Width in px for "(%)" columns.

width_diff

Width in px for risk difference columns.

footer_space

Space in px for footer to display legend.

prop_range

A vector of lower and upper limit of x-axis for proportion figure.

diff_range

A vector of lower and upper limit of x-axis for risk difference figure.

color

A vector of colors for analysis groups. Default value supports up to 4 groups.

ae_col_header

Column header for adverse events item columns. If NULL (default) and "par" specified in components from prepare_ae_forestly(), uses "Adverse Event". If NULL and "soc" specified in components from prepare_ae_forestly(), uses "System Organ Class" for "soc".

diff_label

x-axis label for risk difference.

diff_col_header

Column header for risk difference table columns. If NULL (default), uses "Risk Difference (%)
vs. Reference Group".

diff_fig_header

Column header for risk difference figure. If NULL (default), uses "Risk Difference (%) + 95% CI
vs. Reference Group".

Value

An outdata object.

Examples

adsl <- forestly_adsl[1:100, ]
adae <- forestly_adae[1:100, ]
meta_forestly(
  dataset_adsl = adsl,
  dataset_adae = adae
) |>
  prepare_ae_forestly() |>
  format_ae_forestly()
adsl <- forestly_adsl[1:100, ]
adae <- forestly_adae[1:100, ]
meta_forestly(
  dataset_adsl = adsl,
  dataset_adae = adae
) |>
  prepare_ae_forestly() |>
  format_ae_forestly()

Create metadata for interactive forest plot

Description

Create metadata for interactive forest plot

Usage

meta_forestly(
  dataset_adsl,
  dataset_adae,
  population_term = "apat",
  observation_term = "safety",
  parameter_term = "any;rel",
  population_subset,
  observation_subset,
  treatment_group = "TRTA"
)
meta_forestly(
  dataset_adsl,
  dataset_adae,
  population_term = "apat",
  observation_term = "safety",
  parameter_term = "any;rel",
  population_subset,
  observation_subset,
  treatment_group = "TRTA"
)

Arguments

dataset_adsl

ADSL source dataset.

dataset_adae

ADAE source dataset.

population_term

A character value of population term name.

observation_term

A character value of observation term name.

parameter_term

A character value of parameter term name.

population_subset

An unquoted condition for selecting the populations from ADSL dataset.

observation_subset

An unquoted condition for selecting the observations from ADAE dataset.

treatment_group

A character value of treatment group name.

Value

A metalite object.

Examples

meta_forestly(
  forestly_adsl,
  forestly_adae,
  population_term = "apat",
  observation_term = "safety",
  parameter_term = "any;rel"
)
meta_forestly(
  forestly_adsl,
  forestly_adae,
  population_term = "apat",
  observation_term = "safety",
  parameter_term = "any;rel"
)

Dot plot

Description

Create a dot plot by item. For instance, this could be used to create AEs incidence plot by Preferred Term and treatment group, as part of a rainfall plot.

Usage

plot_dot(
  tbl,
  prop_cols = c("prop_1", "prop_2"),
  y_var,
  label,
  x_breaks = NULL,
  color = NULL,
  shape = NULL,
  title = "AE (%)",
  background_color = c("#69B8F7", "#FFFFFF"),
  background_alpha = 0.3,
  theme = theme_panel(show_text = TRUE, show_ticks = TRUE),
  legend_nrow = 1
)
plot_dot(
  tbl,
  prop_cols = c("prop_1", "prop_2"),
  y_var,
  label,
  x_breaks = NULL,
  color = NULL,
  shape = NULL,
  title = "AE (%)",
  background_color = c("#69B8F7", "#FFFFFF"),
  background_alpha = 0.3,
  theme = theme_panel(show_text = TRUE, show_ticks = TRUE),
  legend_nrow = 1
)

Arguments

tbl

A data frame selected from input data set to display on this plot. y and x variables are required.

prop_cols

A character vector of proportion columns to be used for a plot.

y_var

A character string that specifies a variable to be displayed on the y-axis.

label

A character vector of labels for each treatment group. The control group label should be specified as the last element of the vector.

x_breaks

A numeric vector for x-axis breaks. Default is NULL, which uses a default ggplot2 x-axis breaks presentation.

color

Color for each treatment group.

shape

Shape for each treatment group. Default is circle and square. Input values could be either a character or numeric value, For details, see https://ggplot2.tidyverse.org/articles/ggplot2-specs.html.

title

Panel title. Default is "AE (%)".

background_color

Plot background color. Default is c("#69B8F7", "#FFFFFF"), which are pastel blue and white. The value of this argument is used as input for the background_color argument in background_panel().

background_alpha

Opacity of the background. Default is 0.3. The value of this argument is the input for background_alpha argument in background_panel().

theme

Panel theme, including the y-axis text, ticks, and plot margin. Default is theme_panel(show_text = TRUE, show_ticks = TRUE). For more details, refer to theme_panel.

legend_nrow

Integer, the number of rows for a legend display. Must be smaller than or equal to the number of the treatment groups. To omit the legend, set this to NULL. Default is 1.

Value

AEs incidence plot by item and treatment group.

Examples

forestly_adsl$TRTA <- factor(
  forestly_adsl$TRT01A,
  levels = c("Xanomeline Low Dose", "Placebo"),
  labels = c("Low Dose", "Placebo")
)
forestly_adae$TRTA <- factor(
  forestly_adae$TRTA,
  levels = c("Xanomeline Low Dose", "Placebo"),
  labels = c("Low Dose", "Placebo")
)

meta <- meta_forestly(
  dataset_adsl = forestly_adsl,
  dataset_adae = forestly_adae,
  population_term = "apat",
  observation_term = "wk12",
  parameter_term = "any;rel;ser"
) |>
  prepare_ae_forestly() |>
  format_ae_forestly()

meta_any <- meta$tbl[1:20, ] |> dplyr::filter(parameter == "any")
meta_any |>
  plot_dot("name", prop_cols = c("prop_1", "prop_2"), label = c("Treatment", "Placebo"))
forestly_adsl$TRTA <- factor(
  forestly_adsl$TRT01A,
  levels = c("Xanomeline Low Dose", "Placebo"),
  labels = c("Low Dose", "Placebo")
)
forestly_adae$TRTA <- factor(
  forestly_adae$TRTA,
  levels = c("Xanomeline Low Dose", "Placebo"),
  labels = c("Low Dose", "Placebo")
)

meta <- meta_forestly(
  dataset_adsl = forestly_adsl,
  dataset_adae = forestly_adae,
  population_term = "apat",
  observation_term = "wk12",
  parameter_term = "any;rel;ser"
) |>
  prepare_ae_forestly() |>
  format_ae_forestly()

meta_any <- meta$tbl[1:20, ] |> dplyr::filter(parameter == "any")
meta_any |>
  plot_dot("name", prop_cols = c("prop_1", "prop_2"), label = c("Treatment", "Placebo"))

Plot to display risk difference

Description

Create a plot to display risk difference for each item.

Usage

plot_errorbar(
  tbl,
  ci_cols = c("diff_1", "lower_1", "upper_1"),
  y_var,
  errbar_width = 0.4,
  color = NULL,
  shape = NULL,
  label,
  x_breaks = NULL,
  grp_abbrev = "paired",
  favor_direction = "negative",
  vline = NULL,
  line_type = 1,
  title = "Risk Diff. + 95% CI \n (Percentage Points)",
  background_color = c("#69B8F7", "#FFFFFF"),
  background_alpha = 0.3,
  theme = theme_panel(show_text = TRUE, show_ticks = TRUE),
  legend_nrow = 1
)
plot_errorbar(
  tbl,
  ci_cols = c("diff_1", "lower_1", "upper_1"),
  y_var,
  errbar_width = 0.4,
  color = NULL,
  shape = NULL,
  label,
  x_breaks = NULL,
  grp_abbrev = "paired",
  favor_direction = "negative",
  vline = NULL,
  line_type = 1,
  title = "Risk Diff. + 95% CI \n (Percentage Points)",
  background_color = c("#69B8F7", "#FFFFFF"),
  background_alpha = 0.3,
  theme = theme_panel(show_text = TRUE, show_ticks = TRUE),
  legend_nrow = 1
)

Arguments

tbl

A data frame selected from input data set to display on this plot. y and x variables are required.

ci_cols

A character vector of columns for a risk difference to be used for a plot. Need 3 columns, risk difference, lower bound, and upper bound.

y_var

A character string that specifies a variable to be displayed on the y-axis.

errbar_width

A numeric value to define the error bar width. Default is 0.4. Value of this argument will be a half length of the error bar, for example, errorbar_width = 0.2 means half of the error bar width is 0.2 unit length. If y = 4, the error bar will range from y = 3.8 to y = 4.2.

color

Color for each treatment group.

shape

Shape for each treatment group. Default is circle and square. Input values could be either a character or numeric value, For details, see https://ggplot2.tidyverse.org/articles/ggplot2-specs.html.

label

A character vector of labels for each treatment group. The control group label should be specified as the last element of the vector.

x_breaks

A numeric vector for x-axis breaks. Default is NULL, which uses a default ggplot2 x-axis breaks presentation.

grp_abbrev

A character vector for displaying the treatment groups on a favor bar. If grp_abbrev = "paired", treatment label on the error bar will be the same as in the label argument. If grp_abbrev = "none", the error bar will not be shown. Also, for customized terms, users can provide an alternative vector of treatment labels. Default is "paired".

favor_direction

The position of a favor label under the condition "comparison is treatment – control". For AEs, favor_direction should be "negative"; for efficacy, favor_direction should be "positive".

vline

Vertical reference line position. Default is NULL. Users can define one or multiple numeric values in a vector as a reference line position.

line_type

Reference line type. Default is solid line. Users can define one or multiple line types in a vector (can be numeric such as 1, 2, 3 or character such as "solid", "dashed"). The values will be recycled and the order will be consistent with the argument vline.

title

Plot title. Default is "Risk Diff. + 95% CI \\n (Percentage Points)".

background_color

Plot background color. Default is c("#69B8F7", "#FFFFFF"), which are pastel blue and white. The value of this argument is used as input for the background_color argument in background_panel().

background_alpha

Opacity of the background. Default is 0.3. The value of this argument is the input for background_alpha argument in background_panel().

theme

Panel theme, including the y-axis text, ticks, and plot margin. Default is theme_panel(show_text = TRUE, show_ticks = TRUE). For more details, refer to theme_panel.

legend_nrow

Integer, the number of rows for a legend display. Must be smaller than or equal to the number of the treatment groups. To omit the legend, set this to NULL. Default is 1.

Value

A risk difference plot for each item.

Examples

forestly_adsl$TRTA <- factor(
  forestly_adsl$TRT01A,
  levels = c("Xanomeline Low Dose", "Placebo"),
  labels = c("Low Dose", "Placebo")
)
forestly_adae$TRTA <- factor(
  forestly_adae$TRTA,
  levels = c("Xanomeline Low Dose", "Placebo"),
  labels = c("Low Dose", "Placebo")
)

meta <- meta_forestly(
  dataset_adsl = forestly_adsl,
  dataset_adae = forestly_adae,
  population_term = "apat",
  observation_term = "wk12",
  parameter_term = "any;rel;ser"
) |>
  prepare_ae_forestly() |>
  format_ae_forestly()

meta_any <- meta$tbl[1:20, ] |> dplyr::filter(parameter == "any")
meta_any |>
  dplyr::select(name, diff_1, lower_1, upper_1) |>
  plot_errorbar(
    y_var = "name",
    ci_cols = c("diff_1", "lower_1", "upper_1"),
    label = c("Treatment", "Placebo")
  )
forestly_adsl$TRTA <- factor(
  forestly_adsl$TRT01A,
  levels = c("Xanomeline Low Dose", "Placebo"),
  labels = c("Low Dose", "Placebo")
)
forestly_adae$TRTA <- factor(
  forestly_adae$TRTA,
  levels = c("Xanomeline Low Dose", "Placebo"),
  labels = c("Low Dose", "Placebo")
)

meta <- meta_forestly(
  dataset_adsl = forestly_adsl,
  dataset_adae = forestly_adae,
  population_term = "apat",
  observation_term = "wk12",
  parameter_term = "any;rel;ser"
) |>
  prepare_ae_forestly() |>
  format_ae_forestly()

meta_any <- meta$tbl[1:20, ] |> dplyr::filter(parameter == "any")
meta_any |>
  dplyr::select(name, diff_1, lower_1, upper_1) |>
  plot_errorbar(
    y_var = "name",
    ci_cols = c("diff_1", "lower_1", "upper_1"),
    label = c("Treatment", "Placebo")
  )

Prepare datasets for interactive forest plot

Description

Prepare datasets for interactive forest plot

Usage

prepare_ae_forestly(
  meta,
  population = NULL,
  observation = NULL,
  parameter = NULL,
  components = "par",
  reference_group = NULL,
  ae_listing_display = c("USUBJID", "SITEID", "SEX", "RACE", "AGE", "ASTDY", "AESER",
    "AEREL", "AEACN", "AEOUT", "ADURN", "ADURU"),
  ae_listing_unique = FALSE,
  bisection = 100,
  ...
)
prepare_ae_forestly(
  meta,
  population = NULL,
  observation = NULL,
  parameter = NULL,
  components = "par",
  reference_group = NULL,
  ae_listing_display = c("USUBJID", "SITEID", "SEX", "RACE", "AGE", "ASTDY", "AESER",
    "AEREL", "AEACN", "AEOUT", "ADURN", "ADURU"),
  ae_listing_unique = FALSE,
  bisection = 100,
  ...
)

Arguments

meta

A metadata object created by metalite.

population

A character value of population term name. The term name is used as key to link information.

observation

A character value of observation term name. The term name is used as key to link information.

parameter

A character value of parameter term name. The term name is used as key to link information.

components

A character vector of components name.

reference_group

An integer to indicate reference group. Default is 2 if there are 2 groups, otherwise, the default is 1.

ae_listing_display

A vector of name of variables used to display on AE listing table.

ae_listing_unique

A logical value to display only unique records on AE listing table.

bisection

A numeric value. A control parameter for the bisection method used to calculate confidence the lower and upper confidence interval bounds for the risk. The default value is 1e2.

...

Additional arguments passed to metalite.ae::rate_compare_sum().

Value

An outdata object.

Examples

adsl <- forestly_adsl[1:100, ]
adae <- forestly_adae[1:100, ]
meta_forestly(
  dataset_adsl = adsl,
  dataset_adae = adae
) |>
  prepare_ae_forestly()
adsl <- forestly_adsl[1:100, ]
adae <- forestly_adae[1:100, ]
meta_forestly(
  dataset_adsl = adsl,
  dataset_adae = adae
) |>
  prepare_ae_forestly()

Output static forest plot

Description

Output static forest plot

Usage

rtf_static_forestly(
  outdata,
  plot_calls,
  source,
  parameter = "any",
  n_rows = 25,
  orientation = "portrait",
  fig_size = c(6, 6),
  title = c("analysis", "observation", "population"),
  footnotes = NULL,
  text_font_size = 9,
  path_outdata = tempfile(fileext = ".Rdata"),
  path_outtable = tempfile(fileext = ".rtf")
)
rtf_static_forestly(
  outdata,
  plot_calls,
  source,
  parameter = "any",
  n_rows = 25,
  orientation = "portrait",
  fig_size = c(6, 6),
  title = c("analysis", "observation", "population"),
  footnotes = NULL,
  text_font_size = 9,
  path_outdata = tempfile(fileext = ".Rdata"),
  path_outtable = tempfile(fileext = ".rtf")
)

Arguments

outdata

An outdata object created by format_ae_forestly().

plot_calls

A list or vector of function calls.

source

A character value of the data source.

parameter

A character value of parameter term name.

n_rows

An integer value of the number of rows per page in a plot.

orientation

Orientation in 'portrait' or 'landscape'.

fig_size

A numeric vector of length 2 of figure width and height. The length should be 2 (width, height). The unit is inch.

title

Term "analysis", "observation" and "population") for collecting title from metadata or a character vector of table titles.

footnotes

A character vector of table footnotes.

text_font_size

Text font size. To vary text font size by column, use numeric vector with length of vector equal to number of columns displayed e.g. c(9,20,40).

path_outdata

A character string of the outdata path.

path_outtable

A character string of the outtable path.

Value

RTF file and source dataset for baseline characteristic table.

Examples

forestly_adsl$TRTA <- factor(
  forestly_adsl$TRT01A,
  levels = c("Xanomeline Low Dose", "Placebo"),
  labels = c("Low Dose", "Placebo")
)
forestly_adae$TRTA <- factor(
  forestly_adae$TRTA,
  levels = c("Xanomeline Low Dose", "Placebo"),
  labels = c("Low Dose", "Placebo")
)
outdata <- meta_forestly(
  dataset_adsl = forestly_adsl[1:40, ],
  dataset_adae = forestly_adae[1:40, ]
) |>
  prepare_ae_forestly()|>
  format_ae_forestly()

p1 <- substitute(
  plot_dot(
    tbl,
    prop_cols = c("prop_1", "prop_2"),
    y_var = "name",
    label = c("Treatment", "Placebo")
  )
)
p2 <- substitute(
  plot_errorbar(
    tbl,
    ci_cols = c("diff_1", "lower_1", "upper_1"),
    y_var = "name",
    label = c("Treatment", "Placebo"),
    legend_nrow = NULL,
    theme = theme_panel(show_ticks = FALSE, show_text = FALSE)
  )
)
p3 <- substitute(
  table_panel(
    tbl,
    n_cols = c("n_1", "n_2"),
    prop_cols = c("prop_1", "prop_2"),
    y_var = "name",
    theme = theme_panel(show_ticks = FALSE, show_text = FALSE),
    x_label = c("Treatment \n n(%)", "Placebo \n n(%)")
  )
)
outdata |> rtf_static_forestly(
  plot_calls = c(p1, p2, p3),
  source = "Source:  [CDISCpilot: adam-adsl; adae]",
  path_outdata = tempfile(fileext = ".Rdata"),
  path_outtable =  tempfile(fileext = ".rtf")
)
forestly_adsl$TRTA <- factor(
  forestly_adsl$TRT01A,
  levels = c("Xanomeline Low Dose", "Placebo"),
  labels = c("Low Dose", "Placebo")
)
forestly_adae$TRTA <- factor(
  forestly_adae$TRTA,
  levels = c("Xanomeline Low Dose", "Placebo"),
  labels = c("Low Dose", "Placebo")
)
outdata <- meta_forestly(
  dataset_adsl = forestly_adsl[1:40, ],
  dataset_adae = forestly_adae[1:40, ]
) |>
  prepare_ae_forestly()|>
  format_ae_forestly()

p1 <- substitute(
  plot_dot(
    tbl,
    prop_cols = c("prop_1", "prop_2"),
    y_var = "name",
    label = c("Treatment", "Placebo")
  )
)
p2 <- substitute(
  plot_errorbar(
    tbl,
    ci_cols = c("diff_1", "lower_1", "upper_1"),
    y_var = "name",
    label = c("Treatment", "Placebo"),
    legend_nrow = NULL,
    theme = theme_panel(show_ticks = FALSE, show_text = FALSE)
  )
)
p3 <- substitute(
  table_panel(
    tbl,
    n_cols = c("n_1", "n_2"),
    prop_cols = c("prop_1", "prop_2"),
    y_var = "name",
    theme = theme_panel(show_ticks = FALSE, show_text = FALSE),
    x_label = c("Treatment \n n(%)", "Placebo \n n(%)")
  )
)
outdata |> rtf_static_forestly(
  plot_calls = c(p1, p2, p3),
  source = "Source:  [CDISCpilot: adam-adsl; adae]",
  path_outdata = tempfile(fileext = ".Rdata"),
  path_outtable =  tempfile(fileext = ".rtf")
)

Create table panel ggplot2 object for rainfall or forest plot

Description

Creates a table panel ggplot2 object for rainfall or forest plot.

Usage

table_panel(
  tbl,
  n_cols = c("n_1", "n_2"),
  prop_cols = c("prop_1", "prop_2"),
  y_var,
  x_label = NULL,
  text_color = NULL,
  text_size = 8,
  text_format_by = "column",
  background_color = c("#69B8F7", "#FFFFFF"),
  theme = theme_panel(show_ticks = TRUE, show_text = TRUE),
  background_alpha = 0.3
)
table_panel(
  tbl,
  n_cols = c("n_1", "n_2"),
  prop_cols = c("prop_1", "prop_2"),
  y_var,
  x_label = NULL,
  text_color = NULL,
  text_size = 8,
  text_format_by = "column",
  background_color = c("#69B8F7", "#FFFFFF"),
  theme = theme_panel(show_ticks = TRUE, show_text = TRUE),
  background_alpha = 0.3
)

Arguments

tbl

A data frame to be displayed in this table.

n_cols

A character vector of columns for subject count to be used for a plot.

prop_cols

A character vector of proportion columns to be used for a plot.

y_var

A string of a variable name from tbl for the y axis variable.

x_label

Labels displayed on the top of table for each column of table. Default is NULL, variable name will display as label.

text_color

Defines colors to display each treatment group.

text_size

Numeric font size for data on each column. Default is 8 for each column.

text_format_by

An option for formatting a data by columns or rows. Default is "column" and text color will be varied by column. If text_format_by = "row", then text color will be varied by row. If text_format_by = "group", then text color will be varied by treatment group.

background_color

Color for the plot background. Default is c("#69B8F7", "#FFFFFF") which are pastel blue and white. The value of this argument will be the input value for the background_color argument in background_panel().

theme

Controls display of y axis text, ticks and plot margin. By default, theme_panel(show_text = TRUE, show_ticks = TRUE) is used. Users are suggested to use theme_panel().

background_alpha

Opacity of the background. Default is 0.3. The value of this argument will be the input value for the background_alpha argument in background_panel().

Value

A ggplot2 object for table panel.

Examples

forestly_adsl$TRTA <- factor(
  forestly_adsl$TRT01A,
  levels = c("Xanomeline Low Dose", "Placebo"),
  labels = c("Low Dose", "Placebo")
)
forestly_adae$TRTA <- factor(
  forestly_adae$TRTA,
  levels = c("Xanomeline Low Dose", "Placebo"),
  labels = c("Low Dose", "Placebo")
)

meta <- meta_forestly(
  dataset_adsl = forestly_adsl,
  dataset_adae = forestly_adae,
  population_term = "apat",
  observation_term = "wk12",
  parameter_term = "any;rel;ser"
) |>
  prepare_ae_forestly() |>
  format_ae_forestly()

meta_any <- meta$tbl[1:20, ] |> dplyr::filter(parameter == "any")

meta_any |>
  table_panel(y_var = "name")
forestly_adsl$TRTA <- factor(
  forestly_adsl$TRT01A,
  levels = c("Xanomeline Low Dose", "Placebo"),
  labels = c("Low Dose", "Placebo")
)
forestly_adae$TRTA <- factor(
  forestly_adae$TRTA,
  levels = c("Xanomeline Low Dose", "Placebo"),
  labels = c("Low Dose", "Placebo")
)

meta <- meta_forestly(
  dataset_adsl = forestly_adsl,
  dataset_adae = forestly_adae,
  population_term = "apat",
  observation_term = "wk12",
  parameter_term = "any;rel;ser"
) |>
  prepare_ae_forestly() |>
  format_ae_forestly()

meta_any <- meta$tbl[1:20, ] |> dplyr::filter(parameter == "any")

meta_any |>
  table_panel(y_var = "name")

Theme function for plot with multiple panels

Description

Specifies theme for a plot with multiple panels.

Usage

theme_panel(show_text = TRUE, show_ticks = TRUE)
theme_panel(show_text = TRUE, show_ticks = TRUE)

Arguments

show_text

A logical value that controls text display on the y axis. Default is TRUE.

show_ticks

A logical value that controls ticks display on the y axis. Default is TRUE.

Value

Theme for a specific panel.

Examples

library(ggplot2)

p <- ggplot(mpg, aes(displ, hwy, colour = class)) +
  geom_point()

p
p + theme_panel()
library(ggplot2)

p <- ggplot(mpg, aes(displ, hwy, colour = class)) +
  geom_point()

p
p + theme_panel()

Package 'forestly'

Help Index

Display interactive forest plot

Description

Usage

Arguments

Value

Examples

Add background for creating plot with customized color

Description

Usage

Arguments

Value

Examples

An adverse event dataset

Description

Usage

Format

Details

Source

An adverse event dataset

Description

Usage

Format

Details

Source

A subject level demographic dataset

Description

Usage

Format

Details

Source

A subject level demographic dataset

Description

Usage

Format

Details

Source

Format outdata for interactive forest plot

Description

Usage

Arguments

Value

Examples

Create metadata for interactive forest plot

Description

Usage

Arguments

Value

Examples

Dot plot

Description

Usage

Arguments

Value

Examples

Plot to display risk difference

Description

Usage

Arguments

Value

Examples

Prepare datasets for interactive forest plot

Description

Usage

Arguments

Value

Examples

Output static forest plot

Description

Usage

Arguments

Value

Examples

Create table panel ggplot2 object for rainfall or forest plot

Description

Usage

Arguments

Value

Examples