Personalized Color Choices in Data Visualization

library(forestly)
library(metalite)

The interactive AE forest plots include AE-specific tables that visualize AE proportions, differences, and confidence intervals (CI). In this vignette, we introduce how to customize the plotting colors.

1 Step 1: build your metadata

Building interactive AE forest plots starts with constructing the metadata. The detailed procedure for building metadata is covered in the vignette Generate Interactive AE Forest Plots with Drill Down to AE Listing. Therefore, in this vignette, we will skip those details and directly use the metadata created there.

adsl <- forestly_adsl
adae <- forestly_adae

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

meta <- meta_adam(population = adsl, observation = adae) |>
  define_plan(plan = plan(
    analysis = "ae_forestly",
    population = "apat",
    observation = "apat",
    parameter = "any;drug-related"
  )) |>
  define_analysis(name = "ae_forestly", label = "Interactive Forest Plot") |>
  define_population(
    name = "apat", group = "TRTA", id = "USUBJID",
    subset = SAFFL == "Y", label = "All Patient as Treated"
  ) |>
  define_observation(
    name = "apat", group = "TRTA",
    subset = SAFFL == "Y", label = "All Patient as Treated"
  ) |>
  define_parameter(
    name = "any",
    subset = NULL,
    label = "Any AEs",
    var = "AEDECOD", soc = "AEBODSYS"
  ) |>
  define_parameter(
    name = "drug-related",
    subset = toupper(AREL) == "RELATED",
    label = "Drug-related AEs",
    var = "AEDECOD", soc = "AEBODSYS"
  ) |>
  meta_build()

2 Step 2: personalized color choices

Users can specify custom colors by using the color = ... argument within the format_ae_forestly() function. By default, the color scheme is based on the branding of Merck & Co., Inc., Rahway, NJ, USA.

In the example below, we modify the colors to c("black", "grey60", "grey40") to represent the three arms in the plot. The default color palette supports up to 4 arms; for studies with more than 4 arms, we recommend users define their own color settings to ensure clear visualization.

meta |>
  prepare_ae_forestly() |>
  format_ae_forestly(color = c("black", "grey60", "grey40")) |>
  ae_forestly()

AE Criteria

Incidence (%) in One or More Treatment Groups

Show/Hide SOC column