PKPG06

Boxplot of Metabolite to Parent Ratios by Treatment

---

Output

Plot with Whiskers at ±1.5 Times Inter-Quartile Range

Drug X Boxplot

Preview

plot <- ggplot(anl_x, aes(x = PARAMCD, y = ratio, fill = ACTARM)) +
  geom_boxplot(outlier.size = 2) +
  stat_boxplot(geom = "errorbar") +
  stat_summary(
    geom = "point",
    fun = "mean",
    col = "black",
    size = 5,
    shape = 8,
    position = position_dodge(0.75)
  ) +
  geom_text(
    data = . %>% dplyr::group_by(PARAMCD, ACTARM) %>% dplyr::filter(ratio %in% boxplot.stats(ratio)$out),
    aes(x = PARAMCD, y = ratio, label = USUBJID, col = ACTARM),
    size = 3,
    hjust = -0.2,
    position = position_dodge(0.75),
    show.legend = FALSE
  ) +
  labs(
    title = "Boxplot of Metabolite to Parent Ratios by Treatment",
    subtitle = paste0(
      "Analyte: Plasma Drug X, Metabolite Drug X ",
      "\nPK Parameter: ",
      as.character(paste(unique(anl_x$PARAMCD), collapse = ", ")),
      "\nVisit: ",
      as.character((unique(anl_x$AVISIT)))
    ),
    caption = "Program: \nOutput:",
    x = "Parameter",
    y = "Metabolite to Parent Ratio"
  ) +
  theme(plot.caption = element_text(hjust = 0)) +
  theme_nest()

# PKPG06
plot

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plot <- ggplot(anl_x, aes(x = PARAMCD, y = ratio, fill = ACTARM)) +

geom_boxplot(outlier.size = 2) +

stat_boxplot(geom = "errorbar") +

stat_summary(

geom = "point",

fun = "mean",

col = "black",

size = 5,

shape = 8,

position = position_dodge(0.75)

) +

geom_text(

data = . %>% dplyr::group_by(PARAMCD, ACTARM) %>% dplyr::filter(ratio %in% boxplot.stats(ratio)$out),

aes(x = PARAMCD, y = ratio, label = USUBJID, col = ACTARM),

size = 3,

hjust = -0.2,

position = position_dodge(0.75),

show.legend = FALSE

) +

labs(

title = "Boxplot of Metabolite to Parent Ratios by Treatment",

subtitle = paste0(

"Analyte: Plasma Drug X, Metabolite Drug X ",

"\nPK Parameter: ",

as.character(paste(unique(anl_x$PARAMCD), collapse = ", ")),

"\nVisit: ",

as.character((unique(anl_x$AVISIT)))

),

caption = "Program: \nOutput:",

x = "Parameter",

y = "Metabolite to Parent Ratio"

) +

theme(plot.caption = element_text(hjust = 0)) +

theme_nest()

# PKPG06

_webr_editor_2 = Object {code: "plot <- ggplot(anl_x, aes(x = PARAMCD, y = ratio, …_text(hjust = 0)) +\n theme_nest()\n\n# PKPG06\nplot", options: Object, indicator: Ke}

Drug Y Boxplot

Preview

plot <- ggplot(anl_y, aes(x = PARAMCD, y = ratio, fill = ACTARM)) +
  geom_boxplot(outlier.size = 2) +
  stat_boxplot(geom = "errorbar") +
  stat_summary(
    geom = "point",
    fun = "mean",
    col = "black",
    size = 5,
    shape = 8,
    position = position_dodge(0.75)
  ) +
  geom_text(
    data = . %>% dplyr::group_by(PARAMCD, ACTARM) %>% dplyr::filter(ratio %in% boxplot.stats(ratio)$out),
    aes(x = PARAMCD, y = ratio, label = USUBJID, color = ACTARM),
    size = 3,
    hjust = -0.2,
    position = position_dodge(0.75),
    show.legend = FALSE
  ) +
  labs(
    title = "Boxplot of Metabolite to Parent Ratios by Treatment",
    subtitle = paste0(
      "Analyte: Plasma Drug Y, Metabolite Drug Y ",
      "\nPK Parameter: ",
      as.character(paste(unique(anl_y$PARAMCD), collapse = ", ")),
      "\nVisit: ",
      as.character((unique(anl_y$AVISIT)))
    ),
    caption = "Program: \nOutput:",
    x = "Parameter",
    y = "Metabolite to Parent Ratio"
  ) +
  theme(plot.caption = element_text(hjust = 0)) +
  theme_nest()

# result
plot

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Experimental use!

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plot <- ggplot(anl_y, aes(x = PARAMCD, y = ratio, fill = ACTARM)) +

geom_boxplot(outlier.size = 2) +

stat_boxplot(geom = "errorbar") +

stat_summary(

geom = "point",

fun = "mean",

col = "black",

size = 5,

shape = 8,

position = position_dodge(0.75)

) +

geom_text(

data = . %>% dplyr::group_by(PARAMCD, ACTARM) %>% dplyr::filter(ratio %in% boxplot.stats(ratio)$out),

aes(x = PARAMCD, y = ratio, label = USUBJID, color = ACTARM),

size = 3,

hjust = -0.2,

position = position_dodge(0.75),

show.legend = FALSE

) +

labs(

title = "Boxplot of Metabolite to Parent Ratios by Treatment",

subtitle = paste0(

"Analyte: Plasma Drug Y, Metabolite Drug Y ",

"\nPK Parameter: ",

as.character(paste(unique(anl_y$PARAMCD), collapse = ", ")),

"\nVisit: ",

as.character((unique(anl_y$AVISIT)))

),

caption = "Program: \nOutput:",

x = "Parameter",

y = "Metabolite to Parent Ratio"

) +

theme(plot.caption = element_text(hjust = 0)) +

theme_nest()

# result

_webr_editor_3 = Object {code: "plot <- ggplot(anl_y, aes(x = PARAMCD, y = ratio, …_text(hjust = 0)) +\n theme_nest()\n\n# result\nplot", options: Object, indicator: Ke}

Plot with Whiskers at Minimum and Maximum Values

Preview

# whiskers are formed with the minimum and maximum values
plot <- ggplot(anl_x, aes(x = PARAMCD, y = ratio, fill = ACTARM)) +
  geom_boxplot(outlier.size = 0) +
  stat_boxplot(geom = "errorbar", coef = NULL) +
  stat_summary(geom = "point", fun = "mean", col = "black", size = 5, shape = 8, position = position_dodge(0.75)) +
  labs(
    title = "Boxplot of Metabolite to Parent Ratios by Treatment",
    subtitle = paste0(
      "Analyte: Plasma Drug X, Metabolite Drug X ",
      "\nPK Parameter: ",
      as.character(paste(unique(anl_x$PARAMCD), collapse = ", ")),
      "\nVisit: ",
      as.character((unique(anl_x$AVISIT)))
    ),
    caption = "Program:\nOutput:",
    x = "Parameter",
    y = "Metabolite to Parent Ratio"
  ) +
  theme(plot.caption = element_text(hjust = 0)) +
  theme_nest()

# result
plot

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Experimental use!

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›

# whiskers are formed with the minimum and maximum values

plot <- ggplot(anl_x, aes(x = PARAMCD, y = ratio, fill = ACTARM)) +

geom_boxplot(outlier.size = 0) +

stat_boxplot(geom = "errorbar", coef = NULL) +

stat_summary(geom = "point", fun = "mean", col = "black", size = 5, shape = 8, position = position_dodge(0.75)) +

labs(

title = "Boxplot of Metabolite to Parent Ratios by Treatment",

subtitle = paste0(

"Analyte: Plasma Drug X, Metabolite Drug X ",

"\nPK Parameter: ",

as.character(paste(unique(anl_x$PARAMCD), collapse = ", ")),

"\nVisit: ",

as.character((unique(anl_x$AVISIT)))

),

caption = "Program:\nOutput:",

x = "Parameter",

y = "Metabolite to Parent Ratio"

) +

theme(plot.caption = element_text(hjust = 0)) +

theme_nest()

# result

plot

_webr_editor_4 = Object {code: "# whiskers are formed with the minimum and maximum…_text(hjust = 0)) +\n theme_nest()\n\n# result\nplot", options: Object, indicator: Ke}

Plot with Whiskers at 5th and 95th Percentiles

Preview

anl_x_without_outliers <- anl_x %>%
  dplyr::group_by(PARAMCD, ACTARM) %>%
  dplyr::mutate(outlier = ifelse(outliers(ratio), ratio, as.numeric(NA)))
plot <- ggplot(anl_x, aes(PARAMCD, ratio, fill = ACTARM, label = USUBJID)) +
  stat_summary(
    fun.data = quantiles, geom = "boxplot",
    position = position_dodge(1)
  ) +
  stat_summary(
    geom = "point",
    fun = "mean",
    col = "black",
    size = 5,
    shape = 8,
    position = position_dodge(1)
  ) +
  stat_summary(
    fun.data = quantiles, geom = "errorbar",
    position = position_dodge(1)
  ) +
  geom_point(
    data = anl_x_without_outliers,
    aes(x = PARAMCD, y = outlier),
    na.rm = TRUE,
    size = 2,
    position = position_dodge(1),
    show.legend = FALSE
  ) +
  geom_text(
    data = anl_x_without_outliers,
    aes(x = PARAMCD, y = outlier, label = USUBJID, color = ACTARM),
    na.rm = TRUE,
    size = 3,
    hjust = -0.2,
    vjust = 1,
    position = position_dodge(1),
    show.legend = FALSE
  ) +
  labs(
    title = "Boxplot of Metabolite to Parent Ratios by Treatment",
    subtitle = paste0(
      "Analyte: Plasma Drug X, Metabolite Drug X ",
      "\nPK Parameter: ",
      as.character(paste(unique(anl_x$PARAMCD), collapse = ", ")),
      "\nVisit: ",
      as.character((unique(anl_x$AVISIT)))
    ),
    caption = "Program: \nOutput:",
    x = "Parameter",
    y = "Metabolite to Parent Ratio"
  ) +
  theme(plot.caption = element_text(hjust = 0)) +
  theme_nest()

# result
plot

Try this using WebR

Experimental use!

WebR is a tool allowing you to run R code in the web browser. Modify the code below and click run to see the results. Alternatively, copy the code and click here to open WebR in a new tab.

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anl_x_without_outliers <- anl_x %>%

dplyr::group_by(PARAMCD, ACTARM) %>%

dplyr::mutate(outlier = ifelse(outliers(ratio), ratio, as.numeric(NA)))

plot <- ggplot(anl_x, aes(PARAMCD, ratio, fill = ACTARM, label = USUBJID)) +

stat_summary(

fun.data = quantiles, geom = "boxplot",

position = position_dodge(1)

) +

stat_summary(

geom = "point",

fun = "mean",

col = "black",

size = 5,

shape = 8,

position = position_dodge(1)

) +

stat_summary(

fun.data = quantiles, geom = "errorbar",

position = position_dodge(1)

) +

geom_point(

data = anl_x_without_outliers,

aes(x = PARAMCD, y = outlier),

na.rm = TRUE,

size = 2,

position = position_dodge(1),

show.legend = FALSE

) +

geom_text(

data = anl_x_without_outliers,

aes(x = PARAMCD, y = outlier, label = USUBJID, color = ACTARM),

na.rm = TRUE,

size = 3,

hjust = -0.2,

vjust = 1,

position = position_dodge(1),

_webr_editor_5 = Object {code: "anl_x_without_outliers <- anl_x %>%\n dplyr::group…_text(hjust = 0)) +\n theme_nest()\n\n# result\nplot", options: Object, indicator: Ke}

Data Setup

library(dplyr)
library(ggplot2)
library(tidyr)
library(tern)
library(nestcolor)

adpp <- random.cdisc.data::cadpp

# Filter NAs
adpp <- adpp %>%
  filter(PPSPEC != "NA" & PARAM != "NA" & PPCAT != "NA") %>%
  filter(PARAMCD == "CMAX" | PARAMCD == "AUCIFO", AVISITN == 1)

# filter data by PPCAT and calculate ratio
anl_x <- adpp %>%
  filter(PPCAT %in% c("Metabolite Drug X", "Plasma Drug X")) %>%
  pivot_wider(
    id_cols = c(USUBJID, ACTARM, PARAMCD, AVISIT),
    names_from = PPCAT,
    values_from = AVAL
  ) %>%
  dplyr::mutate(ratio = `Metabolite Drug X` / `Plasma Drug X`) %>%
  filter(!is.na(ratio), ratio != Inf)

anl_y <- adpp %>%
  filter(PPCAT %in% c("Metabolite Drug Y", "Plasma Drug Y")) %>%
  pivot_wider(
    id_cols = c(USUBJID, ACTARM, PARAMCD, AVISIT),
    names_from = PPCAT,
    values_from = AVAL
  ) %>%
  dplyr::mutate(ratio = `Metabolite Drug Y` / `Plasma Drug Y`) %>%
  filter(!is.na(ratio), ratio != Inf)

# functions to calculate custom quantiles and outliers
quantiles <- function(x) {
  quant <- quantile(x, probs = c(0.05, 0.25, 0.5, 0.75, 0.95))
  names(quant) <- c("ymin", "lower", "middle", "upper", "ymax")
  quant
}

outliers <- function(x) {
  return(x < quantile(x, 0.05) | x > quantile(x, 0.95))
}

Reproducibility

Timestamp

[1] "2025-04-05 18:05:52 UTC"

Session Info

─ Session info ───────────────────────────────────────────────────────────────
 setting  value
 version  R version 4.4.2 (2024-10-31)
 os       Ubuntu 24.04.1 LTS
 system   x86_64, linux-gnu
 ui       X11
 language (EN)
 collate  en_US.UTF-8
 ctype    en_US.UTF-8
 tz       Etc/UTC
 date     2025-04-05
 pandoc   3.6.3 @ /usr/bin/ (via rmarkdown)
 quarto   1.6.42 @ /usr/local/bin/quarto

─ Packages ───────────────────────────────────────────────────────────────────
 package           * version     date (UTC) lib source
 backports           1.5.0       2024-05-23 [1] RSPM
 brio                1.1.5       2024-04-24 [1] RSPM
 broom               1.0.8       2025-03-28 [1] RSPM
 checkmate           2.3.2       2024-07-29 [1] RSPM
 cli                 3.6.4       2025-02-13 [1] RSPM
 codetools           0.2-20      2024-03-31 [2] CRAN (R 4.4.2)
 colorspace          2.1-1       2024-07-26 [1] RSPM
 curl                6.2.2       2025-03-24 [1] RSPM
 digest              0.6.37      2024-08-19 [1] RSPM
 dplyr             * 1.1.4       2023-11-17 [1] RSPM
 evaluate            1.0.3       2025-01-10 [1] RSPM
 farver              2.1.2       2024-05-13 [1] RSPM
 fastmap             1.2.0       2024-05-15 [1] RSPM
 formatters        * 0.5.10.9004 2025-04-05 [1] https://p~
 generics            0.1.3       2022-07-05 [1] RSPM
 ggplot2           * 3.5.1       2024-04-23 [1] RSPM
 glue                1.8.0       2024-09-30 [1] RSPM
 gtable              0.3.6       2024-10-25 [1] RSPM
 htmltools           0.5.8.1     2024-04-04 [1] RSPM
 htmlwidgets         1.6.4       2023-12-06 [1] RSPM
 jsonlite            2.0.0       2025-03-27 [1] RSPM
 knitr               1.50        2025-03-16 [1] RSPM
 labeling            0.4.3       2023-08-29 [1] RSPM
 lattice             0.22-7      2025-04-02 [1] RSPM
 lifecycle           1.0.4       2023-11-07 [1] RSPM
 magrittr          * 2.0.3       2022-03-30 [1] RSPM
 Matrix              1.7-3       2025-03-11 [1] CRAN (R 4.4.2)
 munsell             0.5.1       2024-04-01 [1] RSPM
 nestcolor         * 0.1.3.9000  2025-04-05 [1] https://p~
 pillar              1.10.2      2025-04-05 [1] CRAN (R 4.4.2)
 pkgcache            2.2.3       2024-09-12 [1] RSPM
 pkgconfig           2.0.3       2019-09-22 [1] RSPM
 processx            3.8.6       2025-02-21 [1] RSPM
 ps                  1.9.0       2025-02-18 [1] RSPM
 purrr               1.0.4       2025-02-05 [1] RSPM
 R6                  2.6.1       2025-02-15 [1] RSPM
 random.cdisc.data   0.3.16.9002 2025-04-05 [1] https://p~
 rbibutils           2.3         2024-10-04 [1] RSPM
 Rdpack              2.6.3       2025-03-16 [1] RSPM
 rlang               1.1.5       2025-01-17 [1] RSPM
 rmarkdown           2.29        2024-11-04 [1] RSPM
 rtables           * 0.6.11.9017 2025-04-05 [1] https://p~
 scales              1.3.0       2023-11-28 [1] RSPM
 sessioninfo         1.2.3       2025-02-05 [1] any (@1.2.3)
 stringi             1.8.7       2025-03-27 [1] RSPM
 stringr             1.5.1       2023-11-14 [1] RSPM
 survival            3.8-3       2024-12-17 [2] CRAN (R 4.4.2)
 tern              * 0.9.7.9017  2025-04-05 [1] https://p~
 testthat            3.2.3       2025-01-13 [1] RSPM
 tibble              3.2.1       2023-03-20 [1] RSPM
 tidyr             * 1.3.1       2024-01-24 [1] RSPM
 tidyselect          1.2.1       2024-03-11 [1] RSPM
 vctrs               0.6.5       2023-12-01 [1] RSPM
 withr               3.0.2       2024-10-28 [1] RSPM
 xfun                0.52        2025-04-02 [1] RSPM
 yaml                2.3.10      2024-07-26 [1] RSPM

 [1] /usr/local/lib/R/site-library
 [2] /usr/local/lib/R/library
 [3] /github/home/R/x86_64-pc-linux-gnu-library/4.4
 * ── Packages attached to the search path.

──────────────────────────────────────────────────────────────────────────────

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