Function to create a spaghetti plot. — g

This function is rendered by teal.goshawk module

Usage

g_spaghettiplot(
  data,
  subj_id = "USUBJID",
  biomarker_var = "PARAMCD",
  biomarker_var_label = "PARAM",
  biomarker,
  value_var = "AVAL",
  unit_var = "AVALU",
  trt_group,
  trt_group_level = NULL,
  time,
  time_level = NULL,
  color_manual = NULL,
  color_comb = "#39ff14",
  ylim = c(NA, NA),
  alpha = 1,
  facet_ncol = 2,
  facet_scales = c("fixed", "free", "free_x", "free_y"),
  xtick = ggplot2::waiver(),
  xlabel = xtick,
  rotate_xlab = FALSE,
  font_size = 12,
  group_stats = "NONE",
  hline_arb = numeric(0),
  hline_arb_color = "red",
  hline_arb_label = "Horizontal line",
  hline_vars = character(0),
  hline_vars_colors = "green",
  hline_vars_labels = hline_vars
)

Arguments

data: data frame with variables to be summarized and generate statistics which will display in the plot.
subj_id: unique subject id variable name.
biomarker_var: name of variable containing biomarker names.
biomarker_var_label: name of variable containing biomarker labels.
biomarker: biomarker name to be analyzed.
value_var: name of variable containing biomarker results.
unit_var: name of variable containing biomarker units.
trt_group: name of variable representing treatment group.
trt_group_level: vector that can be used to define the factor level of trt_group.
time: name of variable containing visit names.
time_level: vector that can be used to define the factor level of time. Only use it when x-axis variable is character or factor.
color_manual: vector of colors.
color_comb: name or hex value for combined treatment color.
ylim: ('numeric vector') optional, a vector of length 2 to specify the minimum and maximum of the y-axis if the default limits are not suitable.
alpha: subject line transparency (0 = transparent, 1 = opaque)
facet_ncol: number of facets per row.
facet_scales: passed to scales in ggplot2::facet_wrap. Should scales be fixed ("fixed", the default), free ("free"), or free in one dimension ("free_x", "free_y")?
xtick: a vector to define the tick values of time in x-axis. Default value is ggplot2::waiver().
xlabel: vector with same length of xtick to define the label of x-axis tick values. Default value is ggplot2::waiver().
rotate_xlab: boolean whether to rotate x-axis labels.
font_size: control font size for title, x-axis, y-axis and legend font.
group_stats: control group mean or median overlay.
hline_arb: ('numeric vector') value identifying intercept for arbitrary horizontal lines.
hline_arb_color: ('character vector') optional, color for the arbitrary horizontal lines.
hline_arb_label: ('character vector') optional, label for the legend to the arbitrary horizontal lines.
hline_vars: ('character vector'), names of variables (ANR*) or values (*LOQ) identifying intercept values. The data inside of the ggplot2 object must also contain the columns with these variable names
hline_vars_colors: ('character vector') colors for the horizontal lines defined by variables.
hline_vars_labels: ('character vector') labels for the legend to the horizontal lines defined by variables.

Value

ggplot object

Author

Wenyi Liu (wenyi.liu@roche.com)

Examples


# Example using ADaM structure analysis dataset.

library(stringr)

# original ARM value = dose value
arm_mapping <- list(
  "A: Drug X" = "150mg QD", "B: Placebo" = "Placebo", "C: Combination" = "Combination"
)
color_manual <- c("150mg QD" = "#000000", "Placebo" = "#3498DB", "Combination" = "#E74C3C")

ADLB <- goshawk::rADLB
var_labels <- lapply(ADLB, function(x) attributes(x)$label)
ADLB <- ADLB %>%
  mutate(AVISITCD = case_when(
    AVISIT == "SCREENING" ~ "SCR",
    AVISIT == "BASELINE" ~ "BL",
    grepl("WEEK", AVISIT) ~
      paste(
        "W",
        trimws(
          substr(
            AVISIT,
            start = 6,
            stop = str_locate(AVISIT, "DAY") - 1
          )
        )
      ),
    TRUE ~ NA_character_
  )) %>%
  mutate(AVISITCDN = case_when(
    AVISITCD == "SCR" ~ -2,
    AVISITCD == "BL" ~ 0,
    grepl("W", AVISITCD) ~ as.numeric(gsub("\\D+", "", AVISITCD)),
    TRUE ~ NA_real_
  )) %>%
  # use ARMCD values to order treatment in visualization legend
  mutate(TRTORD = ifelse(grepl("C", ARMCD), 1,
    ifelse(grepl("B", ARMCD), 2,
      ifelse(grepl("A", ARMCD), 3, NA)
    )
  )) %>%
  mutate(ARM = as.character(arm_mapping[match(ARM, names(arm_mapping))])) %>%
  mutate(ARM = factor(ARM) %>%
    reorder(TRTORD)) %>%
  mutate(ANRLO = .5, ANRHI = 1) %>%
  rowwise() %>%
  group_by(PARAMCD) %>%
  mutate(LBSTRESC = ifelse(USUBJID %in% sample(USUBJID, 1, replace = TRUE),
    paste("<", round(runif(1, min = .5, max = .7))), LBSTRESC
  )) %>%
  mutate(LBSTRESC = ifelse(USUBJID %in% sample(USUBJID, 1, replace = TRUE),
    paste(">", round(runif(1, min = .9, max = 1.2))), LBSTRESC
  )) %>%
  ungroup()
attr(ADLB[["ARM"]], "label") <- var_labels[["ARM"]]
attr(ADLB[["ANRLO"]], "label") <- "Analysis Normal Range Lower Limit"
attr(ADLB[["ANRHI"]], "label") <- "Analysis Normal Range Upper Limit"

# add LLOQ and ULOQ variables
ADLB_LOQS <- goshawk:::h_identify_loq_values(ADLB)
ADLB <- left_join(ADLB, ADLB_LOQS, by = "PARAM")

g_spaghettiplot(
  data = ADLB,
  subj_id = "USUBJID",
  biomarker_var = "PARAMCD",
  biomarker = "CRP",
  value_var = "AVAL",
  trt_group = "ARM",
  time = "AVISITCD",
  color_manual = color_manual,
  color_comb = "#39ff14",
  alpha = .02,
  xtick = c("BL", "W 1", "W 4"),
  xlabel = c("Baseline", "Week 1", "Week 4"),
  rotate_xlab = FALSE,
  group_stats = "median",
  hline_vars = c("ANRHI", "ANRLO"),
  hline_vars_colors = c("pink", "brown")
)


g_spaghettiplot(
  data = ADLB,
  subj_id = "USUBJID",
  biomarker_var = "PARAMCD",
  biomarker = "CRP",
  value_var = "AVAL",
  trt_group = "ARM",
  time = "AVISITCD",
  color_manual = color_manual,
  color_comb = "#39ff14",
  alpha = .02,
  xtick = c("BL", "W 1", "W 4"),
  xlabel = c("Baseline", "Week 1", "Week 4"),
  rotate_xlab = FALSE,
  group_stats = "median",
  hline_arb = 1.3,
  hline_vars = c("ANRHI", "ANRLO", "ULOQN", "LLOQN"),
  hline_vars_colors = c("pink", "brown", "purple", "gray")
)


g_spaghettiplot(
  data = ADLB,
  subj_id = "USUBJID",
  biomarker_var = "PARAMCD",
  biomarker = "CRP",
  value_var = "AVAL",
  trt_group = "ARM",
  time = "AVISITCDN",
  color_manual = color_manual,
  color_comb = "#39ff14",
  alpha = .02,
  xtick = c(0, 1, 4),
  xlabel = c("Baseline", "Week 1", "Week 4"),
  rotate_xlab = FALSE,
  group_stats = "median",
  hline_arb = c(.5, .7, 1),
  hline_arb_color = c("blue", "red", "green"),
  hline_arb_label = c("Arb_Hori_line_A", "Arb_Hori_line_B", "Arb_Hori_line_C"),
  hline_vars = c("ANRHI", "ANRLO")
)


# removing missing levels from the plot with facet_scales

g_spaghettiplot(
  data = ADLB,
  subj_id = "USUBJID",
  biomarker_var = "PARAMCD",
  biomarker = "CRP",
  value_var = "AVAL",
  trt_group = "ARM",
  time = "RACE",
  color_manual = color_manual,
  color_comb = "#39ff14",
  alpha = .02,
  facet_scales = "fixed",
  rotate_xlab = FALSE,
  group_stats = "median",
  hline_arb = c(.5, .7, 1),
  hline_arb_color = c("blue", "red", "green"),
  hline_arb_label = c("Arb_Hori_line_A", "Arb_Hori_line_B", "Arb_Hori_line_C"),
  hline_vars = c("ANRHI", "ANRLO")
)


g_spaghettiplot(
  data = ADLB,
  subj_id = "USUBJID",
  biomarker_var = "PARAMCD",
  biomarker = "CRP",
  value_var = "AVAL",
  trt_group = "ARM",
  time = "RACE",
  color_manual = color_manual,
  color_comb = "#39ff14",
  alpha = .02,
  facet_scales = "free_x",
  rotate_xlab = FALSE,
  group_stats = "median",
  hline_arb = c(.5, .7, 1),
  hline_arb_color = c("blue", "red", "green"),
  hline_arb_label = c("Arb_Hori_line_A", "Arb_Hori_line_B", "Arb_Hori_line_C"),
  hline_vars = c("ANRHI", "ANRLO")
)