Spaghetti Plot
tm_g_gh_spaghettiplot.RdThis teal module renders the UI and calls the function that creates a spaghetti plot.
Usage
tm_g_gh_spaghettiplot(
label,
dataname,
param_var,
param,
param_var_label = "PARAM",
idvar,
xaxis_var,
yaxis_var,
xaxis_var_level = NULL,
filter_var = yaxis_var,
trt_group,
trt_group_level = NULL,
group_stats = "NONE",
man_color = NULL,
color_comb = NULL,
xtick = ggplot2::waiver(),
xlabel = xtick,
rotate_xlab = FALSE,
facet_ncol = 2,
plot_height = c(600, 200, 2000),
plot_width = NULL,
font_size = c(12, 8, 20),
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,
pre_output = NULL,
post_output = NULL
)Arguments
- label
menu item label of the module in the teal app.
- dataname
analysis data passed to the data argument of teal init. E.g. ADaM structured laboratory data frame ADLB.
- param_var
name of variable containing biomarker codes e.g. PARAMCD.
- param
biomarker selected.
- param_var_label
single name of variable in analysis data that includes parameter labels.
- idvar
name of unique subject id variable.
- xaxis_var
single name of variable in analysis data that is used as x-axis in the plot for the respective goshawk function.
- yaxis_var
single name of variable in analysis data that is used as summary variable in the respective gshawk function.
- xaxis_var_level
vector that can be used to define the factor level of xaxis_var. Only use it when xaxis_var is character or factor.
- filter_var
data constraint variable.
- trt_group
choices_selectedobject with available choices and pre-selected option for variable names representing treatment group e.g. ARM.- trt_group_level
vector that can be used to define factor level of trt_group.
- group_stats
control group mean or median overlay.
- man_color
string vector representing customized colors
- color_comb
name or hex value for combined treatment color.
- xtick
numeric vector to define the tick values of x-axis when x variable is numeric. Default value is waive().
- xlabel
vector with same length of xtick to define the label of x-axis tick values. Default value is waive().
- rotate_xlab
boolean value indicating whether to rotate x-axis labels
- facet_ncol
numeric value indicating number of facets per row.
- plot_height
controls plot height.
- plot_width
optional, controls plot width.
- font_size
control font size for title, x-axis, y-axis and legend font.
- hline_arb
numeric vector of at most 2 values identifying intercepts for arbitrary horizontal lines.
- hline_arb_color
a character vector of at most length of
hline_arb. naming the color for the arbitrary horizontal lines.- hline_arb_label
a character vector of at most length of
hline_arb. naming the label for the arbitrary horizontal lines.- hline_vars
a character vector to name the columns that will define additional horizontal lines.
- hline_vars_colors
a character vector naming the colors for the additional horizontal lines.
- hline_vars_labels
a character vector naming the labels for the additional horizontal lines that will appear in the legend.
- pre_output
(
shiny.tag, optional)
with text placed before the output to put the output into context. For example a title.- post_output
(
shiny.tag, optional) with text placed after the output to put the output into context. For example theshiny::helpText()elements are useful.
Examples
# Example using ADaM structure analysis dataset.
library(dplyr)
library(scda)
# original ARM value = dose value
arm_mapping <- list(
"A: Drug X" = "150mg QD",
"B: Placebo" = "Placebo",
"C: Combination" = "Combination"
)
set.seed(1)
ADSL <- synthetic_cdisc_data("latest")$adsl
ADLB <- synthetic_cdisc_data("latest")$adlb
var_labels <- lapply(ADLB, function(x) attributes(x)$label)
ADLB <- ADLB %>%
dplyr::mutate(
AVISITCD = dplyr::case_when(
AVISIT == "SCREENING" ~ "SCR",
AVISIT == "BASELINE" ~ "BL",
grepl("WEEK", AVISIT) ~ paste("W", stringr::str_extract(AVISIT, "(?<=(WEEK ))[0-9]+")),
TRUE ~ as.character(NA)
),
AVISITCDN = dplyr::case_when(
AVISITCD == "SCR" ~ -2,
AVISITCD == "BL" ~ 0,
grepl("W", AVISITCD) ~ as.numeric(gsub("[^0-9]*", "", AVISITCD)),
TRUE ~ as.numeric(NA)
),
AVISITCD = factor(AVISITCD) %>% reorder(AVISITCDN),
TRTORD = dplyr::case_when(
ARMCD == "ARM C" ~ 1,
ARMCD == "ARM B" ~ 2,
ARMCD == "ARM A" ~ 3
),
ARM = as.character(arm_mapping[match(ARM, names(arm_mapping))]),
ARM = factor(ARM) %>% reorder(TRTORD),
ACTARM = as.character(arm_mapping[match(ACTARM, names(arm_mapping))]),
ACTARM = factor(ACTARM) %>% reorder(TRTORD),
ANRLO = 30,
ANRHI = 75
) %>%
dplyr::rowwise() %>%
dplyr::group_by(PARAMCD) %>%
dplyr::mutate(LBSTRESC = ifelse(USUBJID %in% sample(USUBJID, 1, replace = TRUE),
paste("<", round(runif(1, min = 25, max = 30))), LBSTRESC
)) %>%
dplyr::mutate(LBSTRESC = ifelse(USUBJID %in% sample(USUBJID, 1, replace = TRUE),
paste(">", round(runif(1, min = 70, max = 75))), LBSTRESC
)) %>%
ungroup()
attr(ADLB[["ARM"]], "label") <- var_labels[["ARM"]]
attr(ADLB[["ACTARM"]], "label") <- var_labels[["ACTARM"]]
attr(ADLB[["ANRLO"]], "label") <- "Analysis Normal Range Lower Limit"
attr(ADLB[["ANRHI"]], "label") <- "Analysis Normal Range Upper Limit"
# add LLOQ and ULOQ variables
ALB_LOQS <- goshawk:::h_identify_loq_values(ADLB)
ADLB <- left_join(ADLB, ALB_LOQS, by = "PARAM")
app <- teal::init(
data = cdisc_data(
cdisc_dataset("ADSL", ADSL, code = "ADSL <- synthetic_cdisc_data(\"latest\")$adsl"),
cdisc_dataset(
"ADLB",
ADLB,
code = "set.seed(1)
ADLB <- synthetic_cdisc_data(\"latest\")$adlb
var_labels <- lapply(ADLB, function(x) attributes(x)$label)
ADLB <- ADLB %>%
dplyr::mutate(AVISITCD = dplyr::case_when(
AVISIT == 'SCREENING' ~ 'SCR',
AVISIT == 'BASELINE' ~ 'BL',
grepl('WEEK', AVISIT) ~
paste('W', stringr::str_extract(AVISIT, '(?<=(WEEK ))[0-9]+')),
TRUE ~ as.character(NA)),
AVISITCDN = dplyr::case_when(
AVISITCD == 'SCR' ~ -2,
AVISITCD == 'BL' ~ 0,
grepl('W', AVISITCD) ~ as.numeric(gsub('[^0-9]*', '', AVISITCD)),
TRUE ~ as.numeric(NA)),
AVISITCD = factor(AVISITCD) %>% reorder(AVISITCDN),
TRTORD = dplyr::case_when(
ARMCD == 'ARM C' ~ 1,
ARMCD == 'ARM B' ~ 2,
ARMCD == 'ARM A' ~ 3),
ARM = as.character(arm_mapping[match(ARM, names(arm_mapping))]),
ARM = factor(ARM) %>% reorder(TRTORD),
ACTARM = as.character(arm_mapping[match(ACTARM, names(arm_mapping))]),
ACTARM = factor(ACTARM) %>% reorder(TRTORD),
ANRLO = 30,
ANRHI = 75) %>%
dplyr::rowwise() %>%
dplyr::group_by(PARAMCD) %>%
dplyr::mutate(LBSTRESC = ifelse(USUBJID %in% sample(USUBJID, 1, replace = TRUE),
paste('<', round(runif(1, min = 25, max = 30))), LBSTRESC)) %>%
dplyr::mutate(LBSTRESC = ifelse(USUBJID %in% sample(USUBJID, 1, replace = TRUE),
paste( '>', round(runif(1, min = 70, max = 75))), LBSTRESC)) %>%
ungroup
attr(ADLB[['ARM']], 'label') <- var_labels[['ARM']]
attr(ADLB[['ACTARM']], 'label') <- var_labels[['ACTARM']]
attr(ADLB[['ANRLO']], 'label') <- 'Analysis Normal Range Lower Limit'
attr(ADLB[['ANRHI']], 'label') <- 'Analysis Normal Range Upper Limit'
ALB_LOQS <- goshawk:::h_identify_loq_values(ADLB)
ADLB <- left_join(ADLB, ALB_LOQS, by = 'PARAM')",
vars = list(arm_mapping = arm_mapping)
),
check = FALSE
),
modules = modules(
tm_g_gh_spaghettiplot(
label = "Spaghetti Plot",
dataname = "ADLB",
param_var = "PARAMCD",
param = choices_selected(c("ALT", "CRP", "IGA"), "ALT"),
idvar = "USUBJID",
xaxis_var = choices_selected(c("Analysis Visit Code" = "AVISITCD"), "AVISITCD"),
yaxis_var = choices_selected(c("AVAL", "CHG", "PCHG"), "AVAL"),
filter_var = choices_selected(
c("None" = "NONE", "Screening" = "BASE2", "Baseline" = "BASE"),
"NONE"
),
trt_group = choices_selected(c("ARM", "ACTARM"), "ARM"),
color_comb = "#39ff14",
man_color = c(
"Combination" = "#000000",
"Placebo" = "#fce300",
"150mg QD" = "#5a2f5f"
),
hline_arb = c(60, 50),
hline_arb_color = c("grey", "red"),
hline_arb_label = c("default A", "default B"),
hline_vars = c("ANRHI", "ANRLO", "ULOQN", "LLOQN"),
hline_vars_colors = c("pink", "brown", "purple", "black"),
)
)
)
#> [INFO] 2022-10-19 12:20:03.2175 pid:1931 token:[] teal.goshawk Initializing tm_g_gh_spaghettiplot
if (FALSE) {
shinyApp(app$ui, app$server)
}