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Line plot

tm_g_gh_lineplot.Rd

This teal module renders the UI and calls the function that creates a line plot.

Usage 

tm_g_gh_lineplot(
  label,
  dataname,
  param_var,
  param,
  param_var_label = "PARAM",
  xaxis_var,
  yaxis_var,
  xvar_level = NULL,
  filter_var = yaxis_var,
  filter_var_choices = filter_var,
  trt_group,
  trt_group_level = NULL,
  shape_choices = NULL,
  stat = "mean",
  hline_arb = numeric(0),
  hline_arb_color = "red",
  hline_arb_label = "Horizontal line",
  color_manual = c(getOption("ggplot2.discrete.colour"), c("#ff0000", "#008000",
    "#4ca3dd", "#8a2be2"))[1:4],
  xtick = ggplot2::waiver(),
  xlabel = xtick,
  rotate_xlab = FALSE,
  plot_height = c(600, 200, 4000),
  plot_width = NULL,
  plot_font_size = c(12, 8, 20),
  dodge = c(0.4, 0, 1),
  pre_output = NULL,
  post_output = NULL,
  count_threshold = 0,
  table_font_size = c(12, 4, 20),
  plot_relative_height_value = 1000
)

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.

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.

xvar_level

vector that can be used to define the factor level of xvar. Only use it when xvar is character or factor.

filter_var

data constraint variable.

filter_var_choices

data constraint variable choices.

trt_group

choices_selected object 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.

shape_choices

Vector or choices_selected object with names of ADSL variables which can be used to change shape

stat

string of statistics

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.

color_manual

string vector representing customized colors

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.

plot_height

controls plot height.

plot_width

optional, controls plot width.

plot_font_size

control font size for title, x-axis, y-axis and legend font.

dodge

controls the position dodge of error bar

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 the shiny::helpText() elements are useful.

count_threshold

minimum count of observations (as listed in the output table) to plot nodes on the graph

table_font_size

controls the font size of values in the table

plot_relative_height_value

numeric value between 500 and 5000 for controlling the starting value of the relative plot height slider

Value

shiny object

Author

Wenyi Liu (luiw2) wenyi.liu@roche.com

Balazs Toth (tothb2) toth.balazs@gene.com

Examples 


# Example using ADaM structure analysis dataset.

library(dplyr)
library(scda)
library(stringr)
library(nestcolor)

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

cached_data <- synthetic_cdisc_data("latest")
ADSL <- cached_data$adsl
ADLB <- cached_data$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)
  )
attr(ADLB[["ARM"]], "label") <- var_labels[["ARM"]]
attr(ADLB[["ACTARM"]], "label") <- var_labels[["ACTARM"]]

app <- teal::init(
  data = cdisc_data(
    adsl <- cdisc_dataset("ADSL", ADSL, code = "ADSL <- synthetic_cdisc_data(\"latest\")$adsl"),
    cdisc_dataset("ADLB", ADLB,
      code = "ADLB <- synthetic_cdisc_data(\"latest\")$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))
               attr(ADLB[['ARM']], 'label') <- var_labels[['ARM']]
               attr(ADLB[['ACTARM']], 'label') <- var_labels[['ACTARM']]",
      vars = list(ADSL = adsl, arm_mapping = arm_mapping)
    ),
    check = TRUE
  ),
  modules = modules(
    tm_g_gh_lineplot(
      label = "Line Plot",
      dataname = "ADLB",
      param_var = "PARAMCD",
      param = choices_selected(c("ALT", "CRP", "IGA"), "ALT"),
      shape_choices = c("SEX", "RACE"),
      xaxis_var = choices_selected("AVISITCD", "AVISITCD"),
      yaxis_var = choices_selected(c("AVAL", "BASE", "CHG", "PCHG"), "AVAL"),
      trt_group = choices_selected(c("ARM", "ACTARM"), "ARM"),
      hline_arb = c(20.5, 19.5),
      hline_arb_color = c("red", "green"),
      hline_arb_label = c("A", "B")
    )
  )
)
#> [INFO] 2022-10-19 12:19:50.9474 pid:1931 token:[] teal.goshawk Initializing tm_g_gh_lineplot
if (FALSE) {
shinyApp(app$ui, app$server)
}