Scatter Plot Teal Module For Biomarker Analysis

Scatter Plot Teal Module For Biomarker Analysis

Usage

tm_g_gh_correlationplot(
  label,
  dataname,
  param_var = "PARAMCD",
  xaxis_param = "ALT",
  xaxis_var = "BASE",
  yaxis_param = "CRP",
  yaxis_var = "AVAL",
  trt_group,
  color_manual = NULL,
  shape_manual = NULL,
  facet_ncol = 2,
  visit_facet = TRUE,
  trt_facet = FALSE,
  reg_line = FALSE,
  loq_legend = TRUE,
  rotate_xlab = FALSE,
  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,
  vline_arb = numeric(0),
  vline_arb_color = "red",
  vline_arb_label = "Vertical line",
  vline_vars = character(0),
  vline_vars_colors = "green",
  vline_vars_labels = vline_vars,
  plot_height = c(500, 200, 2000),
  plot_width = NULL,
  font_size = c(12, 8, 20),
  dot_size = c(1, 1, 12),
  reg_text_size = c(3, 3, 10),
  pre_output = NULL,
  post_output = NULL,
  transformators = list()
)

Arguments

label

menu item label of the module in the teal app.

dataname

analysis data passed to the data argument of init. E.g. ADaM structured laboratory data frame ADLB.

param_var

name of variable containing biomarker codes e.g. PARAMCD.

xaxis_param

biomarker selected for x-axis.

xaxis_var

name of variable containing biomarker results displayed on x-axis e.g. BASE.

yaxis_param

biomarker selected for y-axis.

yaxis_var

name of variable containing biomarker results displayed on y-axis e.g. AVAL.

trt_group

choices_selected object with available choices and pre-selected option for variable names representing treatment group e.g. ARM.

color_manual

vector of colors applied to treatment values.

shape_manual

vector of symbols applied to LOQ values.

facet_ncol

numeric value indicating number of facets per row.

visit_facet

visit facet toggle.

trt_facet

facet by treatment group trt_group.

reg_line

include regression line and annotations for slope and coefficient in visualization. Use with facet TRUE.

loq_legend

loq legend toggle.

rotate_xlab

45 degree rotation of x-axis values.

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

vline_arb

numeric vector of at most 2 values identifying intercepts for arbitrary horizontal lines.

vline_arb_color

a character vector of at most length of vline_arb. naming the color for the arbitrary horizontal lines.

vline_arb_label

a character vector of at most length of vline_arb. naming the label for the arbitrary horizontal lines.

vline_vars

a character vector to name the columns that will define additional vertical lines.

vline_vars_colors

a character vector naming the colors for the additional vertical lines.

vline_vars_labels

a character vector naming the labels for the additional vertical lines that will appear

plot_height

controls plot height.

plot_width

optional, controls plot width.

font_size

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

dot_size

plot dot size.

reg_text_size

font size control for regression line annotations.

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.

transformators

(list of teal_transform_module) that will be applied to transform module's data input. To learn more check vignette("transform-input-data", package = "teal").

Reporting

This module returns an object of class teal_module, that contains a server function. Since the server function returns a teal_report object, this makes this module reportable, which means that the reporting functionality will be turned on automatically by the teal framework.

For more information on reporting in teal, see the vignettes:

• vignette("reportable-shiny-application", package = "teal.reporter")

• vignette("adding-support-for-reporting-to-custom-modules", package = "teal")

Author

Nick Paszty (npaszty) paszty.nicholas@gene.com

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

Examples

# Example using ADaM structure analysis dataset.
data <- teal_data()
data <- within(data, {
  library(dplyr)
  library(stringr)

  # use non-exported function from goshawk
  .h_identify_loq_values <- getFromNamespace("h_identify_loq_values", "goshawk")

  # 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")
  # assign LOQ flag symbols: circles for "N" and triangles for "Y", squares for "NA"
  .shape_manual <- c("N" = 1, "Y" = 2, "NA" = 0)

  set.seed(1) # @linksto ADSL ADLB
  ADSL <- rADSL
  ADLB <- 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("[^0-9]*", "", 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(
      ANRHI = case_when(
        PARAMCD == "ALT" ~ 60,
        PARAMCD == "CRP" ~ 70,
        PARAMCD == "IGA" ~ 80,
        TRUE ~ NA_real_
      ),
      ANRLO = case_when(
        PARAMCD == "ALT" ~ 20,
        PARAMCD == "CRP" ~ 30,
        PARAMCD == "IGA" ~ 40,
        TRUE ~ NA_real_
      )
    ) %>%
    rowwise() %>%
    group_by(PARAMCD) %>%
    mutate(LBSTRESC = ifelse(
      USUBJID %in% sample(USUBJID, 1, replace = TRUE),
      paste("<", round(runif(1, min = 25, max = 30))), LBSTRESC
    )) %>%
    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[["ANRHI"]], "label") <- "Analysis Normal Range Upper Limit"
  attr(ADLB[["ANRLO"]], "label") <- "Analysis Normal Range Lower Limit"

  # add LLOQ and ULOQ variables
  ADLB_LOQS <- .h_identify_loq_values(ADLB, "LOQFL")
  ADLB <- left_join(ADLB, ADLB_LOQS, by = "PARAM")
})

join_keys(data) <- default_cdisc_join_keys[names(data)]

app <- init(
  data = data,
  modules = modules(
    tm_g_gh_correlationplot(
      label = "Correlation Plot",
      dataname = "ADLB",
      param_var = "PARAMCD",
      xaxis_param = choices_selected(c("ALT", "CRP", "IGA"), "ALT"),
      yaxis_param = choices_selected(c("ALT", "CRP", "IGA"), "CRP"),
      xaxis_var = choices_selected(c("AVAL", "BASE", "CHG", "PCHG"), "BASE"),
      yaxis_var = choices_selected(c("AVAL", "BASE", "CHG", "PCHG"), "AVAL"),
      trt_group = choices_selected(c("ARM", "ACTARM"), "ARM"),
      color_manual = c(
        "Drug X 100mg" = "#000000",
        "Placebo" = "#3498DB",
        "Combination 100mg" = "#E74C3C"
      ),
      shape_manual = c("N" = 1, "Y" = 2, "NA" = 0),
      plot_height = c(500, 200, 2000),
      facet_ncol = 2,
      visit_facet = TRUE,
      reg_line = FALSE,
      loq_legend = TRUE,
      font_size = c(12, 8, 20),
      dot_size = c(1, 1, 12),
      reg_text_size = c(3, 3, 10),
      hline_arb = c(40, 50),
      hline_arb_label = "arb hori label",
      hline_arb_color = c("red", "blue"),
      hline_vars = c("ANRHI", "ANRLO", "ULOQN", "LLOQN"),
      hline_vars_colors = c("green", "blue", "purple", "cyan"),
      hline_vars_labels = c("ANRHI Label", "ANRLO Label", "ULOQN Label", "LLOQN Label"),
      vline_vars = c("ANRHI", "ANRLO", "ULOQN", "LLOQN"),
      vline_vars_colors = c("yellow", "orange", "brown", "gold"),
      vline_vars_labels = c("ANRHI Label", "ANRLO Label", "ULOQN Label", "LLOQN Label"),
      vline_arb = c(50, 70),
      vline_arb_label = "arb vert A",
      vline_arb_color = c("green", "orange")
    )
  )
)
#> Initializing tm_g_gh_correlationplot
if (interactive()) {
  shinyApp(app$ui, app$server)
}