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<!DOCTYPE html>
<html xmlns="http://www.w3.org/1999/xhtml" lang="en" xml:lang="en"><head>
<meta charset="utf-8">
<meta name="generator" content="quarto-1.1.189">
<meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes">
<title>Dynamic, Interactive Tables, Listings and Figures</title>
<style>
code{white-space: pre-wrap;}
span.smallcaps{font-variant: small-caps;}
div.columns{display: flex; gap: min(4vw, 1.5em);}
div.column{flex: auto; overflow-x: auto;}
div.hanging-indent{margin-left: 1.5em; text-indent: -1.5em;}
ul.task-list{list-style: none;}
ul.task-list li input[type="checkbox"] {
width: 0.8em;
margin: 0 0.8em 0.2em -1.6em;
vertical-align: middle;
}
</style>
<script src="dynamic-tlf_files/libs/clipboard/clipboard.min.js"></script>
<script src="dynamic-tlf_files/libs/quarto-html/quarto.js"></script>
<script src="dynamic-tlf_files/libs/quarto-html/popper.min.js"></script>
<script src="dynamic-tlf_files/libs/quarto-html/tippy.umd.min.js"></script>
<script src="dynamic-tlf_files/libs/quarto-html/anchor.min.js"></script>
<link href="dynamic-tlf_files/libs/quarto-html/tippy.css" rel="stylesheet">
<link href="dynamic-tlf_files/libs/quarto-html/quarto-syntax-highlighting.css" rel="stylesheet" id="quarto-text-highlighting-styles">
<script src="dynamic-tlf_files/libs/bootstrap/bootstrap.min.js"></script>
<link href="dynamic-tlf_files/libs/bootstrap/bootstrap-icons.css" rel="stylesheet">
<link href="dynamic-tlf_files/libs/bootstrap/bootstrap.min.css" rel="stylesheet" id="quarto-bootstrap" data-mode="light">
</head>
<body class="fullcontent">
<div class="page-layout-custom">
<header id="title-block-header" class="quarto-title-block default">
<div class="quarto-title">
<h1 class="title">Dynamic, Interactive Tables, Listings and Figures</h1>
</div>
<div class="quarto-title-meta">
</div>
</header>
<div class="grid">
<div class="g-col-2 w-100 p-2 mysidebar">
<div class="cell">
<div class="cell-output-display">
<div class="col-sm-12" align="center">
<p>Choose variables for the anchor table then click Make Table</p>
<hr>
<div id="treat_vars_ui" class="shiny-html-output"></div>
<br>
<div id="count_vars_ui" class="shiny-html-output"></div>
<br>
<div id="numeric_vars_ui" class="shiny-html-output"></div>
<br>
<button id="go" type="button" class="btn btn-default action-button" style="border-color: #E10033">Make Table</button>
<hr>
<p>
Next, click any
<span style="color:#E10033">result cell</span>
of the anchor table to view associated tables, listings and figures for that subset associated on the right.
</p>
</div>
</div>
</div>
</div>
<div class="g-col-5 w-100 p-2">
<div class="panel-tabset">
<ul class="nav nav-tabs" role="tablist"><li class="nav-item" role="presentation"><a class="nav-link active" id="tabset-1-1-tab" data-bs-toggle="tab" data-bs-target="#tabset-1-1" role="tab" aria-controls="tabset-1-1" aria-selected="true" href="">Anchor Table</a></li></ul>
<div class="tab-content">
<div id="tabset-1-1" class="tab-pane active" role="tabpanel" aria-labelledby="tabset-1-1-tab">
<div class="cell">
<div class="cell-output-display">
<div id="anchor_table" class="reactable html-widget html-widget-output" style="width:auto; height:auto; " data-reactable-output="anchor_table"></div>
</div>
</div>
</div>
</div>
</div>
</div>
<div class="g-col-5 w-100 p-2">
<div class="panel-tabset">
<ul class="nav nav-tabs" role="tablist"><li class="nav-item" role="presentation"><a class="nav-link active" id="tabset-2-1-tab" data-bs-toggle="tab" data-bs-target="#tabset-2-1" role="tab" aria-controls="tabset-2-1" aria-selected="true" href="">Table</a></li><li class="nav-item" role="presentation"><a class="nav-link" id="tabset-2-2-tab" data-bs-toggle="tab" data-bs-target="#tabset-2-2" role="tab" aria-controls="tabset-2-2" aria-selected="false" href="">Figure</a></li><li class="nav-item" role="presentation"><a class="nav-link" id="tabset-2-3-tab" data-bs-toggle="tab" data-bs-target="#tabset-2-3" role="tab" aria-controls="tabset-2-3" aria-selected="false" href="">Listing 1</a></li><li class="nav-item" role="presentation"><a class="nav-link" id="tabset-2-4-tab" data-bs-toggle="tab" data-bs-target="#tabset-2-4" role="tab" aria-controls="tabset-2-4" aria-selected="false" href="">Listing 2</a></li></ul>
<div class="tab-content">
<div id="tabset-2-1" class="tab-pane active" role="tabpanel" aria-labelledby="tabset-2-1-tab">
<div class="cell">
<div class="cell-output-display">
<div id="ae_ctrl" class="shiny-html-output"></div>
</div>
<div class="cell-output-display">
<div id="ae" class="reactable html-widget html-widget-output" style="width:auto; height:auto; " data-reactable-output="ae"></div>
</div>
</div>
</div>
<div id="tabset-2-2" class="tab-pane" role="tabpanel" aria-labelledby="tabset-2-2-tab">
<div class="cell">
<div class="cell-output-display">
<div id="figure" style="width:100%; height:500px; " class="highchart html-widget html-widget-output"></div>
</div>
</div>
</div>
<div id="tabset-2-3" class="tab-pane" role="tabpanel" aria-labelledby="tabset-2-3-tab">
<div class="cell">
<div class="cell-output-display">
<div id="listing1_ctrl" class="shiny-html-output"></div>
</div>
<div class="cell-output-display">
<div id="listing" class="reactable html-widget html-widget-output" style="width:auto; height:auto; " data-reactable-output="listing"></div>
</div>
</div>
</div>
<div id="tabset-2-4" class="tab-pane" role="tabpanel" aria-labelledby="tabset-2-4-tab">
<div class="cell">
<div class="cell-output-display">
<div id="listing2_ctrl" class="shiny-html-output"></div>
</div>
<div class="cell-output-display">
<div id="listing2" class="reactable html-widget html-widget-output" style="width:auto; height:auto; " data-reactable-output="listing2"></div>
</div>
</div>
</div>
</div>
</div>
</div>
</div>
<div class="cell" data-context="server">
</div>
<div class="cell" data-context="server">
</div>
<div class="cell" data-context="server">
</div>
<div class="cell" data-context="server">
</div>
<div class="cell" data-context="server">
</div>
<div class="cell" data-context="server">
</div>
<div class="cell" data-context="server">
</div>
<div class="cell" data-context="server">
</div>
<p>
<script type="application/shiny-prerendered" data-context="server-start">
# libs
library(tidyverse)
library(haven)
library(reactable)
library(reactablefmtr)
library(highcharter)
library(Tplyr)
# data
adsl <- read_xpt(url("https://github.com/phuse-org/TestDataFactory/raw/main/Updated/TDF_ADaM/adsl.xpt"))
adae <- read_xpt(url("https://github.com/phuse-org/TestDataFactory/raw/main/Updated/TDF_ADaM/adae.xpt"))
advs <- read_xpt(url("https://github.com/phuse-org/TestDataFactory/raw/main/Updated/TDF_ADaM/advs.xpt"))
</script>
<script type="application/shiny-prerendered" data-context="server">
# This part of the server renders ui selectors for the grouping, frequency and numeric variables.
# It's done this way so in the future we can upload custom data - for now it's fixed using the adsl data set
output$treat_vars_ui <- renderUI({
selectInput("treat_vars",
"Group Variable",
multiple = FALSE,
selected = "TRT01A",
choices = names(Filter(is.character, adsl))
)
})
output$count_vars_ui <- renderUI({
selectInput("count_vars",
"Frequency Variables",
multiple = TRUE,
selected = c("SEX", "AGEGR1", "ETHNIC"),
choices = names(Filter(is.character, adsl))
)
})
output$numeric_vars_ui <- renderUI({
selectInput("numeric_vars",
"Numeric Variables",
multiple = TRUE,
selected = "BMIBL",
choices = names(Filter(is.numeric, adsl))
)
})
</script>
<script type="application/shiny-prerendered" data-context="server">
# This part of the server captures choices for each of the variables into separate reactives
# These reactives are then used in constructing the anchor table
treat_vars <- reactive({
input$treat_vars
})
count_vars <- reactive({
data.frame(vars = input$count_vars)
})
numeric_vars <- reactive({
data.frame(vars = input$numeric_vars)
})
</script>
<script type="application/shiny-prerendered" data-context="server">
# This part of the server creates the base anchor table using Tplyr
# We currently need at least one count and at least one numeric variable
# Specify anchor table
base_table <- reactive({
tplyr_table(adsl, !!sym(treat_vars())) %>%
# loop through count variables
(function(x) {
for (i in 1:nrow(count_vars())) {
x <- add_layer(
x,
group_count(!!sym(count_vars()$vars[[i]]),
b = !!count_vars()$vars[[i]]
) %>%
add_total_row(f_str("xxxx", n))
)
}
x
})() %>%
# loop through numeric variables
(function(x) {
for (i in 1:nrow(numeric_vars())) {
x <- add_layer(
x,
group_desc(!!sym(numeric_vars()$var[[i]]),
b = !!numeric_vars()$var[[i]]
)
)
}
x
})() %>%
# add the total arm
add_total_group()
}) %>%
bindEvent(input$go)
# Build anchor table, with Tplyr metadata
meta <- reactive({
req(base_table())
build(base_table(), metadata = TRUE) %>%
apply_row_masks(row_breaks = TRUE)
})
# Setup trackers for what cell users click (row + col = cell)
row <- reactive(meta()[input$row$index, 1]$row_id)
col <- reactive(input$col$column)
# Display anchor table using reactable
output$anchor_table <- renderReactable({
reactable(
meta() %>%
select(-starts_with("ord"), -row_id) %>%
relocate("var1_Total", .after = last_col()),
# this JS captures the cell coordinate into input$row, and input$col (row + col = cell)
onClick = JS("function(rowInfo, colInfo) {
if (window.Shiny) {
Shiny.setInputValue('row', { index: rowInfo.index + 1 })
Shiny.setInputValue('col', { column: colInfo.id })
}}"),
pagination = FALSE,
highlight = TRUE,
sortable = FALSE,
defaultColDef = colDef(
align = "center",
html = TRUE
),
style = list(fontSize = "0.5rem"),
columns = list(
row_label1 = colDef(
name = "",
align = "center"
),
row_label2 = colDef(
name = "",
align = "left"
)
)
)
})
</script>
<script type="application/shiny-prerendered" data-context="server">
# This part of the server tracks the cells that are clicked on the anchor table
# We use row + col coordinates of the clicked cell and funnel this to Tplyr::get_meta_subset()
# The result is a intermediary (reactive) data frame of participant ID's I use to construct additional tables, listings and figures (see line 246-248 for an example)
sub_data <- reactive({
# control
req(base_table(), row(), col())
tmp <- get_meta_subset(base_table(), row(), col())
tmp
})
</script>
<script type="application/shiny-prerendered" data-context="server">
# This part of the server creates the adverse events (ae) table
output$ae <- renderReactable({
# control
validate(need(nrow(sub_data()) > 0, "No data to display"))
# subset clicked data from adae
inp <- adae %>%
inner_join(sub_data(), by = c("USUBJID" = "USUBJID")) %>%
inner_join(adsl, by = c("USUBJID" = "USUBJID"))
# build ae table
t2 <- tplyr_table(inp, TRT01P) %>%
add_layer(
group_count(vars(AEBODSYS, AEDECOD))
) %>%
build()
# light post processing on content
t2 <- t2 %>%
mutate(
row_label2 = stringr::str_to_title(row_label2),
row_label1 = stringr::str_to_title(row_label1)
) %>%
# make cells hyperlinkable to Medline
mutate(prep = stringr::str_replace_all(row_label2, " ", " ")) %>%
mutate(prep = glue::glue('<a href="https://vsearch.nlm.nih.gov/vivisimo/cgi-bin/query-meta?v%3Aproject=medlineplus&v%3Asources=medlineplus-bundle&query={prep}" target="_blank">{prep}<\u002fa>')) %>%
select(row_label1, prep, starts_with("var"))
# display ae table
t2 %>%
reactable(.,
elementId = "ae",
width = "auto",
groupBy = c("row_label1"),
pagination = FALSE,
highlight = TRUE,
sortable = FALSE,
compact = TRUE,
searchable = TRUE,
defaultColDef = colDef(
align = "left",
html = TRUE
),
style = list(fontSize = "0.5rem"),
columns = list(
row_label1 = colDef(
name = "System Organ Class"
),
prep = colDef(
name = "System Organ Class<br> Preferred Term"
)
)
)
})
# Create button to expand all nested terms
output$ae_ctrl <- renderUI({
# control
validate(need(nrow(sub_data()) > 0, "No data to display"))
# create action button for expand/collapse SOCs -> PTs
actionButton("expand", "Expand Terms",
style = "border-color: #E10033",
class = "btn btn-secondary btn-sm",
onclick = "Reactable.toggleAllRowsExpanded('ae')"
)
})
</script>
<script type="application/shiny-prerendered" data-context="server">
# This part of the server creates the adverse events (ae) drill down figure
output$figure <- renderHighchart({
# control
validate(need(nrow(sub_data()) > 0, "No data to display"))
# modify existing theme - this is fairly close to lux :D
my_theme <- hc_theme_bloom()
my_theme$drilldown$activeAxisLabelStyle$color <- "00FF00"
# start computations (AEBODSYS is SOC)
top_socs <- adae %>%
inner_join(sub_data(), by = c("USUBJID" = "USUBJID")) %>%
count(AEBODSYS, sort = TRUE) %>%
slice(1:4)
# get PT data (AEDECOD is PT)
pt_data <- adae %>%
inner_join(top_socs) %>%
select(AEBODSYS, AEDECOD, AESEV)
# calc PTs per SOC
pt_calc <- pt_data %>%
group_by(AEBODSYS) %>%
count(AEDECOD, sort = TRUE) %>%
ungroup()
# keep only top 10 PTs
pt_calc <- pt_calc %>%
arrange(AEBODSYS, desc(n)) %>%
group_by(AEBODSYS) %>%
slice(1:10)
# order the data for the sub-graph
# we want the PTs with the highest overall count (i.e. across severity) to show in descending order
sev_calc <- pt_calc %>%
inner_join(pt_data %>%
select(AEBODSYS, AEDECOD, AESEV)) %>%
count(AEBODSYS, AEDECOD, AESEV) %>%
group_by(AEDECOD) %>%
mutate(order = sum(n)) %>%
ungroup() %>%
arrange(desc(order)) %>%
select(-order)
# sub graph (2nd level)
pt_graph <- sev_calc %>%
group_nest(AEBODSYS) %>%
mutate(
id = AEBODSYS,
type = "column",
data = map(data,
mutate,
name = AEDECOD, y = n,
color = colorize(AESEV, colors = c("#000000", "#767676", "#E4E4E4"))
),
data = map(data, list_parse)
)
# main graph (1st level)
hchart(top_socs,
"column",
colorByPoint = TRUE,
hcaes(x = AEBODSYS, y = n, drilldown = AEBODSYS)
) %>%
hc_drilldown(
allowPointsDrillDown = F,
series = c(list_parse(pt_graph))
) %>%
hc_add_theme(my_theme) %>%
hc_xAxis(title = list(text = "System Organ Class → Preferred Term")) %>%
# custom JS for the hovering on the drill down bar chart!
# this essentially acts as a compact legend :)
# the JS conditional below specifies a different legend for 1st and 2nd levels of the chart
hc_tooltip(formatter = JS("function(){
if(this.point.AEDECOD === undefined) {
return ('<b>Term:<\u002fb> ' +
this.point.AEBODSYS +
'<br> <b>Severity:<\u002fb> ' +
'All Severity' +
'<br> <b>Count:<\u002fb> ' +
this.point.n)
} else {
return ('<b>Term:<\u002fb> ' +
this.point.AEDECOD +
'<br> <b>Severity:<\u002fb> ' +
this.point.AESEV +
'<br> <b>Count:<\u002fb> ' +
this.point.n)
}}"))
})
</script>
<script type="application/shiny-prerendered" data-context="server">
# This part of the server creates patient listing 1
output$listing <- renderReactable({
# control
validate(need(nrow(sub_data()) > 0, "No data to display"))
# subset clicked data from adsl (completer flags)
# perform some recoding of completer flag variables
listing_data <- sub_data() %>%
left_join(adsl) %>%
select(USUBJID, ARM, COMP8FL, COMP16FL, COMP24FL) %>%
# isn't it awesome we can do things like this?!
mutate(across(ends_with("FL"),
.fns = ~ case_when(
. == "N" ~ "❌ No",
. == "Y" ~ "✅ Yes",
TRUE ~ "⚠️ Unknown"
)
))
# display patient listing 1
listing_data %>%
reactable(.,
width = "auto",
highlight = TRUE,
filterable = TRUE,
defaultPageSize = 10,
sortable = FALSE,
searchable = TRUE,
compact = TRUE,
defaultColDef = colDef(
align = "center",
html = TRUE
),
columns = list(
COMP8FL = colDef(name = "8 Weeks"),
COMP16FL = colDef(name = "16 Weeks"),
COMP24FL = colDef(name = "24 Weeks")
),
columnGroups = list(
colGroup("Study Completion Milestone",
columns = c("COMP8FL", "COMP16FL", "COMP24FL")
)
),
style = list(fontSize = "0.5rem")
)
})
# Create download button control
output$listing1_ctrl <- renderUI({
# control
validate(need(nrow(sub_data()) > 0, "No data to display"))
# create action button for downloading
actionButton("dl", "Export CSV",
style = "border-color: #E10033",
class = "btn btn-secondary btn-sm",
onclick = "Reactable.downloadDataCSV('listing', 'listing.csv')"
)
})
</script>
<script type="application/shiny-prerendered" data-context="server">
# This part of the server creates patient listing 2
output$listing2 <- renderReactable({
# control
validate(
need(nrow(sub_data()) > 0, "No data to display"),
need(input$time, "Select an analysis time point"),
need(input$param, "Select a vital signs parameter")
)
# subset clicked data from advs (vital signs)
# dependent on shiny inputs (input$time, input$param), which are defined below
# note: not all participants in an anchor table necessarily have to have vital sign data!
listing_data2 <- sub_data() %>%
select(USUBJID) %>%
left_join(advs) %>%
select(USUBJID, AVISIT, PCHG, PARAM, ATPT) %>%
filter(
AVISIT == input$time,
PARAM == input$param
) %>%
pivot_wider(values_from = PCHG, names_from = ATPT, id_cols = USUBJID) %>%
select(USUBJID,
t1 = 3,
t3 = 4,
t5 = 2
) %>%
arrange(t1, t3, t5)
# display patient listing 2
# this part uses reactablefmtr to help draw data bars inside the reactable
listing_data2 %>%
reactable(.,
width = "auto",
pagination = TRUE,
defaultPageSize = 10,
highlight = TRUE,
style = list(fontSize = "0.5rem"),
defaultColDef = colDef(
align = "center",
cell = data_bars(listing_data2,
text_position = "above",
animation = "width 3s ease-out",
box_shadow = TRUE,
number_fmt = scales::label_percent(scale = 1),
fill_color = c("#E10033", "#767676")
)
),
columns = list(
t1 = colDef(name = "1 Minute"),
t3 = colDef(name = "3 Minute"),
t5 = colDef(name = "5 Minute")
),
columnGroups = list(
colGroup("% Change from Baseline by Measurement Time",
columns = c("t1", "t3", "t5")
)
)
)
})
# Create shiny inputs that control Vital Signs parameter and Visit
output$listing2_ctrl <- renderUI({
validate(need(nrow(sub_data()) > 0, "No data to display"))
# create two select inputs; one for blood pressure parameters, one for visit
tagList(
div(
style = "display: inline-block;vertical-align:top;",
selectInput("param",
"Vital Sign",
choices = c(
"DBP (mmHg)" = "Diastolic Blood Pressure (mmHg)",
"SBP (mmHg)" = "Systolic Blood Pressure (mmHg)"
)
)
),
div(
style = "display: inline-block;vertical-align:top;",
selectInput("time",
"Visit",
choices = unique(advs$AVISIT)[-1:-2]
)
)
)
})
</script>
<script type="application/shiny-prerendered" data-context="server-extras">
ojs_define <- function(..., .session = shiny::getDefaultReactiveDomain()) {
quos <- rlang::enquos(...)
vars <- rlang::list2(...)
nm <- names(vars)
if (is.null(nm)) {
nm <- rep_len("", length(vars))
}
mapply(function(q, nm, val) {
# Infer name, if possible
if (nm == "") {
tryCatch({
nm <- rlang::as_name(q)
}, error = function(e) {
code <- paste(collapse = "\n", deparse(rlang::f_rhs(q)))
stop("ojs_define() could not create a name for the argument: ", code)
})
}
.session$output[[nm]] <- val
outputOptions(.session$output, nm, suspendWhenHidden = FALSE)
.session$sendCustomMessage("ojs-export", list(name = nm))
NULL
}, quos, nm, vars, SIMPLIFY = FALSE, USE.NAMES = FALSE)
invisible()
}
</script>
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