This module provides an interactive boxplot for RNA-seq gene expression analysis.
Usage
tm_g_boxplot(
label,
mae_name,
exclude_assays = character(),
summary_funs = list(None = NULL, Mean = colMeans, Median = matrixStats::colMedians, Max
= matrixStats::colMaxs),
pre_output = NULL,
post_output = NULL,
.test = FALSE,
transformators = list()
)
ui_g_boxplot(
id,
mae_name,
summary_funs,
pre_output,
post_output,
.test = FALSE
)
srv_g_boxplot(
id,
data,
filter_panel_api,
reporter,
mae_name,
exclude_assays,
summary_funs,
.test = FALSE
)
sample_tm_g_boxplot(.test = FALSE)Arguments
- label
(
string)
menu item label of the module in the teal app.- mae_name
(
string)
name of the MAE data used in the teal module.- exclude_assays
(
character)
names of the assays which should not be included in choices in the teal module.- summary_funs
(named
listof functions orNULL)
functions which can be used in the the gene signatures. For modules that support also multiple genes without summary,NULLcan be included to not summarize the genes but provide all of them.- pre_output
(
shiny.tagorNULL)
placed before the output to put the output into context (for example a title).- post_output
(
shiny.tagorNULL)
placed after the output to put the output into context (for example theshiny::helpText()elements can be useful).- .test
(
flag)
whether to display the internal structure of the plot for testing purposes.- transformators
(
listofteal_transform_module) that will be applied to transform module's data input. To learn more checkvignette("transform-input-data", package = "teal").- id
(
string) the shiny module id.- data
(
reactive)reactive(<teal_data>)holding all the data sets provided during app initialization after going through the filters.- filter_panel_api
(
FilterPanelAPI)
object describing the actual filter panel API.- reporter
(
Reporter) object
Functions
ui_g_boxplot(): sets up the user interface.srv_g_boxplot(): sets up the server with reactive graph.sample_tm_g_boxplot(): sample module function.
Examples
data <- teal_data(MAE = hermes::multi_assay_experiment)
app <- init(
data = data,
modules = modules(
tm_g_boxplot(
label = "boxplot",
mae_name = "MAE"
)
)
)
#> Initializing tm_g_boxplot
if (interactive()) {
shinyApp(app$ui, app$server)
}
# Alternatively you can run the sample module with this function call:
if (interactive()) {
sample_tm_g_boxplot()
}