Usage
tm_g_scatterplot(
label,
mae_name,
exclude_assays = "counts",
summary_funs = list(Mean = colMeans, Median = matrixStats::colMedians, Max =
matrixStats::colMaxs),
pre_output = NULL,
post_output = NULL
)
ui_g_scatterplot(id, mae_name, summary_funs, pre_output, post_output)
srv_g_scatterplot(
id,
data,
filter_panel_api,
reporter,
mae_name,
exclude_assays,
summary_funs
)
sample_tm_g_scatterplot()
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
list
of functions orNULL
)
functions which can be used in the the gene signatures. For modules that support also multiple genes without summary,NULL
can be included to not summarize the genes but provide all of them.- pre_output
(
shiny.tag
orNULL
)
placed before the output to put the output into context (for example a title).- post_output
(
shiny.tag
orNULL
)
placed after the output to put the output into context (for example theshiny::helpText()
elements can be useful).- 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_scatterplot()
: sets up the user interface.srv_g_scatterplot()
: sets up the server with reactive graph.sample_tm_g_scatterplot()
: sample module function.
Examples
data <- teal_data(MAE = hermes::multi_assay_experiment)
app <- init(
data = data,
modules = modules(
tm_g_scatterplot(
label = "scatterplot",
mae_name = "MAE"
)
)
)
#> [INFO] 2024-02-13 21:31:45.6658 pid:1218 token:[] teal.modules.hermes Initializing tm_g_scatterplot
if (interactive()) {
shinyApp(app$ui, app$server)
}
# Alternatively you can run the sample module with this function call:
if (interactive()) {
sample_tm_g_scatterplot()
}