geposanui/R/methods.R

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# Construct UI for the methods editor.
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methods_ui <- function(id) {
verticalLayout(
h3("Methods"),
div(style = "margin-top: 16px"),
lapply(methods, function(method) {
verticalLayout(
checkboxInput(
NS(id, method$id),
span(
method$description,
style = "font-weight: bold"
),
value = TRUE
),
sliderInput(
NS(id, sprintf("%s_weight", method$id)),
NULL,
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min = -1.0,
max = 1.0,
step = 0.01,
value = 1.0
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)
)
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}),
radioButtons(
NS(id, "target"),
"Optimization target",
choices = list(
"Mean rank of reference genes" = "mean",
"First rank of reference genes" = "min",
"Last rank of reference genes" = "max"
)
),
actionButton(
NS(id, "optimize_button"),
"Optimize weights",
class = "btn-primary"
)
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)
}
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# Construct server for the methods editor.
#
# @param analysis The reactive containing the results to be weighted.
#
# @return A reactive containing the weighted results.
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methods_server <- function(id, analysis) {
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moduleServer(id, function(input, output, session) {
observeEvent(input$optimize_button, {
analysis <- analysis()
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method_ids <- NULL
# Only include activated methods.
for (method in methods) {
if (input[[method$id]]) {
method_ids <- c(method_ids, method$id)
}
}
weights <- geposan::optimal_weights(
analysis,
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method_ids,
analysis$preset$reference_gene_ids,
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target = input$target
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)
for (method_id in method_ids) {
updateSliderInput(
session,
sprintf("%s_weight", method_id),
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value = weights[[method_id]]
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)
}
})
# Observe each method's enable button and synchronise the slider state.
lapply(methods, function(method) {
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observeEvent(input[[method$id]],
{ # nolint
shinyjs::toggleState(sprintf("%s_weight", method$id))
},
ignoreInit = TRUE
)
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})
reactive({
# Take the actual weights from the sliders.
weights <- NULL
for (method in methods) {
if (input[[method$id]]) {
weight <- input[[sprintf("%s_weight", method$id)]]
weights[[method$id]] <- weight
}
}
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geposan::ranking(analysis(), weights)
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})
})
}