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Add optimizer and buttons to disable methods
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parent
529f4a553b
commit
8104e9bd8a
3 changed files with 98 additions and 15 deletions
34
optimize.R
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34
optimize.R
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@ -0,0 +1,34 @@
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#' Find the best weights to rank the data.
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#'
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#' This function ranks the provided data table based on a weighted score
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#' computed from the specified `columns`. It tries to find the optimal weights
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#' that result in a ranking, where the mean rank of the given reference genes
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#' is as high as possible.
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#'
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#' @param data Input data including the columns.
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#' @param colums Columns containing the separate scores between 0.0 and 1.0.
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#' @param reference_gene_ids IDs of the reference genes within the input data.
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#'
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#' @returns Vector of optimal column weights adding up to 1.0.
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optimize_weights <- function(data, columns, reference_gene_ids) {
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#' Compute the mean rank of the reference genes when applying the weights.
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mean_rank <- function(weights) {
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data <- copy(data)
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data[, score := 0.0]
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for (i in seq_along(columns)) {
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column <- columns[i]
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weighted <- weights[i] * data[, ..column]
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data[, score := score + weighted]
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}
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setorder(data, -score)
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data[, rank := .I]
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data[gene %chin% reference_gene_ids, mean(rank)]
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}
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weights <- optim(rep(1.0, length(columns)), mean_rank)$par
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total_weight <- sum(weights)
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weights / total_weight
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}
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44
server.R
44
server.R
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@ -6,6 +6,7 @@ library(rclipboard)
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library(shiny)
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source("init.R")
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source("optimize.R")
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source("rank_plot.R")
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source("scatter_plot.R")
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@ -18,7 +19,7 @@ js_link <- JS("function(row, data) {
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$('td:eq(1)', row).html(`<a href=\"${url}\" target=\"_blank\">${name}</a>`);
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}")
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server <- function(input, output) {
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server <- function(input, output, session) {
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#' Show the customized slider for setting the required number of species.
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output$n_species_slider <- renderUI({
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sliderInput(
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@ -35,6 +36,35 @@ server <- function(input, output) {
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)
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})
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observeEvent(input$optimize_button, {
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results <- isolate(results())
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method_ids <- NULL
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for (method in methods) {
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if (isolate(input[[method$id]])) {
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method_ids <- c(method_ids, method$id)
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}
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}
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reference_gene_ids <- genes[suggested | verified == TRUE, id]
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weights <- optimize_weights(results, method_ids, reference_gene_ids)
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mapply(function(method_id, weight) {
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updateSliderInput(
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session,
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sprintf("%s_weight", method_id),
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value = weight * 100
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)
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}, method_ids, weights)
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})
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# Observe each method's enable button.
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lapply(methods, function(method) {
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observeEvent(input[[method$id]], {
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shinyjs::toggleState(sprintf("%s_weight", method$id))
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}, ignoreInit = TRUE)
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})
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#' Rank the results based on the specified weights. Filter out genes with
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#' too few species but don't apply the cut-off score.
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results <- reactive({
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@ -52,11 +82,13 @@ server <- function(input, output) {
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results[, score := 0.0]
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for (method in methods) {
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weight <- input[[method$id]]
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total_weight <- total_weight + weight
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column <- method$id
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weighted <- weight * results[, ..column]
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results[, score := score + weighted]
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if (input[[method$id]]) {
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weight <- input[[sprintf("%s_weight", method$id)]]
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total_weight <- total_weight + weight
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column <- method$id
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weighted <- weight * results[, ..column]
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results[, score := score + weighted]
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}
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}
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results[, score := score / total_weight]
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35
ui.R
35
ui.R
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@ -6,6 +6,7 @@ library(shiny)
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source("methods.R")
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ui <- fluidPage(
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shinyjs::useShinyjs(),
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rclipboardSetup(),
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titlePanel("TPE-OLD candidates"),
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sidebarLayout(
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@ -30,16 +31,32 @@ ui <- fluidPage(
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step = 1,
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value = 50
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),
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h3("Ranking"),
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h3("Methods"),
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actionButton(
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"optimize_button",
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"Find optimal weights",
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icon = icon("check-double")
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),
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div(style = "margin-top: 16px"),
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lapply(methods, function(method) {
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sliderInput(
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method$id,
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method$description,
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post = "%",
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min = 0,
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max = 100,
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step = 1,
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value = 100
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verticalLayout(
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checkboxInput(
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method$id,
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span(
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method$description,
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style = "font-weight: bold"
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),
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value = TRUE
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),
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sliderInput(
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sprintf("%s_weight", method$id),
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NULL,
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post = "%",
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min = 0,
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max = 100,
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step = 1,
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value = 100
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)
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)
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}),
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checkboxInput(
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