geposanui/R/results.R

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#' Create the UI for the results page.
#'
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#' @param id ID for namespacing.
#' @param options Global options for the application.
#'
#' @return The UI elements.
#'
#' @noRd
results_ui <- function(id, options) {
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ranking_choices <- purrr::lmap(options$methods, function(method) {
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l <- list()
l[[method[[1]]$name]] <- method[[1]]$id
l
})
ranking_choices <- c(ranking_choices, "Combined" = "combined")
sidebarLayout(
sidebarPanel(
width = 3,
comparison_editor_ui(NS(id, "comparison_editor"), options),
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methods_ui(NS(id, "methods"), options)
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),
mainPanel(
width = 9,
tabsetPanel(
type = "pills",
tabPanel(
title = "Overview",
div(
style = "margin-top: 16px",
plotly::plotlyOutput(
NS(id, "rank_plot"),
width = "100%",
height = "600px"
)
)
),
tabPanel(
title = "Method comparison",
div(
style = "margin-top: 16px",
plotly::plotlyOutput(
NS(id, "rankings_plot"),
width = "100%",
height = "600px"
)
)
),
tabPanel(
title = "Method correlation",
div(
class = "flow-layout",
style = "margin-top: 16px",
selectInput(
NS(id, "ranking_y"),
label = NULL,
choices = ranking_choices
),
span(
style = paste0(
"display: inline-block;",
"margin-right: 12px;",
"padding: 0.375rem 0.75rem;"
),
"~"
),
selectInput(
NS(id, "ranking_x"),
label = NULL,
choices = ranking_choices,
selected = "combined"
),
div(
style = paste0(
"display: inline-block;",
"padding: 0.375rem 0.75rem;"
),
checkboxInput(
NS(id, "use_ranks"),
"Use ranks instead of scores",
value = TRUE
)
),
div(
style = paste0(
"display: inline-block;",
"padding: 0.375rem 0.75rem;"
),
checkboxInput(
NS(id, "use_sample"),
"Take random sample of genes",
value = TRUE
)
)
),
plotly::plotlyOutput(
NS(id, "ranking_correlation_plot"),
width = "100%",
height = "600px"
)
),
tabPanel(
title = "Comparison",
div(
style = "margin-top: 16px",
htmlOutput(NS(id, "comparison_text")),
plotly::plotlyOutput(
NS(id, "boxplot"),
width = "100%",
height = "600px"
)
)
),
tabPanel(
title = "Ortholog locations",
div(
style = "margin-top: 16px",
plotly::plotlyOutput(
NS(id, "gene_locations_plot"),
width = "100%",
height = "1200px"
)
)
),
tabPanel(
title = "Scores by position",
div(
class = "flow-layout",
style = "margin-top: 16px",
selectInput(
NS(id, "positions_plot_chromosome_name"),
label = NULL,
choices = c(
list("All chromosomes" = "all"),
chromosome_choices()
)
),
plotly::plotlyOutput(
NS(id, "positions_plot"),
width = "100%",
height = "600px"
)
)
),
tabPanel(
title = "Detailed results",
details_ui(NS(id, "results"))
),
tabPanel(
title = "g:Profiler",
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gsea_ui(NS(id, "gsea"))
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)
)
)
)
}
#' Application logic for the results page.
#'
#' @param id ID for namespacing.
#' @param options Global application options.
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#' @param analysis A reactive containing the analysis that gets visualized.
#'
#' @noRd
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results_server <- function(id, options, analysis) {
preset <- reactive(analysis()$preset)
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moduleServer(id, function(input, output, session) {
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comparison_gene_ids <- comparison_editor_server(
"comparison_editor",
preset,
options
)
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# Rank the results.
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ranking <- methods_server("methods", options, analysis, comparison_gene_ids)
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genes_with_distances <- merge(
geposan::genes,
geposan::distances[species == "hsapiens"],
by.x = "id",
by.y = "gene"
)
# Add gene information to the results.
results <- reactive({
merge(
ranking(),
genes_with_distances,
by.x = "gene",
by.y = "id",
sort = FALSE
)
})
# Server for the detailed results panel.
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details_server("results", options, results)
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output$rank_plot <- plotly::renderPlotly({
preset <- preset()
gene_sets <- list("Reference genes" = preset$reference_gene_ids)
comparison_gene_ids <- comparison_gene_ids()
if (length(comparison_gene_ids) >= 1) {
gene_sets <- c(
gene_sets,
list("Comparison genes" = comparison_gene_ids)
)
}
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geposan::plot_scores(ranking(), gene_sets = gene_sets)
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})
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output$rankings_plot <- plotly::renderPlotly({
preset <- preset()
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rankings <- list()
methods <- preset$methods
all <- ranking()
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for (method in methods) {
weights <- list()
weights[[method$id]] <- 1.0
rankings[[method$name]] <- geposan::ranking(all, weights)
}
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rankings[["Combined"]] <- all
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gene_sets <- list("Reference genes" = preset$reference_gene_ids)
comparison_gene_ids <- comparison_gene_ids()
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if (length(comparison_gene_ids) >= 1) {
gene_sets <- c(
gene_sets,
list("Comparison genes" = comparison_gene_ids)
)
}
geposan::plot_rankings(rankings, gene_sets)
})
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output$ranking_correlation_plot <- plotly::renderPlotly({
preset <- preset()
ranking <- ranking()
ranking_x <- if (input$ranking_x == "combined") {
ranking
} else {
weights <- list()
weights[[input$ranking_x]] <- 1.0
geposan::ranking(ranking, weights)
}
ranking_y <- if (input$ranking_y == "combined") {
ranking
} else {
weights <- list()
weights[[input$ranking_y]] <- 1.0
geposan::ranking(ranking, weights)
}
gene_sets <- list("Reference genes" = preset$reference_gene_ids)
comparison_gene_ids <- comparison_gene_ids()
if (length(comparison_gene_ids) >= 1) {
gene_sets <- c(
gene_sets,
list("Comparison genes" = comparison_gene_ids)
)
}
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method_names <- options$methods |> purrr::lmap(function(method) {
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l <- list()
l[[method[[1]]$id]] <- method[[1]]$name
l
})
method_names[["combined"]] <- "Combined"
geposan::plot_rankings_correlation(
ranking_x,
ranking_y,
method_names[[input$ranking_x]],
method_names[[input$ranking_y]],
gene_sets = gene_sets,
use_ranks = input$use_ranks,
use_sample = input$use_sample
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)
})
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output$comparison_text <- renderUI({
reference <- geposan::compare(
ranking(),
preset()$reference_gene_ids
)
comparison <- if (!is.null(comparison_gene_ids())) {
geposan::compare(ranking(), comparison_gene_ids())
}
num <- function(x, digits) {
format(
round(x, digits = digits),
nsmall = digits,
scientific = FALSE
)
}
comparison_text <- function(name, comparison) {
glue::glue(
"The {name} have a mean score of ",
"<b>{num(comparison$mean_score, 4)}</b> ",
"resulting in a mean rank of ",
"<b>{num(comparison$mean_rank, 1)}</b>. ",
"This corresponds to a percent rank of ",
"<b>{num(100 * comparison$mean_percentile, 2)}%</b>. ",
"A Wilcoxon rank sum test gives an estimated score difference ",
"between <b>{num(comparison$test_result$conf.int[1], 3)}</b> and ",
"<b>{num(comparison$test_result$conf.int[2], 3)}</b> with a 95% ",
"confidence. This corresponds to a p-value of ",
"<b>{num(comparison$test_result$p.value, 4)}</b>."
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)
}
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reference_div <- div(HTML(
comparison_text("reference genes", reference)
))
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if (!is.null(comparison)) {
div(
reference_div,
div(HTML(comparison_text("comparison genes", comparison)))
)
} else {
reference_div
}
})
output$boxplot <- plotly::renderPlotly({
preset <- preset()
gene_sets <- list("Reference genes" = preset$reference_gene_ids)
comparison_gene_ids <- comparison_gene_ids()
if (length(comparison_gene_ids) >= 1) {
gene_sets <- c(
gene_sets,
list("Comparison genes" = comparison_gene_ids)
)
}
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geposan::plot_boxplot(ranking(), gene_sets)
})
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output$gene_locations_plot <- plotly::renderPlotly({
preset <- preset()
gene_sets <- list("Reference genes" = preset$reference_gene_ids)
comparison_gene_ids <- comparison_gene_ids()
if (length(comparison_gene_ids) >= 1) {
gene_sets <- c(
gene_sets,
list("Comparison genes" = comparison_gene_ids)
)
}
geposan::plot_positions(
preset$species_ids,
gene_sets,
reference_gene_ids = preset$reference_gene_ids
)
})
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output$positions_plot <- plotly::renderPlotly({
preset <- preset()
gene_sets <- list("Reference genes" = preset$reference_gene_ids)
comparison_gene_ids <- comparison_gene_ids()
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if (length(comparison_gene_ids) >= 1) {
gene_sets <- c(
gene_sets,
list("Comparison genes" = comparison_gene_ids)
)
}
chromosome <- if (input$positions_plot_chromosome_name == "all") {
NULL
} else {
input$positions_plot_chromosome_name
}
geposan::plot_scores_by_position(
ranking(),
chromosome_name = chromosome,
gene_sets = gene_sets
)
})
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gsea_server("gsea", results)
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})
}
#' Generate a named list for choosing chromosomes.
#' @noRd
chromosome_choices <- function() {
choices <- purrr::lmap(
unique(geposan::genes$chromosome),
function(name) {
choice <- list(name)
names(choice) <- paste0(
"Chromosome ",
name
)
choice
}
)
choices[order(suppressWarnings(sapply(choices, as.integer)))]
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}