mirror of
https://github.com/johrpan/geposanui.git
synced 2025-10-26 11:17:24 +01:00
220 lines
6 KiB
R
220 lines
6 KiB
R
# Java script function to replace gene IDs with Ensembl gene links.
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js_link <- DT::JS("function(row, data) {
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let id = data[1];
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var name = data[2];
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if (!name) name = 'Unknown';
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let url = `https://www.ensembl.org/Homo_sapiens/Gene/Summary?g=${id}`;
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$('td:eq(1)', row).html(`<a href=\"${url}\" target=\"_blank\">${name}</a>`);
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}")
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server <- function(input, output, session) {
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preset <- preset_editor_server("preset_editor")
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# Compute the results according to the preset.
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analysis <- reactive({
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preset <- preset()
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# Perform the analysis cached based on the preset's hash.
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analysis <- withProgress(
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message = "Analyzing genes",
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value = 0.0,
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{ # nolint
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geposan::analyze(preset, function(progress) {
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setProgress(progress)
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})
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}
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)
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analysis
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})
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# Rank the results.
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ranking <- methods_server("methods", analysis)
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# Add gene information to the results.
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results <- reactive({
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merge(
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ranking(),
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geposan::genes,
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by.x = "gene",
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by.y = "id",
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sort = FALSE
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)
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})
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# Apply the filters.
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results_filtered <- filters_server("filters", results)
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# Server for the detailed results panel.
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results_server("results", results_filtered)
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comparison_gene_ids <- comparison_editor_server("comparison_editor", preset)
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output$scatter <- plotly::renderPlotly({
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preset <- preset()
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gene_sets <- list("Reference genes" = preset$reference_gene_ids)
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comparison_gene_ids <- comparison_gene_ids()
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if (length(comparison_gene_ids) >= 1) {
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gene_sets <- c(
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gene_sets,
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list("Comparison genes" = comparison_gene_ids)
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)
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}
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geposan::plot_positions(preset$species_ids, gene_sets)
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})
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output$rank_plot <- plotly::renderPlotly({
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preset <- preset()
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gene_sets <- list("Reference genes" = preset$reference_gene_ids)
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comparison_gene_ids <- comparison_gene_ids()
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if (length(comparison_gene_ids) >= 1) {
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gene_sets <- c(
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gene_sets,
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list("Comparison genes" = comparison_gene_ids)
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)
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}
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geposan::plot_scores(
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ranking(),
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gene_sets = gene_sets,
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max_rank = results_filtered()[, max(rank)]
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)
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})
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output$rankings_plot <- plotly::renderPlotly({
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preset <- preset()
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rankings <- list()
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methods <- preset$methods
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all <- ranking()
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for (method in methods) {
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weights <- list()
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weights[[method$id]] <- 1.0
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rankings[[method$name]] <- geposan::ranking(all, weights)
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}
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rankings[["Combined"]] <- all
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gene_sets <- list("Reference genes" = preset$reference_gene_ids)
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comparison_gene_ids <- comparison_gene_ids()
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if (length(comparison_gene_ids) >= 1) {
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gene_sets <- c(
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gene_sets,
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list("Comparison genes" = comparison_gene_ids)
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)
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}
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geposan::plot_rankings(rankings, gene_sets)
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})
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output$boxplot <- plotly::renderPlotly({
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preset <- preset()
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gene_sets <- list("Reference genes" = preset$reference_gene_ids)
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comparison_gene_ids <- comparison_gene_ids()
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if (length(comparison_gene_ids) >= 1) {
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gene_sets <- c(
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gene_sets,
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list("Comparison genes" = comparison_gene_ids)
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)
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}
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geposan::plot_boxplot(ranking(), gene_sets)
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})
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gost <- reactive({
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withProgress(
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message = "Querying g:Profiler",
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value = 0.0,
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{ # nolint
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setProgress(0.2)
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gprofiler2::gost(results_filtered()[, gene])
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}
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)
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})
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output$gost_plot <- plotly::renderPlotly({
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gprofiler2::gostplot(
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gost(),
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capped = FALSE,
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interactive = TRUE
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)
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})
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output$gost_details <- DT::renderDT({
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data <- data.table(gost()$result)
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setorder(data, p_value)
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data[, total_ratio := term_size / effective_domain_size]
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data[, query_ratio := intersection_size / query_size]
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data <- data[, .(source, term_name, total_ratio, query_ratio, p_value)]
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dt <- DT::datatable(
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data,
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rownames = FALSE,
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colnames = c(
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"Source",
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"Term",
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"Total ratio",
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"Query ratio",
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"p-value"
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),
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style = "bootstrap",
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options = list(
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pageLength = 25
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)
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)
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dt <- DT::formatRound(dt, "p_value", digits = 4)
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dt <- DT::formatPercentage(
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dt,
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c("total_ratio", "query_ratio"),
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digits = 1
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)
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})
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output$disgenet <- DT::renderDT({
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withProgress(
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message = "Querying DisGeNET",
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value = 0.0,
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{ # nolint
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setProgress(0.2)
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gene_names <- results_filtered()[, name]
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gene_names <- unique(gene_names[gene_names != ""])
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diseases <- disgenet2r::disease_enrichment(gene_names)
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data <- data.table(diseases@qresult)
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data <- data[, .(Description, Ratio, BgRatio, pvalue)]
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setorder(data, pvalue)
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dt <- DT::datatable(
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data,
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rownames = FALSE,
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colnames = c(
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"Disease",
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"Query ratio",
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"Total ratio",
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"p-value"
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),
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style = "bootstrap",
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options = list(
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pageLength = 25
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)
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)
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dt <- DT::formatRound(dt, "pvalue", digits = 4)
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dt
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}
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)
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})
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}
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