mirror of
https://github.com/johrpan/ubigen.git
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101 lines
2.3 KiB
R
101 lines
2.3 KiB
R
#' Server implementing the main user interface.
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#' @noRd
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server <- function(input, output) {
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ranked_data <- reactive({
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total_weight <- abs(input$cross_sample_weight) + abs(input$sd_expression)
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data <- data.table::copy(ubigen::genes)
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data[, score :=
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(input$cross_sample_weight * get(input$cross_sample_metric) +
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input$sd_expression * sd_expression_normalized) /
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total_weight]
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data.table::setorder(data, -score)
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data[, rank := .I]
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data[, percentile := 1 - rank / max(rank)]
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data
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})
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custom_genes <- gene_selector_server("custom_genes")
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output$overview_plot <- plotly::renderPlotly(overview_plot(
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ranked_data(),
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highlighted_genes = custom_genes()
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))
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output$scores_plot <- plotly::renderPlotly(scores_plot(
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ranked_data(),
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highlighted_genes = custom_genes()
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))
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output$selected_genes <- DT::renderDataTable({
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selected_points <- plotly::event_data("plotly_selected")
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data <- if (is.null(selected_points)) {
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ranked_data()
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} else {
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ranked_data()[rank %in% selected_points$x]
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}
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genes_table(data)
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})
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}
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#' Create a displayable data table from the gene results data.
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#' @noRd
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genes_table <- function(data) {
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data <- data[, .(
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"Gene" = glue::glue_data(
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data,
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"<a href=\"https://www.ensembl.org/Homo_sapiens/Gene/Summary",
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"?db=core;g={gene}\" target=\"_blank\">{hgnc_name}</a>"
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),
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"Rank" = rank,
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"Percentile" = percentile,
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"Score" = score,
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"Median" = median_expression,
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"Mean" = mean_expression,
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"Standard deviation" = sd_expression,
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"Expressed" = above_zero,
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"Above median" = above_median,
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"Above 95%" = above_95
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)]
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DT::datatable(
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data,
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options = list(
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buttons = list(
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list(
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extend = "copy",
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text = "Copy to clipboard"
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),
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list(
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extend = "csv",
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text = "Download CSV"
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)
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),
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dom = "fBrtip",
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pageLength = 100
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),
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rownames = FALSE,
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escape = FALSE,
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selection = "none",
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extensions = "Buttons"
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) |>
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DT::formatPercentage(
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c(
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"Percentile",
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"Score",
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"Expressed",
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"Above median",
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"Above 95%"
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),
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digits = 2,
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) |>
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DT::formatRound(c(
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"Median",
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"Mean",
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"Standard deviation"
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))
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}
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