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results: Show method correlation coefficient

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This commit is contained in:
Elias Projahn 2022-08-30 10:26:40 +02:00
parent f0a8bce297
commit f9fcb16130
1 changed files with 45 additions and 12 deletions
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57
R/results.R
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@ -109,6 +109,7 @@ results_ui <- function(id, options) {
)
)
),
htmlOutput(NS(id, "method_correlation")),
plotly::plotlyOutput(
NS(id, "ranking_correlation_plot"),
width = "100%",
@ -243,25 +244,57 @@ results_server <- function(id, options, analysis) {
geposan::plot_rankings(rankings, gene_sets)
})
output$ranking_correlation_plot <- plotly::renderPlotly({
preset <- preset()
ranking <- ranking()
ranking_x <- if (input$ranking_x == "combined") {
ranking
ranking_x <- reactive({
if (input$ranking_x == "combined") {
ranking()
} else {
weights <- list()
weights[[input$ranking_x]] <- 1.0
geposan::ranking(ranking, weights)
geposan::ranking(ranking(), weights)
}
})
ranking_y <- if (input$ranking_y == "combined") {
ranking
ranking_y <- reactive({
if (input$ranking_y == "combined") {
ranking()
} else {
weights <- list()
weights[[input$ranking_y]] <- 1.0
geposan::ranking(ranking, weights)
geposan::ranking(ranking(), weights)
}
})
output$method_correlation <- renderText({
data <- merge(
ranking_x()[, c("gene", "score")],
ranking_y()[, c("gene", "score")],
by = "gene"
)
c <- stats::cor(
data$score.x,
data$score.y,
method = "spearman"
) |>
round(digits = 4) |>
format(nsmall = 4)
p <- stats::cor.test(
data$score.x,
data$score.y,
method = "spearman"
)$p.value |>
round(digits = 4) |>
format(nsmall = 4)
HTML(glue::glue(
"Spearman's rank correlation coefficient: ",
"<b>{c}</b>, p = <b>{p}</b>"
))
})
output$ranking_correlation_plot <- plotly::renderPlotly({
preset <- preset()
gene_sets <- list("Reference genes" = preset$reference_gene_ids)
comparison_gene_ids <- comparison_gene_ids()
@ -282,8 +315,8 @@ results_server <- function(id, options, analysis) {
method_names[["combined"]] <- "Combined"
geposan::plot_rankings_correlation(
ranking_x,
ranking_y,
ranking_x(),
ranking_y(),
method_names[[input$ranking_x]],
method_names[[input$ranking_y]],
gene_sets = gene_sets,