Add options to configure default gene sets

This commit is contained in:
Elias Projahn 2022-05-19 16:24:23 +02:00
parent 22f5e86625
commit 74d7865389
9 changed files with 391 additions and 370 deletions

View file

@ -7,225 +7,237 @@ js_link <- DT::JS("function(row, data) {
$('td:eq(1)', row).html(`<a href=\"${url}\" target=\"_blank\">${name}</a>`);
}")
server <- function(input, output, session) {
input_reactives <- input_page_server("input_page")
preset <- input_reactives$preset
comparison_gene_ids <- input_reactives$comparison_gene_ids
#' Create a server function for the application.
#'
#' @param options Global application options.
#' @noRd
server <- function(options) {
function(input, output, session) {
input_reactives <- input_page_server("input_page", options)
preset <- input_reactives$preset
comparison_gene_ids <- input_reactives$comparison_gene_ids
observe({
updateNavbarPage(
session,
"main_page",
selected = "Results"
)
}) |> bindEvent(preset(), ignoreInit = TRUE)
# Compute the results according to the preset.
analysis <- reactive({
withProgress(
message = "Analyzing genes",
value = 0.0,
{ # nolint
geposan::analyze(
preset(),
progress = function(progress) {
setProgress(progress)
},
include_results = FALSE
)
}
)
}) |> bindCache(preset())
# Rank the results.
ranking <- methods_server("methods", analysis, comparison_gene_ids)
# Add gene information to the results.
results <- reactive({
merge(
ranking(),
geposan::genes,
by.x = "gene",
by.y = "id",
sort = FALSE
)
})
# Apply the filters.
results_filtered <- filters_server("filters", results)
# Server for the detailed results panel.
results_server("results", results_filtered)
output$rank_plot <- plotly::renderPlotly({
preset <- preset()
gene_sets <- list("Reference genes" = preset$reference_gene_ids)
comparison_gene_ids <- comparison_gene_ids()
if (length(comparison_gene_ids) >= 1) {
gene_sets <- c(
gene_sets,
list("Comparison genes" = comparison_gene_ids)
observe({
updateNavbarPage(
session,
"main_page",
selected = "Results"
)
}
}) |> bindEvent(preset(), ignoreInit = TRUE)
geposan::plot_scores(
ranking(),
gene_sets = gene_sets,
max_rank = results_filtered()[, max(rank)]
)
})
output$rankings_plot <- plotly::renderPlotly({
preset <- preset()
rankings <- list()
methods <- preset$methods
all <- ranking()
for (method in methods) {
weights <- list()
weights[[method$id]] <- 1.0
rankings[[method$name]] <- geposan::ranking(all, weights)
}
rankings[["Combined"]] <- all
gene_sets <- list("Reference genes" = preset$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_rankings(rankings, gene_sets)
})
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)
)
}
geposan::plot_boxplot(ranking(), gene_sets)
})
output$positions_plot <- plotly::renderPlotly({
preset <- preset()
gene_sets <- list("Reference genes" = preset$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_scores_by_position(
ranking(),
input$positions_plot_chromosome_name,
gene_sets = gene_sets
)
})
gost <- reactive({
withProgress(
message = "Querying g:Profiler",
value = 0.0,
{ # nolint
setProgress(0.2)
gprofiler2::gost(results_filtered()[, gene])
}
)
})
output$gost_plot <- plotly::renderPlotly({
gprofiler2::gostplot(
gost(),
capped = FALSE,
interactive = TRUE
)
})
output$gost_details <- DT::renderDT({
data <- data.table(gost()$result)
setorder(data, p_value)
data[, total_ratio := term_size / effective_domain_size]
data[, query_ratio := intersection_size / query_size]
data <- data[, .(source, term_name, total_ratio, query_ratio, p_value)]
dt <- DT::datatable(
data,
rownames = FALSE,
colnames = c(
"Source",
"Term",
"Total ratio",
"Query ratio",
"p-value"
),
style = "bootstrap",
options = list(
pageLength = 25
)
)
dt <- DT::formatRound(dt, "p_value", digits = 4)
dt <- DT::formatPercentage(
dt,
c("total_ratio", "query_ratio"),
digits = 1
)
})
output$disgenet <- DT::renderDT({
withProgress(
message = "Querying DisGeNET",
value = 0.0,
{ # nolint
setProgress(0.2)
gene_names <- results_filtered()[, name]
gene_names <- unique(gene_names[gene_names != ""])
diseases <- disgenet2r::disease_enrichment(gene_names)
data <- data.table(diseases@qresult)
data <- data[, .(Description, Ratio, BgRatio, pvalue)]
setorder(data, pvalue)
dt <- DT::datatable(
data,
rownames = FALSE,
colnames = c(
"Disease",
"Query ratio",
"Total ratio",
"p-value"
),
style = "bootstrap",
options = list(
pageLength = 25
# Compute the results according to the preset.
analysis <- reactive({
withProgress(
message = "Analyzing genes",
value = 0.0,
{ # nolint
geposan::analyze(
preset(),
progress = function(progress) {
setProgress(progress)
},
include_results = FALSE
)
}
)
}) |> bindCache(preset())
# Rank the results.
ranking <- methods_server("methods", analysis, comparison_gene_ids)
# Add gene information to the results.
results <- reactive({
merge(
ranking(),
geposan::genes,
by.x = "gene",
by.y = "id",
sort = FALSE
)
})
# Apply the filters.
results_filtered <- filters_server("filters", results)
# Server for the detailed results panel.
results_server("results", results_filtered)
output$rank_plot <- plotly::renderPlotly({
preset <- preset()
gene_sets <- list("Reference genes" = preset$reference_gene_ids)
comparison_gene_ids <- comparison_gene_ids()
if (length(comparison_gene_ids) >= 1) {
gene_sets <- c(
gene_sets,
list("Comparison genes" = comparison_gene_ids)
)
dt <- DT::formatRound(dt, "pvalue", digits = 4)
dt
}
)
})
geposan::plot_scores(
ranking(),
gene_sets = gene_sets,
max_rank = results_filtered()[, max(rank)]
)
})
output$rankings_plot <- plotly::renderPlotly({
preset <- preset()
rankings <- list()
methods <- preset$methods
all <- ranking()
for (method in methods) {
weights <- list()
weights[[method$id]] <- 1.0
rankings[[method$name]] <- geposan::ranking(all, weights)
}
rankings[["Combined"]] <- all
gene_sets <- list("Reference genes" = preset$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_rankings(rankings, gene_sets)
})
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)
)
}
geposan::plot_boxplot(ranking(), gene_sets)
})
output$positions_plot <- plotly::renderPlotly({
preset <- preset()
gene_sets <- list("Reference genes" = preset$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_scores_by_position(
ranking(),
input$positions_plot_chromosome_name,
gene_sets = gene_sets
)
})
gost <- reactive({
withProgress(
message = "Querying g:Profiler",
value = 0.0,
{ # nolint
setProgress(0.2)
gprofiler2::gost(results_filtered()[, gene])
}
)
})
output$gost_plot <- plotly::renderPlotly({
gprofiler2::gostplot(
gost(),
capped = FALSE,
interactive = TRUE
)
})
output$gost_details <- DT::renderDT({
data <- data.table(gost()$result)
setorder(data, p_value)
data[, total_ratio := term_size / effective_domain_size]
data[, query_ratio := intersection_size / query_size]
data <- data[, .(
source,
term_name,
total_ratio,
query_ratio,
p_value
)]
dt <- DT::datatable(
data,
rownames = FALSE,
colnames = c(
"Source",
"Term",
"Total ratio",
"Query ratio",
"p-value"
),
style = "bootstrap",
options = list(
pageLength = 25
)
)
dt <- DT::formatRound(dt, "p_value", digits = 4)
dt <- DT::formatPercentage(
dt,
c("total_ratio", "query_ratio"),
digits = 1
)
})
output$disgenet <- DT::renderDT({
withProgress(
message = "Querying DisGeNET",
value = 0.0,
{ # nolint
setProgress(0.2)
gene_names <- results_filtered()[, name]
gene_names <- unique(gene_names[gene_names != ""])
diseases <- disgenet2r::disease_enrichment(gene_names)
data <- data.table(diseases@qresult)
data <- data[, .(Description, Ratio, BgRatio, pvalue)]
setorder(data, pvalue)
dt <- DT::datatable(
data,
rownames = FALSE,
colnames = c(
"Disease",
"Query ratio",
"Total ratio",
"p-value"
),
style = "bootstrap",
options = list(
pageLength = 25
)
)
dt <- DT::formatRound(dt, "pvalue", digits = 4)
dt
}
)
})
}
}