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app.R
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app.R
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# loading libraries -------------------------------------------------------
library(shiny)
library(future)
library(promises)
plan(multisession)
library(shinycssloaders)
library(shinyjs)
library(plotly, warn.conflicts = FALSE)
library(reactable, warn.conflicts = FALSE)
library(bs4Dash, warn.conflicts = FALSE)
library(shinydashboard, warn.conflicts = FALSE)
library(visNetwork, warn.conflicts = FALSE)
library(rintrojs, warn.conflicts = FALSE)
library(shinyBS, warn.conflicts = FALSE)
library(igraph)
library(dplyr, warn.conflicts = FALSE)
library(tidyr, warn.conflicts = FALSE)
library(ggplot2, warn.conflicts = FALSE)
options(spinner.type = 6)
# sourcing external files -------------------------------------------------
source("utils.R")
# ui definition -----------------------------------------------------------
magnetique_ui <- shinydashboard::dashboardPage(
title = "magnetique",
header = shinydashboard::dashboardHeader(disable = TRUE),
# sidebar definition ------------------------------------------------------
sidebar = dashboardSidebar(
img(src = "magnetique_logo.png", class="img-responsive"),
hidden(h2("Options:", style = 'margin: 15px', id='options')),
uiOutput("ui_sidebar")
),
# body definition ---------------------------------------------------------
body = dashboardBody(
introjsUI(),
## handling the overflow in vertical direction for the tabBox
shiny::tags$head(
shiny::tags$style(
HTML("
/* fix overflow */
#myScrollBox{ overflow-y: scroll; }
/* side bar color */
.main-sidebar { background-color: white !important; }
.skin-blue .main-sidebar .sidebar{ color: black; }
/* body */
.content-wrapper, .right-side {background-color: #d3d3d3 ;}")
)
),
## using shinyjs inside the app
shinyjs::useShinyjs(),
## left ctrl to trigger the bookmarking functionality (via button)
shiny::tags$script(
HTML(
"$(function(){
$(document).keyup(function(e) {
if (e.which == 17) {
$('#bookmarker').click()
}
});
})"
)
),
div(
id = "myScrollBox",
## will adjust indentation later ##
tabBox(
width = 12,
id = "magnetique_tab",
tabPanel(
title = "Welcome!", icon = icon("magnet"), value = "tab-welcome",
fluidRow(
column(
width = 12,
div(
actionButton(
"tour_firststeps",
label = "", icon = icon("question-circle"),
style = .helpbutton_biocstyle
),
shinyBS::bsTooltip(
"tour_firststeps",
"Click me to start a tour of this section!",
"bottom",
options = list(container = "body")
),
style = "float:right"
)
)
),
fluidRow(
column(
width = 6,
includeMarkdown("www/overview.md"),
actionButton(inputId = "popup_about_us",
label = "More about the development team",
icon = icon("users"), style = .actionbutton_biocstyle
)
),
column(
width = 6,
h2("Patient characteristics and technical covariates"),
includeHTML("www/metadata_table.html")
)
),
),
tabPanel(
title = "Gene View", icon = icon("dna"), value = "tab-gene-view",
fluidRow(
column(
width = 12,
div(
actionButton(
"tour_geneview",
label = "", icon = icon("question-circle"),
style = .helpbutton_biocstyle
),
shinyBS::bsTooltip(
"tour_geneview",
"Click me to start a tour of this section!",
"bottom",
options = list(container = "body")
),
style = "float:right"
)
)
),
fluidRow(
id = "geneview_row1",
column(
width = 6,
withSpinner(
tagList(
reactableOutput("de_table"),
tags$button("Download as CSV", onclick = "Reactable.downloadDataCSV('de_table', 'de_table.csv')")
)
)
),
column(
width = 3,
withSpinner(
plotlyOutput("de_volcano")
)
),
column(
width = 3,
withSpinner(
plotlyOutput("dtu_volcano")
)
)
),
fluidRow(
id = "geneview_row2",
column(
width = 2,
withSpinner(
plotlyOutput("gene_counts")
)
),
column(
width = 4,
withSpinner(
plotlyOutput("transcript_proportion")
)
),
column(
width = 6,
withSpinner(
plotOutput("gene_structure")
)
)
),
),
tabPanel(
id = "tab-geneset-view",
title = "Gene set View", icon = icon("project-diagram"), value = "tab-geneset-view",
fluidRow(
column(
width = 12,
div(
actionButton(
"tour_genesetview",
label = "", icon = icon("question-circle"),
style = .helpbutton_biocstyle
),
shinyBS::bsTooltip(
"tour_genesetview",
"Click me to start a tour of this section!",
"bottom",
options = list(container = "body")
),
style = "float:right"
)
)
),
fluidRow(
column(
width = 5,
withSpinner(
tagList(
reactableOutput("enrich_table"),
tags$button("Download as CSV", onclick = "Reactable.downloadDataCSV('enrich_table', 'enrich_table.csv')")
)
)
),
column(
width = 7,
withSpinner(
plotlyOutput("enriched_funcres")
)
)
),
fluidRow(
column(
width = 6,
withSpinner(
tagList(
visNetworkOutput("visnet_em"),
shinydashboard::box(
title = "About this enrichment map",
width = 12,
collapsible = TRUE,
collapsed = TRUE,
htmlOutput("visnet_explanation")
)
)
)
),
column(
width = 6,
withSpinner(
plotOutput("emap_signature")
)
)
)
),
tabPanel(
id = "tab-carnival",
title = "Carnival View", icon = icon("network-wired"), value = "tab-carnival",
fluidRow(
column(
width = 12,
div(
actionButton(
"tour_carnivalview",
label = "", icon = icon("question-circle"),
style = .helpbutton_biocstyle
),
shinyBS::bsTooltip(
"tour_carnivalview",
"Click me to start a tour of this section!",
"bottom",
options = list(container = "body")
),
style = "float:right"
)
)
),
fluidRow(
column(
id = "carnival_legend",
width = 3,
img(src = "https://user-images.githubusercontent.com/4517913/166660064-8b171940-b2ce-46e5-bfc6-c2c6685a5bd0.jpeg", class="img-responsive")
),
column(
id = "carnival_network",
width = 9,
visNetworkOutput("visnet_carnival", height = "750px")
)
)
),
tabPanel(
title = "RBP:RNA View", icon = icon("arrows-alt-h"), value = "tab-rbp-view",
fluidRow(
column(
width = 12,
div(
actionButton(
"tour_rbpview",
label = "", icon = icon("question-circle"),
style = .helpbutton_biocstyle
),
shinyBS::bsTooltip(
"tour_rbpview",
"Click me to start a tour of this section!",
"bottom",
options = list(container = "body")
),
style = "float:right"
)
)
),
fluidRow(
id = "rbpview_row1",
column(
width = 8,
withSpinner(
visNetworkOutput("rbp_network")
)
),
)
,
fluidRow(
id = "rbpview_row2",
column(
width = 8,
withSpinner(
tagList(
reactableOutput("rbp_table"),
tags$button("Download as CSV", onclick = "Reactable.downloadDataCSV('rbp_table', 'rbp_table.csv')")
)
)
),
)
),
tabPanel(
title = "Bookmarks", icon = icon("bookmark"), value = "tab-bookmark",
fluidRow(
column(
width = 12,
div(
actionButton(
"tour_bookmarks",
label = "", icon = icon("question-circle"),
style = .helpbutton_biocstyle
),
shinyBS::bsTooltip(
"tour_bookmarks",
"Click me to start a tour of this section!",
"bottom",
options = list(container = "body")
),
style = "float:right"
)
)
),
uiOutput("ui_bookmarks")
)
)
) ## end of the scrollbox
)
)
# server definition -------------------------------------------------------
magnetique_server <- function(input, output, session) {
showNotification("Connecting to the db.", id = "db_connect", duration=NULL)
con <- DBI::dbConnect(
RPostgres::Postgres(),
dbname = "magnetique",
host = Sys.getenv("PGHOST"),
port = Sys.getenv("PGPORT"),
password = Sys.getenv("PGPASSWORD"),
user = Sys.getenv("PGUSER")
)
session$onSessionEnded(function() DBI::dbDisconnect(con))
removeNotification(id = "db_connect")
# reactive objects and setup commands -------------------------------------
rvalues <- reactiveValues()
rvalues$mygenes <- data.frame(matrix(ncol=2,nrow=0, dimnames=list(NULL, c("gene_id", "gene_name"))))
rvalues$mygenesets <- data.frame(matrix(ncol=2,nrow=0, dimnames=list(NULL, c("gs_id", "gs_description"))))
# sidebar server-side -----------------------------------------------------
output$ui_sidebar <- renderUI({
tagList(
sidebarMenu(
hidden(
selectInput("selected_contrast",
label = "Contrast id",
choices = c(
"DCMvsHCM",
"DCMvsNFD",
"HCMvsNFD"
),
selected = "DCMvsHCM"
)
),
shinyjs::hidden(
tagList(
selectInput("selected_ontology",
label = "Gene Ontology (GO)",
choices = c("BP", "MF", "CC"),
selected = "BP"
),
numericInput("number_genesets",
"Number of genesets",
value = 15,
min = 0
),
selectInput("color_by",
"Color by",
choices = c(
"z_score",
"gs_pvalue"
),
selected = "z_score"
)
)
),
hidden(
actionButton("bookmarker",
label = "Bookmark", icon = icon("heart"),
style = "color: #ffffff; background-color: #ac0000; border-color: #ffffff"
)
)
)
)
})
observeEvent(input$magnetique_tab, {
if (input$magnetique_tab == "tab-geneset-view") {
shinyjs::show("selected_contrast")
shinyjs::show("selected_ontology")
shinyjs::show("number_genesets")
shinyjs::show("color_by")
shinyjs::show("bookmarker")
shinyjs::show("options")
} else if (
input$magnetique_tab == "tab-gene-view"
|| input$magnetique_tab == "tab-carnival") {
shinyjs::show("selected_contrast")
shinyjs::hide("selected_ontology")
shinyjs::hide("number_genesets")
shinyjs::hide("color_by")
shinyjs::show("bookmarker")
shinyjs::show("options")
} else if (input$magnetique_tab == "tab-rbp-view") {
shinyjs::show("selected_contrast")
shinyjs::hide("bookmarker")
} else {
shinyjs::hide("selected_contrast")
shinyjs::hide("selected_ontology")
shinyjs::hide("number_genesets")
shinyjs::hide("color_by")
shinyjs::hide("bookmarker")
shinyjs::hide("options")
}
})
rvalues$key <- reactive({
tbl(con, paste0("res_", input$selected_contrast)) %>%
select(
c(
"gene_id",
"SYMBOL",
"padj",
"log2FoldChange",
"dtu_pvadj",
"dtu_dif"
)
) %>%
collect()
})
rvalues$metadata <- reactive({
con %>%
tbl("metadata") %>%
collect()
})
rvalues$counts <- reactive({
con %>%
tbl(paste0("counts_", local(input$selected_contrast))) %>%
collect()
})
rvalues$vst <- reactive({
con %>% tbl("vst")
})
rvalues$res_enrich <- reactive({
tbl(con, paste0("res_enrich_", local(input$selected_contrast))) %>%
filter(ontology == local(input$selected_ontology)) %>%
collect() %>%
as.data.frame(.) %>%
`rownames<-`(.$gs_id)
})
rvalues$annotation_obj <- reactive({
tbl(con, "annotation_obj") %>%
collect() %>%
as.data.frame() %>%
`rownames<-`(.$gene_id)
})
# DE related content ---------------------------------------------------------
output$de_table <- renderReactable({
rvalues$key() %>%
mutate_at(vars(log2FoldChange, dtu_dif), ~round(., 2)) %>%
mutate_at(vars(padj, dtu_pvadj), ~round(-log10(.), 2)) %>%
reactable(
.,
language = reactableLang(
filterPlaceholder = 'Filter'),
searchable = FALSE,
striped = TRUE,
showPageSizeOptions = TRUE,
defaultSorted = c("padj"),
defaultPageSize = 5,
pageSizeOptions = c(5, 10, 25, 50),
highlight = TRUE,
selection = "single",
onClick = "select",
wrap = FALSE,
rowStyle = list(cursor = "pointer"),
theme = reactableTheme(
stripedColor = "#f6f8fa",
highlightColor = "#f0f5f9",
cellPadding = "8px 12px",
rowSelectedStyle = list(backgroundColor = "#eee", boxShadow = "inset 2px 0 0 0 #FF0000")
),
columns = list(
gene_id = colDef(
name = "gene_id",
filterable = TRUE,
html = TRUE,
cell = JS("function(cellInfo) {
const url = 'https://www.ensembl.org/Homo_sapiens/Gene/Summary?g=' + cellInfo.value
return '<a href=\"' + url + '\" target=\"_blank\">' + cellInfo.value + '</a>'
}"),
minWidth = 140,
header = with_tooltip("gene_id", "Link to Ensembl gene page")
),
SYMBOL = colDef(
name = "Gene name",
filterable = TRUE,
header = with_tooltip("gene_name", "Gene symbol")
),
log2FoldChange = colDef(
name = "dge_log2fc",
header = with_tooltip("dge_log2fc", "Fold change for the DESeq2 analysis")
),
padj = colDef(
name = "-log10_dge_padj",
defaultSortOrder = "desc",
minWidth = 120,
filterable = TRUE,
filterMethod = JS("function(rows, columnId, filterValue) {
return rows.filter(function(row) {
return row.values[columnId] >= filterValue
})
}"),
header = with_tooltip("-log10_dge_padj", "Adjusted p-value for the DESeq2 analysis (-log10 transformed)")
),
dtu_pvadj = colDef(
name = "-log10_dtu_padj",
filterable = TRUE,
width = 130,
filterMethod = JS("function(rows, columnId, filterValue) {
return rows.filter(function(row) {
return row.values[columnId] >= filterValue
})
}"),
header = with_tooltip("-log10_dtu_padj", "Adjusted p-value for the DRIMseq analysis (-log10 transformed)")
),
dtu_dif = colDef(
name = "dtu_dif",
header = with_tooltip("dtu_dif", "Difference in isoform usage for the DRIMseq analysis")
)
),
defaultColDef = colDef(sortNALast = TRUE),
elementId = "de_table"
)
})
prev_selected <- reactive(getReactableState("de_table", "selected"))
output$de_volcano <- renderPlotly({
p <- rvalues$key() %>%
plot_ly(., color=I('black'), showlegend = FALSE) %>%
add_markers(
x = ~log2FoldChange,
y = ~ -log10(padj),
type = "scatter",
marker = list(opacity = 0.2),
text = ~ paste0(
"<b>", SYMBOL, "</b>",
"<br><i>GeneID</i>: ", gene_id,
"<br><i>Log2FC</i> = ", format(round(log2FoldChange, 2)),
"<br><i>p-value (adjusted)</i> = ", format(round(padj, 2))
),
hoverinfo = "text"
) %>%
config(
displaylogo = FALSE,
modeBarButtonsToRemove = c(
"zoomIn2d", "zoomOut2d", "pan2d", "resetScale2d",
"hoverCompareCartesian", "hoverClosestCartesian",
"select2d", "lasso2d", "zoom2d"),
toImageButtonOptions = list(
format = "svg",
width = 700,
height = 500,
filename = stringr::str_glue("magnetique_dge_volcano_{input$selected_contrast}")
)
) %>%
toWebGL() %>%
layout(
title = "Differentially expressed genes",
yaxis = list(title = '-log10(dge_padj)'),
xaxis = list(title = 'dge_log2fc')
)
if(length(prev_selected()) == 1) {
df <- rvalues$key() %>%
slice(prev_selected())
p <- add_trace(
p,
x = df[[1, "log2FoldChange"]],
y = ~ -log10(df[[1, "padj"]]),
type = "scatter",
mode = "markers",
color = I("red"),
inherit = FALSE)
}
p
})
output$dtu_volcano <- renderPlotly({
p <- rvalues$key() %>%
plot_ly(., color=I('black'), showlegend = FALSE) %>%
add_markers(
x = ~dtu_dif,
y = ~ -log10(dtu_pvadj),
type = "scatter",
marker = list(opacity = 0.2),
text = ~ paste0(
"<b>", SYMBOL, "</b>",
"<br><i>GeneID</i>: ", gene_id,
"<br><i>dif </i> = ", format(round(dtu_dif, 2)),
"<br><i>p-value (adjusted)</i> = ", format(round(dtu_pvadj, 2))
),
hoverinfo = "text"
) %>%
config(
displaylogo = FALSE,
modeBarButtonsToRemove = c(
"zoomIn2d", "zoomOut2d", "pan2d", "resetScale2d",
"hoverCompareCartesian", "hoverClosestCartesian",
"select2d", "lasso2d", "zoom2d"),
toImageButtonOptions = list(
format = "svg",
width = 700,
height = 500,
filename = stringr::str_glue("magnetique_dge_volcano_{input$selected_contrast}")
)) %>%
toWebGL() %>%
layout(
title = "Genes with differential transcript usage",
yaxis = list(title = '-log10(dtu_padj)'),
xaxis = list(title = 'dtu_dif')
)
if(length(prev_selected()) == 1) {
df <- rvalues$key() %>%
slice(prev_selected())
p <- add_trace(
p,
x = df[[1, "dtu_dif"]],
y = -log10(df[[1, "dtu_pvadj"]]),
type = "scatter",
mode = "markers",
color = I("red"),
inherit = FALSE)
}
p
})
observeEvent(prev_selected(), {
plotlyProxy("de_volcano", session) %>%
plotlyProxyInvoke("restyle", "marker.color", list('rgba(0,0,0,.10)'), 0)
plotlyProxy("dtu_volcano", session) %>%
plotlyProxyInvoke("restyle", "marker.color", list('rgba(0,0,0,.10)'), 0)
})
output$gene_counts <- renderPlotly({
i <- getReactableState("de_table", "selected")
validate(need(!is.na(i),
message = "Please select an entry from the table."
))
i <- rvalues$key()[[i, "gene_id"]]
counts <- rvalues$counts() %>%
filter(row_names == !!i) %>%
select(-row_names) %>%
mutate(n = n()) %>%
collect() %>%
pivot_longer(-n)
metadata <- rvalues$metadata() %>%
select(row_names, Etiology, Race, Age, Sex, SV1, SV2)
left_join(counts, metadata, by = c("name" = "row_names")) %>%
plot_ly(
.,
type = "box",
x = ~Etiology,
y = ~ log10(value),
boxpoints = "all",
jitter = 0.8,
pointpos = 0,
hoverinfo = 'text',
marker = list(opacity = 0.3),
text = ~ paste0(
"<br><i>Sex</i>: ", Sex,
"<br><i>Race</i> = ", Race,
"<br><i>Age</i> = ", Age,
"<br><i>SV1</i> = ", round(SV1, 2),
"<br><i>SV2</i> = ", round(SV2, 2)
),
color = ~factor(Etiology, levels = c("NFD", "DCM", "HCM")),
colors = c(I("steelblue"), I("gold"), I("forestgreen"))
) %>%
config(
displaylogo = FALSE,
modeBarButtonsToRemove = c(
"zoomIn2d", "zoomOut2d", "pan2d", "resetScale2d",
"hoverCompareCartesian", "hoverClosestCartesian",
"select2d", "lasso2d", "zoom2d"),
toImageButtonOptions = list(
format = "svg",
width = 700,
height = 500,
filename = stringr::str_glue("magnetique_gene_counts_{i}")
)
) %>%
layout(
title = "Gene counts",
xaxis = list(title = "", showticklabels = FALSE),
yaxis = list(title = "log10(normalized counts)"),
legend = list(orientation = "h")
)
})
output$gene_structure <- renderPlot({
i <- getReactableState("de_table", "selected")
validate(
need(!is.na(i),
message = "Please select an entry from the table."
)
)
dtu_tested <- rvalues$key()[[i, "dtu_pvadj"]]
validate(
need(!is.na(dtu_tested),
message = "Entry not tested for DTU."
)
)
i <- rvalues$key()[[i, "gene_id"]]
gtf <- con %>%
tbl("gtf") %>%
filter(gene_id == !!i) %>%
collect() %>%
GenomicRanges::GRanges(.)
gtf <- GenomicRanges::split(gtf, gtf$transcript_id)
suppressMessages({
plot_gene_structure(gtf) + labs(title='Gene structure') + theme(plot.title = element_text(size=18))
})
})
output$transcript_proportion <- renderPlotly({
i <- getReactableState("de_table", "selected")
validate(
need(!is.na(i),
message = "Please select an entry from the table."
)
)
dtu_tested <- rvalues$key()[[i, "dtu_pvadj"]]
validate(
need(!is.na(dtu_tested),
message = "Entry not tested for DTU."
)
)
i <- rvalues$key()[[i, "gene_id"]]
x <- con %>%
tbl("gene2tx") %>%
filter(gene_id == !!i) %>%
left_join(
tbl(con, "dtu_fit_proportions"),
by = (c("transcript_id" = "row_names"))
) %>%
collect()
x <- x %>% pivot_longer(
-c(gene_id, transcript_id),
names_to = "Run",
values_to = "proportion"
)
metadata <- rvalues$metadata() %>%
collect()
left_join(x, metadata, by = c("Run" = "Run")) %>%
plot_ly(
type = "box",
boxpoints = "all",
jitter = 1,
pointpos = 0,
y = ~transcript_id,
x = ~proportion,
hoverinfo = 'text',
text = ~ paste0(
"<br><i>Sex</i>: ", Sex,
"<br><i>Race</i> = ", Race,
"<br><i>Age</i> = ", Age,
"<br><i>SV1</i> = ", round(SV1, 2),
"<br><i>SV2</i> = ", round(SV2, 2)
),
color = ~factor(Etiology, levels = c("NFD", "DCM", "HCM")),
colors = c(I("steelblue"), I("gold"), I("forestgreen")),
orientation = 'h',
marker = list(opacity = 0.3)) %>%
layout(boxmode = "group",
title = "Transcript proportion",
yaxis = list(title = ""),
showlegend = FALSE) %>%
config(
displaylogo = FALSE,
modeBarButtonsToRemove = c(
"zoomIn2d", "zoomOut2d", "pan2d", "resetScale2d",
"hoverCompareCartesian", "hoverClosestCartesian",
"select2d", "lasso2d", "zoom2d"),
toImageButtonOptions = list(
format = "svg",
width = 700,
height = 500,
filename = stringr::str_glue("magnetique_transcript_proportion_{i}")
)
)
})
# enrichment map related content ---------------------------------------------
output$enrich_table <- renderReactable({
rvalues$res_enrich() %>%
rename(
c(
"id" = "gs_id",
"description" = "gs_description",
"expected" = "Expected",
"observed"= "gs_de_count",
"pval" = "gs_pvalue")) %>%
select(id, description, pval, expected, observed) %>%
arrange(pval) %>%
reactable(
.,
elementId = "enrich_table",
showPageSizeOptions = TRUE,
defaultPageSize = 5,
pageSizeOptions = c(5, 10, 25, 50),
searchable = FALSE,
striped = TRUE,
rownames = FALSE,
highlight = TRUE,
selection = "single",
onClick = "select",
wrap = FALSE,
rowStyle = list(cursor = "pointer"),
theme = reactableTheme(
stripedColor = "#f6f8fa",
highlightColor = "#f0f5f9",
cellPadding = "8px 12px",
rowSelectedStyle = list(backgroundColor = "#eee", boxShadow = "inset 2px 0 0 0 #FF0000")
),
defaultColDef = colDef(width = 70),
language = reactableLang(
filterPlaceholder = 'Filter'),
columns = list(
id = colDef(
html = TRUE,
filterable = TRUE,
cell = JS("function(cellInfo) {
const url = 'http://amigo.geneontology.org/amigo/term/' + cellInfo.value
return '<a href=\"' + url + '\" target=\"_blank\">' + cellInfo.value + '</a>'
}"),
minWidth = 100,
width = 120,
header = with_tooltip("gs_id", "Gene set ID and link to AMIGO db")),
description = colDef(
width = 250,
filterable = TRUE,
header = with_tooltip("gs_description", "Description for the gene set")),
pval = colDef(
filterable = TRUE,
filterMethod = JS("function(rows, columnId, filterValue) {
return rows.filter(function(row) {
return row.values[columnId] <= filterValue
})
}"),
header = with_tooltip("pval", "p-value for the TopGO enrichment test")),
expected = colDef(
header = with_tooltip("expec.", "Expected number of genes in the gene set")),
observed = colDef(
header = with_tooltip("obser.", "Number of genes observed in the gene set"))
)
)
})
emap_graph <- reactive({
res_enrich <- rvalues$res_enrich() %>% as.data.frame(.)
rownames(res_enrich) <- res_enrich$gs_id
res_de <- tbl(con, paste0("res_", local(input$selected_contrast))) %>%
collect()
res_de <- res_de %>%
filter(!is.na(SYMBOL)) %>%
arrange(-desc(padj)) %>%
select(gene_id, log2FoldChange, padj, SYMBOL)
res_de <- DESeq2::DESeqResults(
S4Vectors::DataFrame(res_de))
rownames(res_de) <- res_de$gene_id
res_de$pvalue <- res_de$padj
res_de$description <- ''
annotation_obj <- rvalues$annotation_obj()
emg <- GeneTonic::enrichment_map(
res_enrich,
res_de,
annotation_obj,
n_gs = input$number_genesets,
overlap_threshold = 0.1,
scale_edges_width = 200,
color_by = input$color_by
)
return(emg)
})
output$visnet_em <- renderVisNetwork({
validate(
need({ecount(emap_graph()) > 0},
message = paste0(
"No edges detected in the enrichment map. ",
"Please select a larger number of genesets to generate a full graph")
)
)
visNetwork::visIgraph(emap_graph()) %>%
visOptions(
highlightNearest = list(
enabled = TRUE,
degree = 1
),
nodesIdSelection = TRUE
) %>%
visExport(
name = "emap_network",
type = "pdf",
label = "Save enrichment map"
)
})
output$visnet_explanation <- renderUI({
validate(
need({ecount(emap_graph()) > 0},
message = ""
)
)
HTML(
paste0(
"If selecting <b>color</b> by <em>z_score</em>, red nodes display gene sets with positive values, ",
"while blue nodes represent gene sets with negative values. ",
"If showing the gene set <em>p-value</em>, darker colors represent gene sets with smaller ",
"p-values, indicating a more significant enrichment.",
"<br>The <b>size</b> of the node is representing the size of the gene set (number of genes ",
"assigned to it)."
)
)
})
output$emap_signature <- renderPlot({
i <- getReactableState("enrich_table", "selected")
validate(
need(!is.na(i),
message = "Please select a gene set from the table."
)
)
res_enrich <- rvalues$res_enrich() %>% as.data.frame(.)
sel_gs <- res_enrich[[i, "gs_id"]]
gs_description <- res_enrich[[i, "gs_description"]]