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app.R
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app.R
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#
# This is a ShinyActivePathways.
# A Shiny App runs ActivePathways and visualize data in enrichment map.
# You can run the application by clicking
# the 'Run App' button above.
#
library(shiny)
library(ActivePathways)
library(visNetwork) # For interactive Network
library(shinyWidgets) # For some fancy shiny component
library(shinyscreenshot)
library(shinyalert) # For dialogue
library(tools)
library(dplyr)
library(spsComps) # For error handling
source(file = "./enrichmentMap/enrichmentMap.R")
source(file = "./color/color.R")
source(file = "./documentation/documentation.R")
options(shiny.maxRequestSize = 100*1024^2) # define maximum upload file size
# Define UI for application that draws a histogram
ui <- fluidPage(
includeCSS("www/styles.css"), # include css file
# naviation bar
navbarPage(title = "ShinyActivePathways",
collapsible = TRUE,
tabPanel("Visualization",
# side bar
sidebarLayout(
sidebarPanel(
tabsetPanel(
tabPanel("Input Files", wellPanel(
tags$p(
"ShinyActivePathways can run ActivePathways method for
enrichment analysis and visualize result as enrichment map"
),
tags$p(
"Upload scoresFile and gmtFile, then click 'Run ActivePathways!'"
),
fileInput(inputId = "scoresFile",
label = "Score file",
accept = c(
".tsv",
".csv"
)
),
fileInput(inputId = "gmtFile",
label = "GMT file",
accept = c(
".gmt"
)
),
actionButton(inputId = "runPanel",
label = "Run ActivePathways!") %>%
bsTooltip("Run ActivePathways with Parameters", "bottom", bgcolor = "#219ebc"),
actionButton(inputId = "runEx",
label = "Run Example") %>%
bsTooltip("Run ActivePathways with an Example", "bottom", bgcolor = "#ffb703"),
# sliderInput(inputId = "size", "Label Size: ", min = 0, max = 30, value = 14),
)),
tabPanel("Adjust", wellPanel(
shinyWidgets::sliderTextInput(
inputId = "size",
label = "Font Size: ",
seq(from = 0, to = 28),
selected = 14
),
sliderInput(
inputId = "edgeCutoff",
label = "Edge cutoff (Similarity): ",
min = 0.25,
max = 1.0,
value = 0.25
),
numericInput("edgePrecise",
label = "Value:",
value = 0.25,
min = 0.25,
max = 1.0),
checkboxInput("highlightNeighbors",
label = "highlight neighbors"),
checkboxInput("navigationButtons",
label = "hide navigation buttons"),
checkboxInput("manipulation",
label = "enable manipulation")
),
),
tabPanel("Download", wellPanel(
downloadLink('downloadNetwork', 'Download network as .html'),
)
)
)
),
# Main panel
mainPanel(
wellPanel(
visNetworkOutput(outputId = "visNet",
width = "100%",
height = "500px"),
),
hr(),
verbatimTextOutput('geneList')
)
)
),
tabPanel("Documentation",
wellPanel(
tags$div(
HTML(documentHTML)
)
))
)
)
# Define server logic
server <- function(input, output, session) {
# Parameters for ActivePathways
observeEvent(input$runPanel, {
shinyalert::shinyalert(html = TRUE, text = tagList(
div(style="display:inline-block",
textInput(inputId = "cutoff", value = 0.1, label = "Cutoff")),
div(style="display:inline-block",
textInput(inputId = "significant", value = 0.05, label = "Significant")),
selectInput(inputId = "mergeMethod", choices = c("Brown", "Fisher"), selected = "Brown", label = "Merge Method"),
selectInput(inputId = "correctionMethod", choices = c("holm",
"fdr",
"hochberg",
"hommel",
"bonferroni",
"BH",
"BY",
"none"),
selected = "holm",
label = "Correction Method"),
sliderInput(inputId = "filterRange",
"Geneset Filter:",
min = 0, max = 1500,
value = c(5, 1000)),
hr(),
selectInput(inputId = "metric",
choices = c("jaccard", "overlap", "combined - 50% each"),
selected = "jaccard",
label = "Overlap measures"),
type = "input"
))
})
# Uploads score files
scores <- reactive({
print(input$scoresFile)
preTable <- NULL
if (file_ext(input$scoresFile$datapath) == "tsv") {
preTable <- read.table(file = input$scoresFile$datapath, header = TRUE, sep = '\t', row.names = 1)
} else if (file_ext(input$scoresFile$datapath) == "csv") {
preTable <- read.table(file = input$scoresFile$datapath, header = TRUE, sep = ',', row.names = 1)
}
data <- as.matrix(preTable)
data[is.na(data)] <- 1
return(data)
})
# Uploads gmt file
gmt <- reactive({
return(read.GMT(input$gmtFile$datapath))
})
enrichmentResult <- reactiveValues(data = NULL)
enrichNetwork <- reactiveValues(data = NULL)
# Render visNetwork
output$visNet <- renderVisNetwork({
if (! is.null(enrichNetwork$data)) {
enrichNetwork$data %>%
visInteraction(navigationButtons = TRUE, multiselect = TRUE) %>%
visEvents(select = "function(nodes) {
Shiny.onInputChange('current_node_id', nodes.nodes);
;}") # for display genes contained in each gene set
}
})
gmtDataRAW <- reactiveValues(value = NULL)
# For display genes contained in each gene set
selectedPathwayId <- reactiveValues(data = NULL)
observeEvent(input$current_node_id, {
print(paste("The selected node ID is:", input$current_node_id))
gmtData <- getDataFromGMT(gmtDataRAW$value)
selectedPathwayId$data <- gmtData$ids[gmtData$pathwayNames == input$current_node_id]
print(paste("The pathway ID is:", selectedPathwayId$data))
})
# Render information of gene list in text
output$geneList <- renderPrint({
if (! is.null(selectedPathwayId$data)) {
gmtDataRAW$value[[selectedPathwayId$data]]
}})
# Modify network properties
observe({
visNetworkProxy("visNet") %>%
visNodes(font = list(size = input$size)) %>% # for change font size of network
visOptions(highlightNearest = input$highlightNeighbors) %>% # for highlight neighbors
visInteraction(navigationButtons = !input$navigationButtons) %>%
visOptions(manipulation = input$manipulation)
# Download network as html files
output$downloadNetwork <- downloadHandler(
filename = function() {
paste('network-', Sys.Date(), '.html', sep='')
},
content = function(con) {
enrichNetwork$data %>% visSave(con)
}
)
})
# Run ActivePathways
fullResult <- reactiveValues(nodes = NULL, edges = NULL)
observeEvent(input$shinyalert, {
if (input$shinyalert) {
shinyCatch(
gmtDataRAW$value <- gmt()
, blocking_level = "error"
)
shinyCatch(
enrichmentResult$data <- ActivePathways(score = scores(),
gmt = gmt(),
cutoff = as.numeric(input$cutoff),
significant = as.numeric(input$significant),
merge.method = input$mergeMethod,
correction.method = input$correctionMethod,
geneset.filter = input$filterRange)
, blocking_level = "error")
}
g <- NULL
shinyCatch(
g <- plotEnrichmentMap(gmt(),
enrichmentResult$data,
algorithm = input$metric,
similarityCutoff = 0.25,
pvalueCutoff = NULL,
k = 0.5)
, blocking_level = "error")
visigraph <- visNetwork::visIgraph(g)
nodes <- visigraph$x$nodes
nodes$color <- getColors(enrichmentResult$data)
edges <- visigraph$x$edges
edges$id <- paste0("e", seq_along(edges$from))
edges$color <- rgb(137,207,240, max = 255)
fullResult$nodes <- nodes
fullResult$edges <- edges
enrichNetwork$data <- visNetwork(nodes, edges) %>%
visIgraphLayout() %>%
visExport(type = "png", name = "export-network",
float = "left", label = "Save network", style= "")
})
# Hardcoded example
observeEvent(input$runEx, {
nodes <- data.frame(id = c("DAP12 signaling",
"Axon guidance",
"Signaling by EGFR",
"Cellular Senescence"))
nodes$size <- c(21.90, 31.75, 22.30, 13.80)
nodes$color <- c("#FF0000", "#FFFFB3", "#FF6D00", "#FF2400")
nodes$label <- c("DAP12 signaling",
"Axon guidance",
"Signaling by EGFR",
"Cellular Senescence")
nodes$x <- c(-0.86622341, -1.00000000, -0.71840501, 0.91650067)
nodes$y <- c(-0.5461513 -0.3337750 -0.4780640 -1.0000000)
edges <- data.frame(from = c("DAP12 signaling",
"DAP12 signaling",
"Axon guidance"
))
edges$to <- c("Axon guidance",
"Signaling by EGFR",
"Signaling by EGFR"
)
edges$weight <- c(0.4111283, 0.8952880, 0.4039634)
edges$width <- c(0.8222566, 1.7905759, 0.8079268)
edges$id <- paste0("e", seq_along(edges$from))
edges$color <- rgb(137,207,240, max = 255)
fullResult$nodes <- nodes
fullResult$edges <- edges
enrichNetwork$data <- visNetwork(nodes, edges) %>%
visIgraphLayout() %>%
visExport(type = "png", name = "export-network",
float = "left", label = "Save network", style= "")
gmtDataRAW$value <- list()
lstItem1 <- list()
lstItem1$id <- "REAC:2424491"
lstItem1$name <- "DAP12 signaling"
lstItem1$genes <- c("IL17RD", "PSMC1", "PDGFRB", "PSMD14", "TNRC6C",
"CD80", "DUSP10", "(Not showing full list for example)")
lstItem2 <- list()
lstItem2$id <- "REAC:177929"
lstItem2$name <- "Signaling by EGFR"
lstItem2$genes <- c("ADCY3", "HRAS", "PSMC4", "TLN1", "MLST8", "THEM4",
"LAMTOR2", "CALM3", "RASGRF1", "DUSP7", "PSMC2",
"(Not showing full list for example)")
lstItem3 <- list()
lstItem3$id <- "REAC:422475"
lstItem3$name <- "Axon guidance"
lstItem3$genes <- c("SEMA3E", "PSME4", "FGF10", "TIAM1", "RGMA", "JAK1",
"CD72", "GRB7", "COL6A5", "PSMC2", "SRGAP2", "LAMTOR2",
"(Not showing full list for example)")
lstItem4 <- list()
lstItem4$id <- "REAC:2559583"
lstItem4$name <- "Cellular Senescence"
lstItem4$genes <- c("E2F3", "MDM4", "MDM2", "HIST3H3", "CDC27", "CBX2",
"ACD", "CDK2", "CBX8", "KDM6B", "TNRC6B",
"(Not showing full list for example)")
gmtLst <- list()
gmtLst$"REAC:2424491" <- lstItem1
gmtLst$"REAC:177929" <- lstItem2
gmtLst$"REAC:422475" <- lstItem3
gmtLst$"REAC:2559583" <- lstItem4
gmtDataRAW$value <- gmtLst
})
# edge Cutoff logic
observe({
updateSliderInput(
session = session,
inputId = "edgeCutoff",
value = input$edgePrecise
)
})
observe({
updateSliderInput(
session = session,
inputId = "edgePrecise",
value = input$edgeCutoff
)
})
observe({
filteredResult <- fullResult$edges[fullResult$edges$weight < input$edgeCutoff, ]
print(filteredResult)
filteredEdges <- filteredResult$id
hiddenEdges <- fullResult$edges[! fullResult$edges$id %in% filteredEdges,]
if (!is.null(filteredResult) & !is.null(filteredEdges)) {
visRemoveEdges(visNetworkProxy("visNet"), id = filteredEdges)
visUpdateEdges(visNetworkProxy("visNet"), edges = hiddenEdges)
}
})
}
# Run the application
shinyApp(ui = ui, server = server)