R/start_GUI.R
In LucaGiudice/propaGUIation: Gui for Propagation Visualization
Defines functions
start_GUI
Documented in
start_GUI
#' This function starts a shiny gui for the visualization of propagation results
#'
#' @param net1 igraph object to visualize
#' @param ann_net_b dataframe, specifies the genes positions (chromosome, start
#' and end position)
#' @param chr_len dataframe, specifies the chromosomes (first column) and their length
#' (second column)
#' @param example boolean, show 5 genes to select as an example
#'
#' @return NULL
#' @export
#'
#' @import shiny
#' @import shinydashboard
#' @import shinyjs
#' @import RCy3
#' @import visNetwork
#' @import plotfunctions
#' @import fields
#' @import DT
#' @import spam
#' @import dplyr
#' @import igraph
#' @import plyr
#' @import grDevices
#' @import graphics
#' @import stats
#'
start_GUI = function(net1, ann_net_b, chr_len, example=FALSE){
#index annotated genes to chromosomes
rownames(chr_len)=chr_len$chrom
index_all=list()
for (i in c(1:19,"X","Y")){
index_all[[i]]=which(ann_net_b[,"chr"] %in% paste("chr",i,sep=""))
}
names(index_all)=paste("chr",names(index_all),sep="")
if(example){
for(i in 1:length(index_all)){
index_all[[i]]=seq(1,min(dim(ann_net_b)[1],5))
}
}
#Get connected components
dg<-decompose.graph(net1)
length_dg=1:length(dg)
name_in_dg=list()
for (i in 1:length(dg)){
length_dg[i]=length(V(dg[[i]]))
name_in_dg[[i]]=igraph::get.vertex.attribute(dg[[i]],"name")
}
if(sum(igraph::get.vertex.attribute(net1)$shape == "square") > 0){
wp <- wellPanel(
h3("Legend",style="color:#0066CC"),
fluidRow(
column(12,h5(tags$b("Node's shape: "))),
column(6,h5(tags$b("Genes")),icon("fas fa-circle")),
column(6,h5(tags$b("Fragments")),icon("fas fa-square"),style="height:100px")
),
fluidRow(
column(12,h5(tags$b("Edge's color: "))),
column(6,h5(tags$b("Gene-fragment or gene-gene connection: orange")), style="color:#E96928"),
column(6,h5(tags$b("Fragment-fragment connection: purple")),style="color:#B616DE")
),
br(),
dataTableOutput("legend")
)
}
else {
wp <- wellPanel(
h3("Legend",style="color:#0066CC"),
fluidRow(
column(12,h5(tags$b("Node's shape: "))),
column(6,h5(tags$b("Genes")),icon("fas fa-circle")),
),
fluidRow(
column(12,h5(tags$b("Edge's color: "))),
column(6,h5(tags$b("Gene-gene connection: orange")), style="color:#E96928"),
),
br(),
dataTableOutput("legend")
)
}
ui <- dashboardPage(
dashboardHeader(
title=span("Visualization tool"),
tags$li(class = "dropdown",
tags$style(".main-header {max-height: 80px}"),
tags$style(".main-header .logo {height: 60px;}"))
),
dashboardSidebar(
fluidRow(
column(
width = 12,
selectInput("chr", shiny::HTML("<p><span style='color: blue'>Select nodes by chromosome</span></p>"),choices =names(index_all), multiple = FALSE),
sliderInput( "region", shiny::HTML("<p><span style='color: blue'>Select nodes by genome region</span></p>"),min=1,max=195456987,step=10000,value=c(1,195456987)),
selectizeInput(
'node', shiny::HTML("<p><span style='color: blue'>Select or type node</span></p>"), choices = c("node1","node2"),
options = list(maxOptions = 2,placeholder = 'Please select an option below',
onInitialize = I('function() { this.setValue(""); }'))
),
numericInput("dist", shiny::HTML("<p><span style='color: blue'>Distance from selected node</span></p>"), 0, min = 0, max = 100),
br(),
actionButton("button","Search", style="background-color:#0066CC; color:#FFF; border-color: #004C99")
)
)
),
dashboardBody(
tags$head(tags$style(HTML('.content-wrapper, .right-side {
background-color: #E2ECEB}
.skin-blue .main-sidebar {
background-color: #C2CEFF;
}
'))),
useShinyjs(),
fluidRow(class="myRow",
column(
width = 9,
visNetworkOutput("network")#,
#div(style = "height:1000px")
),
column(width=3, fluid=FALSE,
plotOutput("legendG")#,
#div(style = "height:1000px")
)
),
checkboxInput("relativebox","Scale colours based by only this subnetwork", value = FALSE, width = NULL),
fluidRow(
column(1,actionButton("morebutton","More", style="background-color:#0066CC; color:#FFF; border-color: #004C99", offset=0)),
column(1,actionButton("lessbutton","Less", style="background-color:#0066CC; color:#FFF; border-color: #004C99")),
column(3,actionButton("cys","Open in cytoscape", style="background-color:#0066CC; color:#FFF; border-color: #004C99"),offset = 5),
column(2,downloadButton("export",style="background-color:#0066CC; color:#FFF; border-color: #004C99"))
),
br(),
#legend space
wp
)
)
server <- function(input, output, session) {
value<-reactiveVal(NULL)
observeEvent(input$chr,{
cat("observeEvent chr \n")
value_max=chr_len[input$chr,]$length
element<<-ann_net_b[index_all[[input$chr]],]
updateSliderInput(session,"region",max=value_max,value = c(1,value_max),min = 1)
})
observeEvent(input$region,{
cat("observeEvent region \n")
element_pos<-ifelse((element[,3]>=input$region[1] & element[,3]<=input$region[2]) |
(element[,4]>=input$region[1] & element[,4]<=input$region[2]),TRUE,FALSE)
element_select<-element[element_pos,1]
updateSelectizeInput(session, 'node', choices = element_select, server = TRUE,options = list(maxOptions = length(element_select)))
})
#find the connected component to which the node belongs to...
observeEvent(input$node, {
cat("observeEvent node \n")
if (input$node == ""){
return()
}
print(input$node)
for (i in 1:length(dg)) {
if (input$node %in% name_in_dg[[i]]){
comp<-dg[[i]]
break
}
}
print(comp)
#...and set the max distance based on the result
max=max(distances(comp,v=input$node, V(comp), weights=NULL))
cat("node max:");print(max);cat("\n")
updateNumericInput(session, "dist",value = 0, max = max)
})
#reaction to search button
observeEvent(input$button, {
cat("observeEvent search button \n")
value_dist<<-input$dist
#generate the graph
subnet=make_ego_graph(net1, order = input$dist, nodes = input$node, mode = "all", mindist = 0)
plot_gr<<-subnet[[1]]
plot_gr<<-fun2(plot_gr)
#vertex_attr(plot_gr,"color",which(V(plot_gr)$name==input$node))<-"#00FF00"
dati<-toVisNetworkData(plot_gr,idToLabel = TRUE)
newValue=dati
value(newValue)
})
#reaction to more button
observeEvent(input$morebutton, {
cat("observeEvent more button \n")
value_dist<<-value_dist+1
cat("value_dist:",value_dist,"\n")
cat("input node:");print(input$node);cat("\n")
#generate the graph
subnet=make_ego_graph(net1, order = value_dist, nodes = input$node, mode = "all", mindist = 0)
plot_gr<<-subnet[[1]]
plot_gr<<-fun2(plot_gr)
dati<-toVisNetworkData(plot_gr,idToLabel = TRUE)
newValue=dati
value(newValue)
})
#reaction to less button
observeEvent(input$lessbutton, {
cat("observeEvent less button \n")
value_dist<<-value_dist-1
if(value_dist<0){
value_dist<<-0
}
#generate the graph
subnet=make_ego_graph(net1, order = value_dist, nodes = input$node, mode = "all", mindist = 0)
plot_gr<<-subnet[[1]]
plot_gr<<-fun2(plot_gr)
dati<-toVisNetworkData(plot_gr,idToLabel = TRUE)
newValue=dati
value(newValue)
})
#visualization of the visNetowrk
output$network <- renderVisNetwork({
cat("observeEvent renderVisNetwork \n")
if(is.null(value())){
return()
}
if (input$relativebox==TRUE) {
data=value()
data$nodes$color=value()$nodes$color_rel
data$nodes$color_rel=value()$nodes$color
} else {
data=value()
}
data$nodes$color=replace(data$nodes$color,which(data$nodes$id==input$node),"#00FF00")
prv=data$nodes$propagation
qs=quantile(prv,probs = c(0,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1))
for(k in 1:length(qs)){
if(k==1){
qs_names=paste(qs[k],sep="-")
}else{
new_name=paste(qs[k-1],qs[k],sep="-")
qs_names=c(qs_names,new_name)
}
}
map=data.frame(indx=seq(1,11),qs_names,stringsAsFactors = F)
propagation_ranges=findInterval(prv, qs)
propagation_ranges=plyr::mapvalues(propagation_ranges,from=map$indx,to=map$qs_names,warn_missing = F)
data$nodes$propagation_ranges=propagation_ranges
#creation of the visNetwork object
save(data,file="data.rda")
vis<<-visNetwork(nodes = data$nodes, edges =data$edges, width = "auto", height = "auto")%>%
visNodes( font = list("color"="#000",size=15),size=20,) %>%
visEdges(length=150, width = 2, smooth = T) %>%
visLayout(randomSeed = 250) %>%
visEvents(stabilizationIterationsDone="function () {this.setOptions( { physics: false } );}") %>%
visPhysics(maxVelocity = 50, minVelocity = 1) %>%
visOptions(highlightNearest = list(enabled = T, hover = T),
selectedBy = list(variable = "propagation_ranges" , multiple=T, sort=T, main="Select by propagation ranges",
style = 'width: 220px; height: 26px;
background: #f8f8f8;
color: darkblue;
border:none;
outline:none;'))
})
#visualization of the reactive sidebar legend
output$legendG=renderPlot({
cat("observeEvent renderPlot \n")
par(bg="#E2ECEB")
emptyPlot(0,0,axes=F)
if(is.null(value())){
return()
}
if(input$relativebox==TRUE) {
if (length(value()$nodes$propagation)==1) {
legend("bottomright", bty = "n", fill=value()$nodes$color_rel,legend=round(value()$nodes$propagation, digits=2), border = 'black',cex = 1.2)
} else {
zlim=c(round(min(value()$nodes$propagation),digits=2),round(max(value()$nodes$propagation), digits=2))
my_palette = colorRampPalette(c('white','orange1'))
image.plot(legend.only=T, horizontal=F, legend.shrink=0.5, legend.width=0.65, col= my_palette(5000), zlim=zlim, axes=F,
axis.args=list(at=zlim, labels=zlim),smallplot=c(0.1,0.2,0.1,0.9))
}
} else {
zlim=c(round(min(V(net1)$propagation),digits=2),round(max(V(net1)$propagation),digits=2))
my_palette = colorRampPalette(c('white','orange1'))
image.plot(legend.only=T, horizontal=F, legend.shrink=0.5, legend.width=0.65, col= my_palette(5000), zlim=zlim, axes=F,
axis.args=list(at=zlim, labels=zlim),smallplot=c(0.1,0.2,0.1,0.9))
}
})
#button to open the graph in cytoscape
observeEvent(input$cys,{
cat("observeEvent cys \n")
cytoscapePing()
createNetworkFromIgraph(plot_gr,"myIgraph")
})
#download network
output$export <- downloadHandler(
filename = "Network.html",
content = function(con) {
visSave(vis, con)
})
#output of the complete legend
output$legend <- renderDataTable({
if(input$button) {
data_leg<-value()$nodes
cols=c("label","shape","expr","propagation","color","color_rel","title","id")
datatable(data_leg[,cols],options=list(columnDefs=list(list(visible=F,targets=c(1,2,7,8)))),colnames =c("Starting expression"="expr", "Propagation"="propagation", "Color based on the global network"="color", "Color based on the subnetwork"="color_rel")) %>%
formatStyle (columns = "Color based on the global network", backgroundColor=styleEqual(data_leg$color ,as.character(data_leg$color)), color=styleEqual(data_leg$color ,as.character(data_leg$color))) %>%
formatStyle (columns = "Color based on the subnetwork", backgroundColor=styleEqual(data_leg$color_rel ,as.character(data_leg$color_rel)), color=styleEqual(data_leg$color_rel ,as.character(data_leg$color_rel)))
}
})
}
shiny::shinyApp(ui, server)
}
LucaGiudice/propaGUIation documentation built on Dec. 17, 2021, 1:13 a.m.
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Defines functions start_GUI
Documented in start_GUI
#' This function starts a shiny gui for the visualization of propagation results
#'
#' @param net1 igraph object to visualize
#' @param ann_net_b dataframe, specifies the genes positions (chromosome, start
#' and end position)
#' @param chr_len dataframe, specifies the chromosomes (first column) and their length
#' (second column)
#' @param example boolean, show 5 genes to select as an example
#'
#' @return NULL
#' @export
#'
#' @import shiny
#' @import shinydashboard
#' @import shinyjs
#' @import RCy3
#' @import visNetwork
#' @import plotfunctions
#' @import fields
#' @import DT
#' @import spam
#' @import dplyr
#' @import igraph
#' @import plyr
#' @import grDevices
#' @import graphics
#' @import stats
#'
start_GUI = function(net1, ann_net_b, chr_len, example=FALSE){
#index annotated genes to chromosomes
rownames(chr_len)=chr_len$chrom
index_all=list()
for (i in c(1:19,"X","Y")){
index_all[[i]]=which(ann_net_b[,"chr"] %in% paste("chr",i,sep=""))
}
names(index_all)=paste("chr",names(index_all),sep="")
if(example){
for(i in 1:length(index_all)){
index_all[[i]]=seq(1,min(dim(ann_net_b)[1],5))
}
}
#Get connected components
dg<-decompose.graph(net1)
length_dg=1:length(dg)
name_in_dg=list()
for (i in 1:length(dg)){
length_dg[i]=length(V(dg[[i]]))
name_in_dg[[i]]=igraph::get.vertex.attribute(dg[[i]],"name")
}
if(sum(igraph::get.vertex.attribute(net1)$shape == "square") > 0){
wp <- wellPanel(
h3("Legend",style="color:#0066CC"),
fluidRow(
column(12,h5(tags$b("Node's shape: "))),
column(6,h5(tags$b("Genes")),icon("fas fa-circle")),
column(6,h5(tags$b("Fragments")),icon("fas fa-square"),style="height:100px")
),
fluidRow(
column(12,h5(tags$b("Edge's color: "))),
column(6,h5(tags$b("Gene-fragment or gene-gene connection: orange")), style="color:#E96928"),
column(6,h5(tags$b("Fragment-fragment connection: purple")),style="color:#B616DE")
),
br(),
dataTableOutput("legend")
)
}
else {
wp <- wellPanel(
h3("Legend",style="color:#0066CC"),
fluidRow(
column(12,h5(tags$b("Node's shape: "))),
column(6,h5(tags$b("Genes")),icon("fas fa-circle")),
),
fluidRow(
column(12,h5(tags$b("Edge's color: "))),
column(6,h5(tags$b("Gene-gene connection: orange")), style="color:#E96928"),
),
br(),
dataTableOutput("legend")
)
}
ui <- dashboardPage(
dashboardHeader(
title=span("Visualization tool"),
tags$li(class = "dropdown",
tags$style(".main-header {max-height: 80px}"),
tags$style(".main-header .logo {height: 60px;}"))
),
dashboardSidebar(
fluidRow(
column(
width = 12,
selectInput("chr", shiny::HTML("<p><span style='color: blue'>Select nodes by chromosome</span></p>"),choices =names(index_all), multiple = FALSE),
sliderInput( "region", shiny::HTML("<p><span style='color: blue'>Select nodes by genome region</span></p>"),min=1,max=195456987,step=10000,value=c(1,195456987)),
selectizeInput(
'node', shiny::HTML("<p><span style='color: blue'>Select or type node</span></p>"), choices = c("node1","node2"),
options = list(maxOptions = 2,placeholder = 'Please select an option below',
onInitialize = I('function() { this.setValue(""); }'))
),
numericInput("dist", shiny::HTML("<p><span style='color: blue'>Distance from selected node</span></p>"), 0, min = 0, max = 100),
br(),
actionButton("button","Search", style="background-color:#0066CC; color:#FFF; border-color: #004C99")
)
)
),
dashboardBody(
tags$head(tags$style(HTML('.content-wrapper, .right-side {
background-color: #E2ECEB}
.skin-blue .main-sidebar {
background-color: #C2CEFF;
}
'))),
useShinyjs(),
fluidRow(class="myRow",
column(
width = 9,
visNetworkOutput("network")#,
#div(style = "height:1000px")
),
column(width=3, fluid=FALSE,
plotOutput("legendG")#,
#div(style = "height:1000px")
)
),
checkboxInput("relativebox","Scale colours based by only this subnetwork", value = FALSE, width = NULL),
fluidRow(
column(1,actionButton("morebutton","More", style="background-color:#0066CC; color:#FFF; border-color: #004C99", offset=0)),
column(1,actionButton("lessbutton","Less", style="background-color:#0066CC; color:#FFF; border-color: #004C99")),
column(3,actionButton("cys","Open in cytoscape", style="background-color:#0066CC; color:#FFF; border-color: #004C99"),offset = 5),
column(2,downloadButton("export",style="background-color:#0066CC; color:#FFF; border-color: #004C99"))
),
br(),
#legend space
wp
)
)
server <- function(input, output, session) {
value<-reactiveVal(NULL)
observeEvent(input$chr,{
cat("observeEvent chr \n")
value_max=chr_len[input$chr,]$length
element<<-ann_net_b[index_all[[input$chr]],]
updateSliderInput(session,"region",max=value_max,value = c(1,value_max),min = 1)
})
observeEvent(input$region,{
cat("observeEvent region \n")
element_pos<-ifelse((element[,3]>=input$region[1] & element[,3]<=input$region[2]) |
(element[,4]>=input$region[1] & element[,4]<=input$region[2]),TRUE,FALSE)
element_select<-element[element_pos,1]
updateSelectizeInput(session, 'node', choices = element_select, server = TRUE,options = list(maxOptions = length(element_select)))
})
#find the connected component to which the node belongs to...
observeEvent(input$node, {
cat("observeEvent node \n")
if (input$node == ""){
return()
}
print(input$node)
for (i in 1:length(dg)) {
if (input$node %in% name_in_dg[[i]]){
comp<-dg[[i]]
break
}
}
print(comp)
#...and set the max distance based on the result
max=max(distances(comp,v=input$node, V(comp), weights=NULL))
cat("node max:");print(max);cat("\n")
updateNumericInput(session, "dist",value = 0, max = max)
})
#reaction to search button
observeEvent(input$button, {
cat("observeEvent search button \n")
value_dist<<-input$dist
#generate the graph
subnet=make_ego_graph(net1, order = input$dist, nodes = input$node, mode = "all", mindist = 0)
plot_gr<<-subnet[[1]]
plot_gr<<-fun2(plot_gr)
#vertex_attr(plot_gr,"color",which(V(plot_gr)$name==input$node))<-"#00FF00"
dati<-toVisNetworkData(plot_gr,idToLabel = TRUE)
newValue=dati
value(newValue)
})
#reaction to more button
observeEvent(input$morebutton, {
cat("observeEvent more button \n")
value_dist<<-value_dist+1
cat("value_dist:",value_dist,"\n")
cat("input node:");print(input$node);cat("\n")
#generate the graph
subnet=make_ego_graph(net1, order = value_dist, nodes = input$node, mode = "all", mindist = 0)
plot_gr<<-subnet[[1]]
plot_gr<<-fun2(plot_gr)
dati<-toVisNetworkData(plot_gr,idToLabel = TRUE)
newValue=dati
value(newValue)
})
#reaction to less button
observeEvent(input$lessbutton, {
cat("observeEvent less button \n")
value_dist<<-value_dist-1
if(value_dist<0){
value_dist<<-0
}
#generate the graph
subnet=make_ego_graph(net1, order = value_dist, nodes = input$node, mode = "all", mindist = 0)
plot_gr<<-subnet[[1]]
plot_gr<<-fun2(plot_gr)
dati<-toVisNetworkData(plot_gr,idToLabel = TRUE)
newValue=dati
value(newValue)
})
#visualization of the visNetowrk
output$network <- renderVisNetwork({
cat("observeEvent renderVisNetwork \n")
if(is.null(value())){
return()
}
if (input$relativebox==TRUE) {
data=value()
data$nodes$color=value()$nodes$color_rel
data$nodes$color_rel=value()$nodes$color
} else {
data=value()
}
data$nodes$color=replace(data$nodes$color,which(data$nodes$id==input$node),"#00FF00")
prv=data$nodes$propagation
qs=quantile(prv,probs = c(0,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1))
for(k in 1:length(qs)){
if(k==1){
qs_names=paste(qs[k],sep="-")
}else{
new_name=paste(qs[k-1],qs[k],sep="-")
qs_names=c(qs_names,new_name)
}
}
map=data.frame(indx=seq(1,11),qs_names,stringsAsFactors = F)
propagation_ranges=findInterval(prv, qs)
propagation_ranges=plyr::mapvalues(propagation_ranges,from=map$indx,to=map$qs_names,warn_missing = F)
data$nodes$propagation_ranges=propagation_ranges
#creation of the visNetwork object
save(data,file="data.rda")
vis<<-visNetwork(nodes = data$nodes, edges =data$edges, width = "auto", height = "auto")%>%
visNodes( font = list("color"="#000",size=15),size=20,) %>%
visEdges(length=150, width = 2, smooth = T) %>%
visLayout(randomSeed = 250) %>%
visEvents(stabilizationIterationsDone="function () {this.setOptions( { physics: false } );}") %>%
visPhysics(maxVelocity = 50, minVelocity = 1) %>%
visOptions(highlightNearest = list(enabled = T, hover = T),
selectedBy = list(variable = "propagation_ranges" , multiple=T, sort=T, main="Select by propagation ranges",
style = 'width: 220px; height: 26px;
background: #f8f8f8;
color: darkblue;
border:none;
outline:none;'))
})
#visualization of the reactive sidebar legend
output$legendG=renderPlot({
cat("observeEvent renderPlot \n")
par(bg="#E2ECEB")
emptyPlot(0,0,axes=F)
if(is.null(value())){
return()
}
if(input$relativebox==TRUE) {
if (length(value()$nodes$propagation)==1) {
legend("bottomright", bty = "n", fill=value()$nodes$color_rel,legend=round(value()$nodes$propagation, digits=2), border = 'black',cex = 1.2)
} else {
zlim=c(round(min(value()$nodes$propagation),digits=2),round(max(value()$nodes$propagation), digits=2))
my_palette = colorRampPalette(c('white','orange1'))
image.plot(legend.only=T, horizontal=F, legend.shrink=0.5, legend.width=0.65, col= my_palette(5000), zlim=zlim, axes=F,
axis.args=list(at=zlim, labels=zlim),smallplot=c(0.1,0.2,0.1,0.9))
}
} else {
zlim=c(round(min(V(net1)$propagation),digits=2),round(max(V(net1)$propagation),digits=2))
my_palette = colorRampPalette(c('white','orange1'))
image.plot(legend.only=T, horizontal=F, legend.shrink=0.5, legend.width=0.65, col= my_palette(5000), zlim=zlim, axes=F,
axis.args=list(at=zlim, labels=zlim),smallplot=c(0.1,0.2,0.1,0.9))
}
})
#button to open the graph in cytoscape
observeEvent(input$cys,{
cat("observeEvent cys \n")
cytoscapePing()
createNetworkFromIgraph(plot_gr,"myIgraph")
})
#download network
output$export <- downloadHandler(
filename = "Network.html",
content = function(con) {
visSave(vis, con)
})
#output of the complete legend
output$legend <- renderDataTable({
if(input$button) {
data_leg<-value()$nodes
cols=c("label","shape","expr","propagation","color","color_rel","title","id")
datatable(data_leg[,cols],options=list(columnDefs=list(list(visible=F,targets=c(1,2,7,8)))),colnames =c("Starting expression"="expr", "Propagation"="propagation", "Color based on the global network"="color", "Color based on the subnetwork"="color_rel")) %>%
formatStyle (columns = "Color based on the global network", backgroundColor=styleEqual(data_leg$color ,as.character(data_leg$color)), color=styleEqual(data_leg$color ,as.character(data_leg$color))) %>%
formatStyle (columns = "Color based on the subnetwork", backgroundColor=styleEqual(data_leg$color_rel ,as.character(data_leg$color_rel)), color=styleEqual(data_leg$color_rel ,as.character(data_leg$color_rel)))
}
})
}
shiny::shinyApp(ui, server)
}
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