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Update shiny App
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@LamineTourelab
LamineTourelab authored Mar 13, 2024
1 parent 1b4eb83 commit ce941fd
Showing 1 changed file with 268 additions and 51 deletions.
319 changes: 268 additions & 51 deletions DataViz/app.R
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Original file line number Diff line number Diff line change
Expand Up @@ -2,18 +2,32 @@ library(shiny)
library(shinydashboard)
library(shinyjs)
library(ggplot2)
library(ggrepel)
library(plotly)
library(tidyverse)
library(dplyr)
library(factoextra)
library(FactoMineR)
library(enrichR)


data(diamonds, package = 'ggplot2')

listEnrichrSites()
setEnrichrSite("Enrichr")
websiteLive <- TRUE

dbs <- listEnrichrDbs()



# Ui

dashHeader = dashboardHeader(title = 'Simple Shinydashboard')
dashsidebar = dashboardSidebar(
sidebarMenu(
menuItem(
text = 'home',
text = 'Home',
tabName = 'hometab',
icon = icon('dashboard', style = "color:#E87722")),

Expand All @@ -22,6 +36,16 @@ dashsidebar = dashboardSidebar(
tabName = 'Graphstab',
icon = icon('chart-column', style = "color:#E87722")),

menuItem(
text = 'Statistics',
tabName = 'Statistics',
icon = icon('chart-column', style = "color:#E87722")),

menuItem(
text = 'DEA',
tabName = 'diffexp',
icon = icon('chart-column', style = "color:#E87722")),

menuItem(
text = 'File Explore',
tabName = 'FileExplore',
Expand Down Expand Up @@ -54,14 +78,14 @@ dashbody <- dashboardBody(
collapsible = TRUE,
title = 'Side bar',
status = 'primary', solidHeader = TRUE,
selectInput("dataset", "Choose a dataset:", choices = c("test-data", "own")),
fileInput(inputId = 'file1', 'ID, logFC, Pvalue',
selectInput("datasetgraph", "Choose a dataset:", choices = c("test-data", "own")),
fileInput(inputId = 'filegraph', 'Please upload a matrix file',
accept=c('text/csv', 'text/comma-separated-values,text/plain', '.csv')),
# Placeholder for input selection
selectInput('Vartoplot',
label = 'choose a variable',
choices = c('carat', 'depth', 'table', 'price'),
selected = 'price'),
fluidRow(
column(6, selectInput(inputId = 'Vartoplot', label = 'Waiting for data', choices = NULL)),
column(6, selectInput(inputId='VarColor',label = 'Waiting for data Color', choices = NULL))
),
# Choose number of bins
sliderInput(inputId='histbins',
label = 'please select a number of bins',
Expand All @@ -70,30 +94,12 @@ dashbody <- dashboardBody(
tabBox(width = 10,
tabPanel(title='Histogram',
#Placeholder for plot
plotOutput(outputId='Histplot'),
h4("Exporting the ggVolcanoR plot"),
fluidRow(

column(3,numericInput("width", "Width of PDF", value=10)),
column(3,numericInput("height", "Height of PDF", value=8)),
column(3),
column(3,style = "margin-top: 25px;",downloadButton('downloadPlot','Download PDF'))
),

fluidRow(
column(3,numericInput("width_png","Width of PNG", value = 1600)),
column(3,numericInput("height_png","Height of PNG", value = 1200)),
column(3,numericInput("resolution_PNG","Resolution of PNG", value = 144)),
column(3,style = "margin-top: 25px;",downloadButton('downloadPlotPNG','Download PNG'))
)
),
tabPanel(title='Volvano plot',
plotOutput(outputId = 'Volcanoplot'),

),

tabPanel(title='Density',
plotOutput(outputId='density')
plotlyOutput(outputId='Histplot')
# plotlyOutput(outputId='density')
),
tabPanel(title='Box Plot',
plotlyOutput(outputId='boxplot'),
plotlyOutput(outputId='corrplot')
),
tabPanel(title='Table',
DT::dataTableOutput(outputId = 'thetable')
Expand All @@ -103,6 +109,86 @@ dashbody <- dashboardBody(
)
)
),

# Statistical Analysis.
tabItem(tabName = 'Statistics',
fluidRow(
box(width = 2, height = 1170,
collapsible = TRUE,
title = 'Side bar',
status = 'primary', solidHeader = TRUE,
selectInput("dataset1", "Choose a dataset:", choices = c("test-data", "own")),
fileInput(inputId = 'fileuploadstats', 'Please upload a matrix file',
accept=c('text/csv', 'text/comma-separated-values,text/plain', '.csv')),
# Placeholder for input selection
fluidRow(
column(6, selectInput(inputId='Vartoplot1',label = 'Waiting for data',choices = NULL )),
column(6, selectInput(inputId='VarColor1',label = 'Waiting for data Color',choices = NULL ))
),
# Choose number of bins
sliderInput(inputId='histbins1',
label = 'please select a number of bins',
min = 5, max = 50, value = 30)
),
tabBox( width = 10,
tabPanel(title='PCA',
#Placeholder for plot
plotlyOutput(outputId='pca'),
),
tabPanel(title='Test',
#Placeholder for plot
plotlyOutput(outputId='stattest'),
),
tabPanel(title='Heatmap',
#Placeholder for plot
plotlyOutput(outputId='heatmap'),
),
tabPanel(title='Correlation plot',
#Placeholder for plot
plotlyOutput(outputId='Corrplot')
)
)
)

),
# Differential expression Analysis.
tabItem(tabName = 'diffexp',
fluidRow(
box(width = 2, height = 1170,
collapsible = TRUE,
title = 'Side bar',
status = 'primary', solidHeader = TRUE,
selectInput("datasetdiff", "Choose a dataset:", choices = c("test-data", "own")),
fileInput(inputId = 'filediff', 'ID, logFC, Pvalue',
accept=c('text/csv', 'text/comma-separated-values,text/plain', '.csv')),
# Placeholder for input selection
fluidRow(
column(6, selectInput(inputId='Vartoplotdiff',label = 'Waiting for data plot',choices = NULL )),
column(6, checkboxGroupInput(inputId='Vardatabasediff',label = 'Choose database',choices = dbs$libraryName ))
)
),
tabBox( width = 10,
tabPanel(title='Volcano plot',
textOutput("number_of_points"),
plotlyOutput(outputId = 'Volcanoplot')
),
tabPanel(title='Summary Table',
#Placeholder for plot
h2("Data table:"),
DT::dataTableOutput(outputId = 'summarytable'),
h2("The summary count table:"),
DT::dataTableOutput(outputId = 'summarytablecount')
),
tabPanel(title='Gene Set Enrichment',
#Placeholder for plot
textInput(inputId = 'textinputdiff', label = 'Paste a gene list'),
plotlyOutput(outputId='gsea'),
)
)
)

),
# Exploring file
tabItem(
tabName ='FileExplore',
fileInput(
Expand Down Expand Up @@ -187,50 +273,181 @@ ui <- dashboardPage(

server <- shinyServer(function(input, output, session)
{
output$Histplot <- renderPlot({
ggplot(diamonds, aes_string(x=input$Vartoplot)) + geom_histogram(bins = input$histbins)
# ============================================= Graph part results ====================================================== #

Datagraph <- reactive({
if(is.null(input$filegraph)){
return(NULL)
}
readr::read_csv(input$filegraph$datapath)

})

observe({
updateSelectInput(
inputId = 'Vartoplot',
session = session,
label = 'Please choose a variable',
choices = names(Datagraph())
)
})

observe({
updateSelectInput(
inputId = 'VarColor',
session = session,
label = 'Please choose a variable',
choices = names(Datagraph())
)
})

output$Histplot <- renderPlotly({
Hist <- ggplot(Datagraph(), aes_string(x=input$Vartoplot, fill=input$VarColor)) + geom_histogram(bins = input$histbins)
Hist %>%
ggplotly(tooltip = 'all')
})

Datav <- reactive({
if(is.null(input$file1)){
output$density <- renderPlotly({
Dens <- ggplot(Datagraph(), aes_string(x=input$Vartoplot)) + geom_density(fill='grey50')
Dens %>%
ggplotly(tooltip = 'all') %>%
layout(dragmode = "select")
})

output$boxplot <- renderPlotly({
Boxp <- ggplot(Datagraph(), aes_string(x=input$Vartoplot, fill=input$VarColor)) + geom_boxplot()
Boxp %>%
ggplotly(tooltip = 'all')
})

output$corrplot <- renderPlotly({
Corrp <- ggplot(Datagraph()) + geom_point(aes_string(input$Vartoplot , input$VarColor), position = "jitter")
Corrp %>%
ggplotly(tooltip = 'all')
})


output$thetable <- DT::renderDataTable({
DT::datatable(Datagraph(), rownames = FALSE)
},
server = TRUE)

# ============================================. Differntial Part results ========================================= #

Datadiff <- reactive({
if(is.null(input$filediff)){
return(NULL)
}
readr::read_csv(input$file1$datapath)
readr::read_csv(input$filediff$datapath)

})

observe({
updateSelectInput(
inputId = 'Vartoplotdiff',
session = session,
label = 'Please choose a variable',
choices = dbs$libraryName
)
})

output$Volcanoplot <- renderPlot({

output$number_of_points <- renderPrint({
dat <- data.frame(Datadiff())
dat$diffexpressed <- "NO"
dat$diffexpressed[dat$logFC > 0.6 & dat$Pvalue < 0.05] <- "UP"
dat$diffexpressed[dat$logFC < -0.6 & dat$Pvalue < 0.05] <- "DOWN"
dat$delabel <- NA
dat$delabel[dat$diffexpressed != "NO"] <- dat$ID[dat$diffexpressed != "NO"]
dat <- dat[order(dat$Pvalue),]
dat$logP <- -log10(dat$Pvalue)
total <- as.numeric(dim(dat)[1])
totalDown <- as.numeric(dim(dat[dat$diffexpressed=='DOWN',])[1])
totalNO <- as.numeric(dim(dat[dat$diffexpressed=='NO',])[1])
totalUP <- as.numeric(dim(dat[dat$diffexpressed=='UP',])[1])

cat('\n There are a total of ', total, ' where ' , totalDown, ' are dowregulated ', totalUP, ' are upregulated and ', totalNO, ' are none. ',
' which represents ' ,round(totalNO/total*100,2),'% of the data',sep='')
})

output$Volcanoplot <- renderPlotly({

Datadiff = data.frame(Datadiff())
# add a column of NAs
Datav = data.frame(Datav())
Datav$diffexpressed <- "NO"
Datadiff$diffexpressed <- "NO"
# if log2Foldchange > 0.6 and pvalue < 0.05, set as "UP"
Datav$diffexpressed[Datav$logFC > 0.6 & Datav$Pvalue < 0.05] <- "UP"
Datadiff$diffexpressed[Datadiff$logFC > 0.6 & Datadiff$Pvalue < 0.05] <- "UP"
# if log2Foldchange < -0.6 and pvalue < 0.05, set as "DOWN"
Datav$diffexpressed[Datav$logFC < -0.6 & Datav$Pvalue < 0.05] <- "DOWN"
Datadiff$diffexpressed[Datadiff$logFC < -0.6 & Datadiff$Pvalue < 0.05] <- "DOWN"

# Now write down the name of genes beside the points...
# Create a new column "delabel" to de, that will contain the name of genes differentially expressed (NA in case they are not)
Datav$delabel <- NA
Datav$delabel[Datav$diffexpressed != "NO"] <- Datav$ID[Datav$diffexpressed != "NO"]
Datadiff$delabel <- NA
Datadiff$delabel[Datadiff$diffexpressed != "NO"] <- Datadiff$ID[Datadiff$diffexpressed != "NO"]

volcano_gplot <- ggplot(data=Datav, aes(x=logFC, y=-log10(Pvalue), col=diffexpressed, label=delabel)) +
volcano_gplot <- ggplot(data=Datadiff, aes(x=logFC, y=-log10(Pvalue), col=diffexpressed, label=delabel)) +
geom_point() +
theme_minimal() +
geom_text_repel() +
scale_color_manual(values=c("blue", "black", "red")) +
# Add vertical lines for log2FoldChange thresholds, and one horizontal line for the p-value threshold
geom_vline(xintercept=c(-0.6, 0.6), col="red") +
geom_hline(yintercept=-log10(0.05), col="red")
volcano_gplot
volcano_gplot %>%
ggplotly(tooltip = 'all') %>%
layout(dragmode = "select")
})

output$density <- renderPlot({
ggplot(diamonds, aes_string(x=input$Vartoplot)) + geom_density(fill='grey50')
output$summarytable <- DT::renderDataTable({
dat <- data.frame(Datadiff())
dat$diffexpressed <- "NO"
dat$diffexpressed[dat$logFC > 0.6 & dat$Pvalue < 0.05] <- "UP"
dat$diffexpressed[dat$logFC < -0.6 & dat$Pvalue < 0.05] <- "DOWN"
dat$delabel <- NA
dat$delabel[dat$diffexpressed != "NO"] <- dat$ID[dat$diffexpressed != "NO"]

dat <- DT::datatable(dat)
dat
})

output$thetable <- DT::renderDataTable({
DT::datatable(diamonds, rownames = FALSE)
},
server = TRUE)
output$summarytablecount <- DT::renderDataTable({
dat <- data.frame(Datadiff())
dat$diffexpressed <- "NO"
dat$diffexpressed[dat$logFC > 0.6 & dat$Pvalue < 0.05] <- "UP"
dat$diffexpressed[dat$logFC < -0.6 & dat$Pvalue < 0.05] <- "DOWN"
dat$delabel <- NA
dat$delabel[dat$diffexpressed != "NO"] <- dat$ID[dat$diffexpressed != "NO"]
dat <- dat %>% count(diffexpressed)
DT::datatable(dat)
})

##### Enrichment

output$textinputdiff <- renderPrint({
input$textinputdiff
})

output$gsea <- renderPlotly({
listEnrichrSites()
setEnrichrSite("Enrichr")
websiteLive <- TRUE

dbs <- listEnrichrDbs()
dbs <- c("GO_Molecular_Function_2015", "GO_Cellular_Component_2015", "GO_Biological_Process_2015",
"Reactome_2015", "Reactome_2016", "OMIM_Disease", "MSigDB_Oncogenic_Signatures", "KEGG_2015",
"KEGG_2016", "GO_Biological_Process_2018", "Human_Phenotype_Ontology", "Cancer_Cell_Line_Encyclopedia",
"RNA-Seq_Disease_Gene_and_Drug_Signatures_from_GEO")
if (websiteLive) {
enriched <- enrichr(c("SFRP1", "RELN", "FLT1", "GPC3", "APOBEC3B", "CD47", "NTRK2", "TLR8",
"FGF10", "E2F1", "HBEGF", "SLC19A3", "DUSP6", "FOS", "GNG5"), input$Vardatabasediff)
}

plotEnrich(enriched[[input$Vartoplotdiff]], showTerms = 20, numChar = 50,
y = "Count", orderBy = "P.value", title = "Enrichment analysis with selected Modules using KEGG",
xlab = "Enriched pathways")
})
# ===================================================. Exploring file ==============================================#


theData <- reactive({
if(is.null(input$fileupload)){
Expand Down

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