inst/application/old/app15.R
In mjmccoy/REVAvis: What the Package Does (One Line, Title Case)
############################
## REVAvis v0.9 ##
## Author: Matt McCoy ##
## Date: February 3, 2020 ##
############################
# This is a Shiny web application that visualizes REVA output. You can run the application by clicking
# the 'Run App' button above.
# Load libraries
library(shiny)
library(ggplot2)
library(dplyr)
# library(plotly)
# library(DT) # overwrites shiny's renderDataTable and dataTableOutput to work properly
# Load functions
source(file = "../../R/read.input.files.R")
source(file = "../../R/chromPlot.R")
# source(file = "../../R/agg_chromPlot.R")
source(file = "../../R/ManhattanPlot.R")
source(file = "../../R/2DPlot.R")
# Define UI for application
ui <- navbarPage("REVA Visualization",
tabPanel("Data Input",
fluidRow(
# Input Condition 1 files:
column(4, wellPanel(
fileInput(
inputId = "condition1_files",
label = "Choose REVA Output Files for Condition 1",
multiple = TRUE,
accept = c(".tdv")
),
textInput(
inputId = "condition1_name",
label = "Name for Condition 1",
value = "Condition1"),
checkboxInput("condition1_norm", "RPM normalize", TRUE)
)),
# Output Condition 1 file names:
column(4,
tableOutput("condition1_files")
)
),
fluidRow(
# Input Condition 2 files:
column(4, wellPanel(
fileInput(
inputId = "condition2_files",
label = "Choose REVA Output Files for Condition 2",
multiple = TRUE,
accept = c(".tdv")
),
textInput(
inputId = "condition2_name",
label = "Name for Condition 2",
value = "Condition2"),
checkboxInput("condition2_norm", "RPM normalize", TRUE)
)),
# Outout Condition 2 file names:
column(4,
tableOutput("condition2_files")
)
),
fluidRow(
column(4,
submitButton("Submit")
)
)
),
tabPanel("Individual Plots",
fluidRow(
column(2,
uiOutput("render_ui_1"),
submitButton("Submit")
),
column(10,
plotOutput("condition1_chromPlot"),
uiOutput("render_download_condition1_chromPlot")
)
),
fluidRow(
column(2),
column(10,
plotOutput("condition2_chromPlot"),
uiOutput("render_download_condition2_chromPlot")
)
)
),
# tabPanel("Aggregate Plots",
# fluidRow(
# column(2,
# uiOutput("render_ui_2"),
# submitButton("Submit")
# ),
# column(10,
# plotOutput("agg_chromPlot")
# )
# )
# ),
tabPanel("Manhattan Plots",
fluidRow(
column(2,
uiOutput("render_ui_3"),
submitButton("Submit")
),
column(10,
plotOutput("condition1_ManhattanPlot"),
uiOutput("render_download_condition1_ManhattanPlot")
)
),
fluidRow(
column(2),
column(10,
plotOutput("condition2_ManhattanPlot"),
uiOutput("render_download_condition2_ManhattanPlot")
)
),
fluidRow(
column(2),
column(10,
plotOutput("ManhattanPlot_ratio"),
uiOutput("render_download_ManhattanPlot_ratio")
)
)
),
tabPanel("2D Plots",
fluidRow(
column(2,
uiOutput("render_ui_4"),
submitButton("Submit")
),
column(5,
plotOutput("TwoDPlot_plot"),
uiOutput("render_download_TwoDPlot_plot")
)
)
)
)
# Define server logic
server <- function(input, output) {
# Limit file size
options(shiny.maxRequestSize=10000*1024^2) # ~10 Gb
###############################
## Define reactive variables ##
###############################
# condition files
condition1_data <- reactive({
req(input$condition1_files)
read.input.files(
file.list = input$condition1_files,
condition = input$condition1_name,
normalized = input$condition1_norm
)
})
condition2_data <- reactive({
req(input$condition2_files)
read.input.files(
file.list = input$condition2_files,
condition = input$condition2_name,
normalized = input$condition2_norm)
})
# chr and feature values
vals <- reactiveValues()
observe({
vals$condition1_name <- input$condition1_name
vals$condition2_name <- input$condition2_name
vals$chr_1 <- as.factor(input$chr_1)
# vals$chr_2 <- as.factor(input$chr_2)
vals$chr_3 <- as.factor(input$chr_3)
vals$chr_4 <- as.factor(input$chr_4)
vals$feature_1 <- input$feature_1
# vals$feature_2 <- input$feature_2
vals$feature_3 <- input$feature_3
vals$feature_4 <- input$feature_4
vals$log_scale_1 <- input$log_scale_1
vals$log_scale_3 <- input$log_scale_3
vals$plot_height_1 <- input$plot_height_1
vals$plot_width_1 <- input$plot_width_1
# vals$plot_height_2 <- input$plot_height_2
# vals$plot_width_2 <- input$plot_width_2
vals$plot_height_3 <- input$plot_height_3
vals$plot_width_3 <- input$plot_width_3
vals$plot_height_4 <- input$plot_height_4
vals$plot_width_4 <- input$plot_width_4
})
####################
## Define outputs ##
####################
# condition file names
output$condition1_files <- renderTable({
out.table <- input$condition1_files[['name']]
if(is.null(out.table)){
return(NULL)
}
out.table <- as.data.frame(out.table)
names(out.table) <- input$condition1_name
return(out.table)
})
output$condition2_files <- renderTable({
out.table <- input$condition2_files[['name']]
if(is.null(out.table)){
return(NULL)
}
out.table <- as.data.frame(out.table)
names(out.table) <- input$condition2_name
return(out.table)
})
# Render UI
output$render_ui_1 <- renderUI({
list(
selectInput(
inputId = "chr_1",
label = "Chromosome name:",
choices = unique(as.character(condition1_data()$Chr))),
selectInput(
inputId = 'feature_1',
label = 'Feature',
choices = names(condition1_data())[5:(length(names(condition1_data())) - 1)]),
checkboxInput("log_scale_1", "log10(x + 1)", TRUE),
numericInput('plot_height_1', 'Download plot height (in)', 3,
min = 1, max = 48),
numericInput('plot_width_1', 'Download plot width (in)', 8,
min = 1, max = 48)
)
})
#
# output$render_ui_2 <- renderUI({
# list(
# selectInput(
# inputId = "chr_2",
# label = "Chromosome name:",
# choices = unique(as.character(condition1_data()$Chr))),
# selectInput(
# inputId = 'feature_2',
# label = 'Feature',
# choices = names(condition1_data())[5:(length(names(condition1_data())) - 1)]),
# checkboxInput("mean_se", "Mean + SE", TRUE)
# )
# })
output$render_ui_3 <- renderUI({
list(
selectInput(
inputId = "chr_3",
label = "Chromosome name:",
choices = unique(as.character(condition1_data()$Chr)),
multiple = T),
selectInput(
inputId = 'feature_3',
label = 'Feature',
choices = names(condition1_data())[5:(length(names(condition1_data())) - 1)]),
checkboxInput("log_scale_3", "log10(x + 1)", TRUE),
numericInput('plot_height_3', 'Download plot height (in)', 3,
min = 1, max = 48),
numericInput('plot_width_3', 'Download plot width (in)', 8,
min = 1, max = 48)
)
})
output$render_ui_4 <- renderUI({
list(
selectInput(
inputId = "chr_4",
label = "Chromosome name:",
choices = unique(as.character(condition1_data()$Chr)),
multiple = T),
selectInput(
inputId = 'feature_4',
label = 'Feature',
choices = names(condition1_data())[5:(length(names(condition1_data())) - 1)]),
numericInput('plot_height_4', 'Download plot height (in)', 3,
min = 1, max = 48),
numericInput('plot_width_4', 'Download plot width (in)', 8,
min = 1, max = 48)
)
})
###########
## Plots ##
###########
# condition1_chromPlot
condition1_chromPlot <- reactive({
req(vals$chr_1)
p <- chromPlot(
data = condition1_data(),
chr = vals$chr_1,
feature = vals$feature_1,
log_scale = vals$log_scale_1
)
})
output$condition1_chromPlot <- renderPlot({
print(condition1_chromPlot())
})
# condition2_chromPlot
condition2_chromPlot <- reactive({
req(vals$chr_1)
p <- chromPlot(
data = condition2_data(),
chr = vals$chr_1,
feature = vals$feature_1,
log_scale = vals$log_scale_1
)
})
output$condition2_chromPlot <- renderPlot({
print(condition2_chromPlot())
})
#
# # agg_chromPlot
# output$agg_chromPlot <- renderPlot({
# req(vals$chr_2)
# agg_chromPlot(
# data1 = condition1_data(),
# data2 = condition2_data(),
# chr = vals$chr_2,
# feature = vals$feature_2,
# mean_se = input$mean_se
# )
# })
# condition1_ManhattanPlot
condition1_ManhattanPlot <- reactive({
req(vals$chr_3)
p <- ManhattanPlot(
data = condition1_data(),
chr = vals$chr_3,
feature = vals$feature_3,
log_scale = input$log_scale_3
)
})
output$condition1_ManhattanPlot <- renderPlot({
print(condition1_ManhattanPlot())
})
# condition2_ManhattanPlot
condition2_ManhattanPlot <- reactive({
req(vals$chr_3)
p <- ManhattanPlot(
data = condition2_data(),
chr = vals$chr_3,
feature = vals$feature_3,
log_scale = input$log_scale_3
)
})
output$condition2_ManhattanPlot <- renderPlot({
print(condition2_ManhattanPlot())
})
# ManhattanPlot_ratio
ManhattanPlot_ratio <- reactive({
req(vals$chr_3)
p <- ManhattanPlot(
data = condition1_data(),
data2 = condition2_data(),
chr = vals$chr_3,
feature = vals$feature_3,
log_scale = input$log_scale_3,
condition1_name = input$condition1_name,
condition2_name = input$condition2_name
)
})
output$ManhattanPlot_ratio <- renderPlot({
print(ManhattanPlot_ratio())
})
# 2D Plot
TwoDPlot_plot <- reactive({
req(vals$chr_4)
p <- TwoDPlot(
data1 = condition1_data(),
data2 = condition2_data(),
chr = vals$chr_4,
feature = vals$feature_4,
condition1_name = input$condition1_name,
condition2_name = input$condition2_name
)
})
output$TwoDPlot_plot <- renderPlot({
print(TwoDPlot_plot())
})
# Download Plots
output$download_condition1_chromPlot <- downloadHandler(
filename = function() {
paste(
vals$condition1_name,
'-',
vals$chr_1,
'-',
Sys.Date(),
'.pdf',
sep=''
)
},
content = function(file) {
pdf(
file,
bg = "white",
useDingbats = F,
width = vals$plot_width_1,
height = vals$plot_height_1
)
print(condition1_chromPlot())
dev.off()
},
contentType = 'image/pdf'
)
output$download_condition2_chromPlot <- downloadHandler(
filename = function() {
paste(
vals$condition2_name,
'-',
vals$chr_1,
'-',
Sys.Date(),
'.pdf',
sep=''
)
},
content = function(file) {
pdf(
file,
bg = "white",
useDingbats = F,
width = vals$plot_width_1,
height = vals$plot_height_1
)
print(condition2_chromPlot())
dev.off()
},
contentType = 'image/pdf'
)
output$download_condition1_ManhattanPlot <- downloadHandler(
filename = function() {
paste(
vals$condition1_name,
'-',
"Manhattan",
'-',
Sys.Date(),
'.pdf',
sep=''
)
},
content = function(file) {
pdf(
file,
bg = "white",
useDingbats = F,
width = vals$plot_width_3,
height = vals$plot_height_3
)
print(condition1_ManhattanPlot())
dev.off()
},
contentType = 'image/pdf'
)
output$download_condition2_ManhattanPlot <- downloadHandler(
filename = function() {
paste(
vals$condition2_name,
'-',
"Manhattan",
'-',
Sys.Date(),
'.pdf',
sep=''
)
},
content = function(file) {
pdf(
file,
bg = "white",
useDingbats = F,
width = vals$plot_width_3,
height = vals$plot_height_3
)
print(condition2_ManhattanPlot())
dev.off()
},
contentType = 'image/pdf'
)
output$download_ManhattanPlot_ratio <- downloadHandler(
filename = function() {
paste(
vals$condition1_name,
'-',
vals$condition2_name,
'-',
"Manhattan",
'-',
Sys.Date(),
'.pdf',
sep=''
)
},
content = function(file) {
pdf(
file,
bg = "white",
useDingbats = F,
width = vals$plot_width_3,
height = vals$plot_height_3
)
print(ManhattanPlot_ratio())
dev.off()
},
contentType = 'image/pdf'
)
output$download_TwoDPlot_plot <- downloadHandler(
filename = function() {
paste(
vals$condition1_name,
'-',
vals$condition2_name,
'-',
"2DPlot",
'-',
Sys.Date(),
'.pdf',
sep=''
)
},
content = function(file) {
pdf(
file,
bg = "white",
useDingbats = F,
width = vals$plot_width_4,
height = vals$plot_height_4
)
print(TwoDPlot_plot())
dev.off()
},
contentType = 'image/pdf'
)
output$render_download_condition1_chromPlot <- renderUI({
req(vals$chr_1)
downloadButton("download_condition1_chromPlot", "Download plot")
})
output$render_download_condition2_chromPlot <- renderUI({
req(vals$chr_1)
downloadButton("download_condition2_chromPlot", "Download plot")
})
output$render_download_condition1_ManhattanPlot <- renderUI({
req(vals$chr_3)
downloadButton("download_condition1_ManhattanPlot", "Download plot")
})
output$render_download_condition2_ManhattanPlot <- renderUI({
req(vals$chr_3)
downloadButton("download_condition2_ManhattanPlot", "Download plot")
})
output$render_download_ManhattanPlot_ratio <- renderUI({
req(vals$chr_3)
downloadButton("download_ManhattanPlot_ratio", "Download plot")
})
output$render_download_TwoDPlot_plot <- renderUI({
req(vals$chr_4)
downloadButton("download_TwoDPlot_plot", "Download plot")
})
}
# Run the application
shinyApp(ui = ui, server = server)
mjmccoy/REVAvis documentation built on April 8, 2021, 8:11 p.m.
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############################
## REVAvis v0.9 ##
## Author: Matt McCoy ##
## Date: February 3, 2020 ##
############################
# This is a Shiny web application that visualizes REVA output. You can run the application by clicking
# the 'Run App' button above.
# Load libraries
library(shiny)
library(ggplot2)
library(dplyr)
# library(plotly)
# library(DT) # overwrites shiny's renderDataTable and dataTableOutput to work properly
# Load functions
source(file = "../../R/read.input.files.R")
source(file = "../../R/chromPlot.R")
# source(file = "../../R/agg_chromPlot.R")
source(file = "../../R/ManhattanPlot.R")
source(file = "../../R/2DPlot.R")
# Define UI for application
ui <- navbarPage("REVA Visualization",
tabPanel("Data Input",
fluidRow(
# Input Condition 1 files:
column(4, wellPanel(
fileInput(
inputId = "condition1_files",
label = "Choose REVA Output Files for Condition 1",
multiple = TRUE,
accept = c(".tdv")
),
textInput(
inputId = "condition1_name",
label = "Name for Condition 1",
value = "Condition1"),
checkboxInput("condition1_norm", "RPM normalize", TRUE)
)),
# Output Condition 1 file names:
column(4,
tableOutput("condition1_files")
)
),
fluidRow(
# Input Condition 2 files:
column(4, wellPanel(
fileInput(
inputId = "condition2_files",
label = "Choose REVA Output Files for Condition 2",
multiple = TRUE,
accept = c(".tdv")
),
textInput(
inputId = "condition2_name",
label = "Name for Condition 2",
value = "Condition2"),
checkboxInput("condition2_norm", "RPM normalize", TRUE)
)),
# Outout Condition 2 file names:
column(4,
tableOutput("condition2_files")
)
),
fluidRow(
column(4,
submitButton("Submit")
)
)
),
tabPanel("Individual Plots",
fluidRow(
column(2,
uiOutput("render_ui_1"),
submitButton("Submit")
),
column(10,
plotOutput("condition1_chromPlot"),
uiOutput("render_download_condition1_chromPlot")
)
),
fluidRow(
column(2),
column(10,
plotOutput("condition2_chromPlot"),
uiOutput("render_download_condition2_chromPlot")
)
)
),
# tabPanel("Aggregate Plots",
# fluidRow(
# column(2,
# uiOutput("render_ui_2"),
# submitButton("Submit")
# ),
# column(10,
# plotOutput("agg_chromPlot")
# )
# )
# ),
tabPanel("Manhattan Plots",
fluidRow(
column(2,
uiOutput("render_ui_3"),
submitButton("Submit")
),
column(10,
plotOutput("condition1_ManhattanPlot"),
uiOutput("render_download_condition1_ManhattanPlot")
)
),
fluidRow(
column(2),
column(10,
plotOutput("condition2_ManhattanPlot"),
uiOutput("render_download_condition2_ManhattanPlot")
)
),
fluidRow(
column(2),
column(10,
plotOutput("ManhattanPlot_ratio"),
uiOutput("render_download_ManhattanPlot_ratio")
)
)
),
tabPanel("2D Plots",
fluidRow(
column(2,
uiOutput("render_ui_4"),
submitButton("Submit")
),
column(5,
plotOutput("TwoDPlot_plot"),
uiOutput("render_download_TwoDPlot_plot")
)
)
)
)
# Define server logic
server <- function(input, output) {
# Limit file size
options(shiny.maxRequestSize=10000*1024^2) # ~10 Gb
###############################
## Define reactive variables ##
###############################
# condition files
condition1_data <- reactive({
req(input$condition1_files)
read.input.files(
file.list = input$condition1_files,
condition = input$condition1_name,
normalized = input$condition1_norm
)
})
condition2_data <- reactive({
req(input$condition2_files)
read.input.files(
file.list = input$condition2_files,
condition = input$condition2_name,
normalized = input$condition2_norm)
})
# chr and feature values
vals <- reactiveValues()
observe({
vals$condition1_name <- input$condition1_name
vals$condition2_name <- input$condition2_name
vals$chr_1 <- as.factor(input$chr_1)
# vals$chr_2 <- as.factor(input$chr_2)
vals$chr_3 <- as.factor(input$chr_3)
vals$chr_4 <- as.factor(input$chr_4)
vals$feature_1 <- input$feature_1
# vals$feature_2 <- input$feature_2
vals$feature_3 <- input$feature_3
vals$feature_4 <- input$feature_4
vals$log_scale_1 <- input$log_scale_1
vals$log_scale_3 <- input$log_scale_3
vals$plot_height_1 <- input$plot_height_1
vals$plot_width_1 <- input$plot_width_1
# vals$plot_height_2 <- input$plot_height_2
# vals$plot_width_2 <- input$plot_width_2
vals$plot_height_3 <- input$plot_height_3
vals$plot_width_3 <- input$plot_width_3
vals$plot_height_4 <- input$plot_height_4
vals$plot_width_4 <- input$plot_width_4
})
####################
## Define outputs ##
####################
# condition file names
output$condition1_files <- renderTable({
out.table <- input$condition1_files[['name']]
if(is.null(out.table)){
return(NULL)
}
out.table <- as.data.frame(out.table)
names(out.table) <- input$condition1_name
return(out.table)
})
output$condition2_files <- renderTable({
out.table <- input$condition2_files[['name']]
if(is.null(out.table)){
return(NULL)
}
out.table <- as.data.frame(out.table)
names(out.table) <- input$condition2_name
return(out.table)
})
# Render UI
output$render_ui_1 <- renderUI({
list(
selectInput(
inputId = "chr_1",
label = "Chromosome name:",
choices = unique(as.character(condition1_data()$Chr))),
selectInput(
inputId = 'feature_1',
label = 'Feature',
choices = names(condition1_data())[5:(length(names(condition1_data())) - 1)]),
checkboxInput("log_scale_1", "log10(x + 1)", TRUE),
numericInput('plot_height_1', 'Download plot height (in)', 3,
min = 1, max = 48),
numericInput('plot_width_1', 'Download plot width (in)', 8,
min = 1, max = 48)
)
})
#
# output$render_ui_2 <- renderUI({
# list(
# selectInput(
# inputId = "chr_2",
# label = "Chromosome name:",
# choices = unique(as.character(condition1_data()$Chr))),
# selectInput(
# inputId = 'feature_2',
# label = 'Feature',
# choices = names(condition1_data())[5:(length(names(condition1_data())) - 1)]),
# checkboxInput("mean_se", "Mean + SE", TRUE)
# )
# })
output$render_ui_3 <- renderUI({
list(
selectInput(
inputId = "chr_3",
label = "Chromosome name:",
choices = unique(as.character(condition1_data()$Chr)),
multiple = T),
selectInput(
inputId = 'feature_3',
label = 'Feature',
choices = names(condition1_data())[5:(length(names(condition1_data())) - 1)]),
checkboxInput("log_scale_3", "log10(x + 1)", TRUE),
numericInput('plot_height_3', 'Download plot height (in)', 3,
min = 1, max = 48),
numericInput('plot_width_3', 'Download plot width (in)', 8,
min = 1, max = 48)
)
})
output$render_ui_4 <- renderUI({
list(
selectInput(
inputId = "chr_4",
label = "Chromosome name:",
choices = unique(as.character(condition1_data()$Chr)),
multiple = T),
selectInput(
inputId = 'feature_4',
label = 'Feature',
choices = names(condition1_data())[5:(length(names(condition1_data())) - 1)]),
numericInput('plot_height_4', 'Download plot height (in)', 3,
min = 1, max = 48),
numericInput('plot_width_4', 'Download plot width (in)', 8,
min = 1, max = 48)
)
})
###########
## Plots ##
###########
# condition1_chromPlot
condition1_chromPlot <- reactive({
req(vals$chr_1)
p <- chromPlot(
data = condition1_data(),
chr = vals$chr_1,
feature = vals$feature_1,
log_scale = vals$log_scale_1
)
})
output$condition1_chromPlot <- renderPlot({
print(condition1_chromPlot())
})
# condition2_chromPlot
condition2_chromPlot <- reactive({
req(vals$chr_1)
p <- chromPlot(
data = condition2_data(),
chr = vals$chr_1,
feature = vals$feature_1,
log_scale = vals$log_scale_1
)
})
output$condition2_chromPlot <- renderPlot({
print(condition2_chromPlot())
})
#
# # agg_chromPlot
# output$agg_chromPlot <- renderPlot({
# req(vals$chr_2)
# agg_chromPlot(
# data1 = condition1_data(),
# data2 = condition2_data(),
# chr = vals$chr_2,
# feature = vals$feature_2,
# mean_se = input$mean_se
# )
# })
# condition1_ManhattanPlot
condition1_ManhattanPlot <- reactive({
req(vals$chr_3)
p <- ManhattanPlot(
data = condition1_data(),
chr = vals$chr_3,
feature = vals$feature_3,
log_scale = input$log_scale_3
)
})
output$condition1_ManhattanPlot <- renderPlot({
print(condition1_ManhattanPlot())
})
# condition2_ManhattanPlot
condition2_ManhattanPlot <- reactive({
req(vals$chr_3)
p <- ManhattanPlot(
data = condition2_data(),
chr = vals$chr_3,
feature = vals$feature_3,
log_scale = input$log_scale_3
)
})
output$condition2_ManhattanPlot <- renderPlot({
print(condition2_ManhattanPlot())
})
# ManhattanPlot_ratio
ManhattanPlot_ratio <- reactive({
req(vals$chr_3)
p <- ManhattanPlot(
data = condition1_data(),
data2 = condition2_data(),
chr = vals$chr_3,
feature = vals$feature_3,
log_scale = input$log_scale_3,
condition1_name = input$condition1_name,
condition2_name = input$condition2_name
)
})
output$ManhattanPlot_ratio <- renderPlot({
print(ManhattanPlot_ratio())
})
# 2D Plot
TwoDPlot_plot <- reactive({
req(vals$chr_4)
p <- TwoDPlot(
data1 = condition1_data(),
data2 = condition2_data(),
chr = vals$chr_4,
feature = vals$feature_4,
condition1_name = input$condition1_name,
condition2_name = input$condition2_name
)
})
output$TwoDPlot_plot <- renderPlot({
print(TwoDPlot_plot())
})
# Download Plots
output$download_condition1_chromPlot <- downloadHandler(
filename = function() {
paste(
vals$condition1_name,
'-',
vals$chr_1,
'-',
Sys.Date(),
'.pdf',
sep=''
)
},
content = function(file) {
pdf(
file,
bg = "white",
useDingbats = F,
width = vals$plot_width_1,
height = vals$plot_height_1
)
print(condition1_chromPlot())
dev.off()
},
contentType = 'image/pdf'
)
output$download_condition2_chromPlot <- downloadHandler(
filename = function() {
paste(
vals$condition2_name,
'-',
vals$chr_1,
'-',
Sys.Date(),
'.pdf',
sep=''
)
},
content = function(file) {
pdf(
file,
bg = "white",
useDingbats = F,
width = vals$plot_width_1,
height = vals$plot_height_1
)
print(condition2_chromPlot())
dev.off()
},
contentType = 'image/pdf'
)
output$download_condition1_ManhattanPlot <- downloadHandler(
filename = function() {
paste(
vals$condition1_name,
'-',
"Manhattan",
'-',
Sys.Date(),
'.pdf',
sep=''
)
},
content = function(file) {
pdf(
file,
bg = "white",
useDingbats = F,
width = vals$plot_width_3,
height = vals$plot_height_3
)
print(condition1_ManhattanPlot())
dev.off()
},
contentType = 'image/pdf'
)
output$download_condition2_ManhattanPlot <- downloadHandler(
filename = function() {
paste(
vals$condition2_name,
'-',
"Manhattan",
'-',
Sys.Date(),
'.pdf',
sep=''
)
},
content = function(file) {
pdf(
file,
bg = "white",
useDingbats = F,
width = vals$plot_width_3,
height = vals$plot_height_3
)
print(condition2_ManhattanPlot())
dev.off()
},
contentType = 'image/pdf'
)
output$download_ManhattanPlot_ratio <- downloadHandler(
filename = function() {
paste(
vals$condition1_name,
'-',
vals$condition2_name,
'-',
"Manhattan",
'-',
Sys.Date(),
'.pdf',
sep=''
)
},
content = function(file) {
pdf(
file,
bg = "white",
useDingbats = F,
width = vals$plot_width_3,
height = vals$plot_height_3
)
print(ManhattanPlot_ratio())
dev.off()
},
contentType = 'image/pdf'
)
output$download_TwoDPlot_plot <- downloadHandler(
filename = function() {
paste(
vals$condition1_name,
'-',
vals$condition2_name,
'-',
"2DPlot",
'-',
Sys.Date(),
'.pdf',
sep=''
)
},
content = function(file) {
pdf(
file,
bg = "white",
useDingbats = F,
width = vals$plot_width_4,
height = vals$plot_height_4
)
print(TwoDPlot_plot())
dev.off()
},
contentType = 'image/pdf'
)
output$render_download_condition1_chromPlot <- renderUI({
req(vals$chr_1)
downloadButton("download_condition1_chromPlot", "Download plot")
})
output$render_download_condition2_chromPlot <- renderUI({
req(vals$chr_1)
downloadButton("download_condition2_chromPlot", "Download plot")
})
output$render_download_condition1_ManhattanPlot <- renderUI({
req(vals$chr_3)
downloadButton("download_condition1_ManhattanPlot", "Download plot")
})
output$render_download_condition2_ManhattanPlot <- renderUI({
req(vals$chr_3)
downloadButton("download_condition2_ManhattanPlot", "Download plot")
})
output$render_download_ManhattanPlot_ratio <- renderUI({
req(vals$chr_3)
downloadButton("download_ManhattanPlot_ratio", "Download plot")
})
output$render_download_TwoDPlot_plot <- renderUI({
req(vals$chr_4)
downloadButton("download_TwoDPlot_plot", "Download plot")
})
}
# Run the application
shinyApp(ui = ui, server = server)
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