inst/application/app.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 application that visualizes REVA output. For now, you can run the application by clicking
# the 'Run App' button above in Rstudio or by running 'Rscript app.R' in the terminal.
# Load libraries
library(shiny)
library(waiter)
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")
# Set default browser
options(browser="/usr/bin/firefox")
# 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,
use_waiter(),
plotOutput("condition1_chromPlot"),
uiOutput("render_download_condition1_chromPlot")
)
),
fluidRow(
column(2),
column(10,
use_waiter(),
plotOutput("condition2_chromPlot"),
uiOutput("render_download_condition2_chromPlot")
)
)
),
tabPanel("Aggregate Plots",
fluidRow(
column(2,
uiOutput("render_ui_2"),
submitButton("Submit")
),
column(10,
use_waiter(),
plotOutput("agg_chromPlot_plot"),
uiOutput("render_download_agg_chromPlot_plot")
)
)
),
tabPanel("Manhattan Plots",
fluidRow(
column(2,
uiOutput("render_ui_3"),
submitButton("Submit")
),
column(10,
use_waiter(),
plotOutput("condition1_ManhattanPlot"),
uiOutput("render_download_condition1_ManhattanPlot")
)
),
fluidRow(
column(2),
column(10,
use_waiter(),
plotOutput("condition2_ManhattanPlot"),
uiOutput("render_download_condition2_ManhattanPlot")
)
),
fluidRow(
column(2),
column(10,
use_waiter(),
plotOutput("ManhattanPlot_ratio"),
uiOutput("render_download_ManhattanPlot_ratio")
)
)
),
tabPanel("2D Plots",
fluidRow(
column(2,
uiOutput("render_ui_4"),
submitButton("Submit")
),
column(5,
use_waiter(),
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
waiter <- Waiter$new(
id = c(
"condition1_chromPlot",
"condition2_chromPlot",
"agg_chromPlot_plot",
"condition1_ManhattanPlot",
"condition2_ManhattanPlot",
"ManhattanPlot_ratio",
"TwoDPlot_plot"
),
html = spin_throbber(),
color = "white"
)
###############################
## Define reactive variables ##
###############################
# condition files
condition1_data <- reactive({
req(input$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$feature_4
vals$norm_feature_1 <- input$norm_feature_1
vals$norm_feature_2 <- input$norm_feature_2
vals$norm_feature_3 <- input$norm_feature_3
vals$norm_feature_4 <- input$norm_feature_4
vals$log_scale_1 <- input$log_scale_1
vals$log_scale_2 <- input$log_scale_2
vals$log_scale_3 <- input$log_scale_3
vals$mean_se <- input$mean_se
vals$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()$Chr))
),
selectInput(
inputId = 'feature_1',
label = 'Feature',
choices = names(condition1_data())[5:(length(names(condition1_data())) - 1)]
),
selectInput(
inputId = 'norm_feature_1',
label = 'Normalization feature',
choices = c("", names(condition1_data())[5:(length(names(condition1_data())) - 1)])
),
checkboxInput(
inputId = "log_scale_1",
label = "log2(x)",
value = TRUE),
numericInput(
inputId = 'plot_height_1',
label = 'Download plot height (in)',
value = 3,
min = 1,
max = 48
),
numericInput(
inputId = 'plot_width_1',
label = 'Download plot width (in)',
value = 8,
min = 1,
max = 48
)
)
})
output$render_ui_2 <- renderUI({
list(
selectInput(
inputId = "chr_2",
label = "Chromosome name:",
choices = unique(as.character(condition1_data()$Chr))),
selectInput(
inputId = 'feature_2',
label = 'Feature',
choices = names(condition1_data())[5:(length(names(condition1_data())) - 1)]
),
selectInput(
inputId = 'norm_feature_2',
label = 'Normalization feature',
choices = c("", names(condition1_data())[5:(length(names(condition1_data())) - 1)])
),
checkboxInput(
inputId = "mean_se",
label = "Mean + SE",
value = TRUE
),
checkboxInput(
inputId = "log_scale_2",
label = "log2(x)",
value = TRUE
),
numericInput(
inputId = 'plot_height_2',
label = 'Download plot height (in)',
value = 3,
min = 1,
max = 48
),
numericInput(
inputId = 'plot_width_2',
label = 'Download plot width (in)',
value = 8,
min = 1,
max = 48
)
)
})
output$render_ui_3 <- renderUI({
list(
selectInput(
inputId = "chr_3",
label = "Chromosome name:",
choices = unique(as.character(condition1_data()$Chr)),
multiple = T
),
selectInput(
inputId = 'feature_3',
label = 'Feature',
choices = names(condition1_data())[5:(length(names(condition1_data())) - 1)]
),
selectInput(
inputId = 'norm_feature_3',
label = 'Normalization feature',
choices = c("", names(condition1_data())[5:(length(names(condition1_data())) - 1)])
),
checkboxInput(
inputId = "log_scale_3",
label = "log2(x)",
value = TRUE
),
numericInput(
inputId = 'plot_height_3',
label = 'Download plot height (in)',
value = 3,
min = 1,
max = 48
),
numericInput(
inputId = 'plot_width_3',
label = 'Download plot width (in)',
value = 8,
min = 1,
max = 48
)
)
})
output$render_ui_4 <- renderUI({
list(
selectInput(
inputId = "chr_4",
label = "Chromosome name:",
choices = unique(as.character(condition1_data()$Chr)),
multiple = T),
selectInput(
inputId = 'feature_4',
label = 'Feature',
choices = names(condition1_data())[5:(length(names(condition1_data())) - 1)]),
selectInput(
inputId = 'norm_feature_4',
label = 'Normalization feature',
choices = c("", names(condition1_data())[5:(length(names(condition1_data())) - 1)])
),
numericInput(
inputId = 'plot_height_4',
label = 'Download plot height (in)',
value = 3,
min = 1,
max = 48
),
numericInput(
inputId = 'plot_width_4',
label = 'Download plot width (in)',
value = 8,
min = 1,
max = 48
)
)
})
###########
## Plots ##
###########
# condition1_chromPlot
condition1_chromPlot <- reactive({
req(vals$chr_1)
p <- chromPlot(
data = condition1_data(),
chr = vals$chr_1,
feature = vals$feature_1,
norm_feature = vals$norm_feature_1,
log_scale = vals$log_scale_1
)
})
output$condition1_chromPlot <- renderPlot({
waiter$show()
Sys.sleep(1)
print(condition1_chromPlot())
})
# condition2_chromPlot
condition2_chromPlot <- reactive({
req(vals$chr_1)
p <- chromPlot(
data = condition2_data(),
chr = vals$chr_1,
feature = vals$feature_1,
norm_feature = vals$norm_feature_1,
log_scale = vals$log_scale_1
)
})
output$condition2_chromPlot <- renderPlot({
waiter$show()
Sys.sleep(1)
print(condition2_chromPlot())
})
# agg_chromPlot
agg_chromPlot_plot <- reactive({
req(vals$chr_2)
p <- agg_chromPlot(
data1 = condition1_data(),
data2 = condition2_data(),
chr = vals$chr_2,
feature = vals$feature_2,
norm_feature = vals$norm_feature_2,
mean_se = vals$mean_se,
log_scale = vals$log_scale_2
)
})
output$agg_chromPlot_plot <- renderPlot({
waiter$show()
Sys.sleep(1)
print(agg_chromPlot_plot())
})
# condition1_ManhattanPlot
condition1_ManhattanPlot <- reactive({
req(vals$chr_3)
p <- ManhattanPlot(
data = condition1_data(),
chr = vals$chr_3,
feature = vals$feature_3,
norm_feature = vals$norm_feature_3,
log_scale = input$log_scale_3
)
})
output$condition1_ManhattanPlot <- renderPlot({
waiter$show()
Sys.sleep(1)
print(condition1_ManhattanPlot())
})
# condition2_ManhattanPlot
condition2_ManhattanPlot <- reactive({
req(vals$chr_3)
p <- ManhattanPlot(
data = condition2_data(),
chr = vals$chr_3,
feature = vals$feature_3,
norm_feature = vals$norm_feature_3,
log_scale = input$log_scale_3
)
})
output$condition2_ManhattanPlot <- renderPlot({
waiter$show()
Sys.sleep(1)
print(condition2_ManhattanPlot())
})
# ManhattanPlot_ratio
ManhattanPlot_ratio <- reactive({
req(vals$chr_3)
p <- ManhattanPlot(
data = condition1_data(),
data2 = condition2_data(),
chr = vals$chr_3,
feature = vals$feature_3,
norm_feature = vals$norm_feature_3,
log_scale = input$log_scale_3,
condition1_name = input$condition1_name,
condition2_name = input$condition2_name
)
})
output$ManhattanPlot_ratio <- renderPlot({
waiter$show()
Sys.sleep(1)
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$feature_4,
norm_feature = vals$norm_feature_4,
condition1_name = input$condition1_name,
condition2_name = input$condition2_name
)
})
output$TwoDPlot_plot <- renderPlot({
waiter$show()
Sys.sleep(1)
print(TwoDPlot_plot())
})
# Download Plots
output$download_condition1_chromPlot <- downloadHandler(
filename = function() {
paste(
vals$condition1_name,
'-',
vals$feature_1,
'-',
ifelse(
vals$norm_feature_1 == "",
'',
paste(
'normalized-to-',
vals$norm_feature_1,
'-',
sep = ''
)
),
vals$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$feature_1,
'-',
ifelse(
vals$norm_feature_1 == "",
'',
paste(
'normalized-to-',
vals$norm_feature_1,
'-',
sep = ''
)
),
vals$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$download_agg_chromPlot_plot <- downloadHandler(
filename = function() {
paste(
vals$condition1_name,
'-',
vals$condition2_name,
'-',
vals$feature_2,
'-',
ifelse(
vals$norm_feature_2 == "",
'',
paste(
'normalized-to-',
vals$norm_feature_2,
'-',
sep = ''
)
),
vals$chr_2,
'-',
'agg-',
Sys.Date(),
'.pdf',
sep=''
)
},
content = function(file) {
pdf(
file,
bg = "white",
useDingbats = F,
width = vals$plot_width_2,
height = vals$plot_height_2
)
print(agg_chromPlot())
dev.off()
},
contentType = 'image/pdf'
)
output$download_condition1_ManhattanPlot <- downloadHandler(
filename = function() {
paste(
vals$condition1_name,
'-',
vals$feature_3,
'-',
ifelse(
vals$norm_feature_3 == "",
'',
paste(
'normalized-to-',
vals$norm_feature_3,
'-',
sep = ''
)
),
"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,
'-',
vals$feature_3,
'-',
ifelse(
vals$norm_feature_3 == "",
'',
paste(
'normalized-to-',
vals$norm_feature_3,
'-',
sep = ''
)
),
"Manhattan",
'-',
Sys.Date(),
'.pdf',
sep=''
)
},
content = function(file) {
pdf(
file,
bg = "white",
useDingbats = F,
width = vals$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,
'-',
vals$feature_3,
'-',
ifelse(
vals$norm_feature_3 == "",
'',
paste(
'normalized-to-',
vals$norm_feature_3,
'-',
sep = ''
)
),
"Manhattan",
'-',
Sys.Date(),
'.pdf',
sep=''
)
},
content = function(file) {
pdf(
file,
bg = "white",
useDingbats = F,
width = vals$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,
'-',
vals$feature_4,
'-',
ifelse(
vals$norm_feature_4 == "",
'',
paste(
'normalized-to-',
vals$norm_feature_4,
'-',
sep = ''
)
),
"2DPlot",
'-',
Sys.Date(),
'.pdf',
sep=''
)
},
content = function(file) {
pdf(
file,
bg = "white",
useDingbats = F,
width = vals$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_agg_chromPlot_plot <- renderUI({
req(vals$chr_2)
downloadButton("download_agg_chromPlot_plot", "Download plot")
})
output$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 application that visualizes REVA output. For now, you can run the application by clicking
# the 'Run App' button above in Rstudio or by running 'Rscript app.R' in the terminal.
# Load libraries
library(shiny)
library(waiter)
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")
# Set default browser
options(browser="/usr/bin/firefox")
# 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,
use_waiter(),
plotOutput("condition1_chromPlot"),
uiOutput("render_download_condition1_chromPlot")
)
),
fluidRow(
column(2),
column(10,
use_waiter(),
plotOutput("condition2_chromPlot"),
uiOutput("render_download_condition2_chromPlot")
)
)
),
tabPanel("Aggregate Plots",
fluidRow(
column(2,
uiOutput("render_ui_2"),
submitButton("Submit")
),
column(10,
use_waiter(),
plotOutput("agg_chromPlot_plot"),
uiOutput("render_download_agg_chromPlot_plot")
)
)
),
tabPanel("Manhattan Plots",
fluidRow(
column(2,
uiOutput("render_ui_3"),
submitButton("Submit")
),
column(10,
use_waiter(),
plotOutput("condition1_ManhattanPlot"),
uiOutput("render_download_condition1_ManhattanPlot")
)
),
fluidRow(
column(2),
column(10,
use_waiter(),
plotOutput("condition2_ManhattanPlot"),
uiOutput("render_download_condition2_ManhattanPlot")
)
),
fluidRow(
column(2),
column(10,
use_waiter(),
plotOutput("ManhattanPlot_ratio"),
uiOutput("render_download_ManhattanPlot_ratio")
)
)
),
tabPanel("2D Plots",
fluidRow(
column(2,
uiOutput("render_ui_4"),
submitButton("Submit")
),
column(5,
use_waiter(),
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
waiter <- Waiter$new(
id = c(
"condition1_chromPlot",
"condition2_chromPlot",
"agg_chromPlot_plot",
"condition1_ManhattanPlot",
"condition2_ManhattanPlot",
"ManhattanPlot_ratio",
"TwoDPlot_plot"
),
html = spin_throbber(),
color = "white"
)
###############################
## 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$norm_feature_1 <- input$norm_feature_1
vals$norm_feature_2 <- input$norm_feature_2
vals$norm_feature_3 <- input$norm_feature_3
vals$norm_feature_4 <- input$norm_feature_4
vals$log_scale_1 <- input$log_scale_1
vals$log_scale_2 <- input$log_scale_2
vals$log_scale_3 <- input$log_scale_3
vals$mean_se <- input$mean_se
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)]
),
selectInput(
inputId = 'norm_feature_1',
label = 'Normalization feature',
choices = c("", names(condition1_data())[5:(length(names(condition1_data())) - 1)])
),
checkboxInput(
inputId = "log_scale_1",
label = "log2(x)",
value = TRUE),
numericInput(
inputId = 'plot_height_1',
label = 'Download plot height (in)',
value = 3,
min = 1,
max = 48
),
numericInput(
inputId = 'plot_width_1',
label = 'Download plot width (in)',
value = 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)]
),
selectInput(
inputId = 'norm_feature_2',
label = 'Normalization feature',
choices = c("", names(condition1_data())[5:(length(names(condition1_data())) - 1)])
),
checkboxInput(
inputId = "mean_se",
label = "Mean + SE",
value = TRUE
),
checkboxInput(
inputId = "log_scale_2",
label = "log2(x)",
value = TRUE
),
numericInput(
inputId = 'plot_height_2',
label = 'Download plot height (in)',
value = 3,
min = 1,
max = 48
),
numericInput(
inputId = 'plot_width_2',
label = 'Download plot width (in)',
value = 8,
min = 1,
max = 48
)
)
})
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)]
),
selectInput(
inputId = 'norm_feature_3',
label = 'Normalization feature',
choices = c("", names(condition1_data())[5:(length(names(condition1_data())) - 1)])
),
checkboxInput(
inputId = "log_scale_3",
label = "log2(x)",
value = TRUE
),
numericInput(
inputId = 'plot_height_3',
label = 'Download plot height (in)',
value = 3,
min = 1,
max = 48
),
numericInput(
inputId = 'plot_width_3',
label = 'Download plot width (in)',
value = 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)]),
selectInput(
inputId = 'norm_feature_4',
label = 'Normalization feature',
choices = c("", names(condition1_data())[5:(length(names(condition1_data())) - 1)])
),
numericInput(
inputId = 'plot_height_4',
label = 'Download plot height (in)',
value = 3,
min = 1,
max = 48
),
numericInput(
inputId = 'plot_width_4',
label = 'Download plot width (in)',
value = 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$feature_1,
norm_feature = vals$norm_feature_1,
log_scale = vals$log_scale_1
)
})
output$condition1_chromPlot <- renderPlot({
waiter$show()
Sys.sleep(1)
print(condition1_chromPlot())
})
# condition2_chromPlot
condition2_chromPlot <- reactive({
req(vals$chr_1)
p <- chromPlot(
data = condition2_data(),
chr = vals$chr_1,
feature = vals$feature_1,
norm_feature = vals$norm_feature_1,
log_scale = vals$log_scale_1
)
})
output$condition2_chromPlot <- renderPlot({
waiter$show()
Sys.sleep(1)
print(condition2_chromPlot())
})
# agg_chromPlot
agg_chromPlot_plot <- reactive({
req(vals$chr_2)
p <- agg_chromPlot(
data1 = condition1_data(),
data2 = condition2_data(),
chr = vals$chr_2,
feature = vals$feature_2,
norm_feature = vals$norm_feature_2,
mean_se = vals$mean_se,
log_scale = vals$log_scale_2
)
})
output$agg_chromPlot_plot <- renderPlot({
waiter$show()
Sys.sleep(1)
print(agg_chromPlot_plot())
})
# condition1_ManhattanPlot
condition1_ManhattanPlot <- reactive({
req(vals$chr_3)
p <- ManhattanPlot(
data = condition1_data(),
chr = vals$chr_3,
feature = vals$feature_3,
norm_feature = vals$norm_feature_3,
log_scale = input$log_scale_3
)
})
output$condition1_ManhattanPlot <- renderPlot({
waiter$show()
Sys.sleep(1)
print(condition1_ManhattanPlot())
})
# condition2_ManhattanPlot
condition2_ManhattanPlot <- reactive({
req(vals$chr_3)
p <- ManhattanPlot(
data = condition2_data(),
chr = vals$chr_3,
feature = vals$feature_3,
norm_feature = vals$norm_feature_3,
log_scale = input$log_scale_3
)
})
output$condition2_ManhattanPlot <- renderPlot({
waiter$show()
Sys.sleep(1)
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$feature_3,
norm_feature = vals$norm_feature_3,
log_scale = input$log_scale_3,
condition1_name = input$condition1_name,
condition2_name = input$condition2_name
)
})
output$ManhattanPlot_ratio <- renderPlot({
waiter$show()
Sys.sleep(1)
print(ManhattanPlot_ratio())
})
# 2D Plot
TwoDPlot_plot <- reactive({
req(vals$chr_4)
p <- TwoDPlot(
data1 = condition1_data(),
data2 = condition2_data(),
chr = vals$chr_4,
feature = vals$feature_4,
norm_feature = vals$norm_feature_4,
condition1_name = input$condition1_name,
condition2_name = input$condition2_name
)
})
output$TwoDPlot_plot <- renderPlot({
waiter$show()
Sys.sleep(1)
print(TwoDPlot_plot())
})
# Download Plots
output$download_condition1_chromPlot <- downloadHandler(
filename = function() {
paste(
vals$condition1_name,
'-',
vals$feature_1,
'-',
ifelse(
vals$norm_feature_1 == "",
'',
paste(
'normalized-to-',
vals$norm_feature_1,
'-',
sep = ''
)
),
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$condition2_name,
'-',
vals$feature_1,
'-',
ifelse(
vals$norm_feature_1 == "",
'',
paste(
'normalized-to-',
vals$norm_feature_1,
'-',
sep = ''
)
),
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_agg_chromPlot_plot <- downloadHandler(
filename = function() {
paste(
vals$condition1_name,
'-',
vals$condition2_name,
'-',
vals$feature_2,
'-',
ifelse(
vals$norm_feature_2 == "",
'',
paste(
'normalized-to-',
vals$norm_feature_2,
'-',
sep = ''
)
),
vals$chr_2,
'-',
'agg-',
Sys.Date(),
'.pdf',
sep=''
)
},
content = function(file) {
pdf(
file,
bg = "white",
useDingbats = F,
width = vals$plot_width_2,
height = vals$plot_height_2
)
print(agg_chromPlot())
dev.off()
},
contentType = 'image/pdf'
)
output$download_condition1_ManhattanPlot <- downloadHandler(
filename = function() {
paste(
vals$condition1_name,
'-',
vals$feature_3,
'-',
ifelse(
vals$norm_feature_3 == "",
'',
paste(
'normalized-to-',
vals$norm_feature_3,
'-',
sep = ''
)
),
"Manhattan",
'-',
Sys.Date(),
'.pdf',
sep=''
)
},
content = function(file) {
pdf(
file,
bg = "white",
useDingbats = F,
width = vals$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$condition2_name,
'-',
vals$feature_3,
'-',
ifelse(
vals$norm_feature_3 == "",
'',
paste(
'normalized-to-',
vals$norm_feature_3,
'-',
sep = ''
)
),
"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$condition2_name,
'-',
vals$feature_3,
'-',
ifelse(
vals$norm_feature_3 == "",
'',
paste(
'normalized-to-',
vals$norm_feature_3,
'-',
sep = ''
)
),
"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$condition2_name,
'-',
vals$feature_4,
'-',
ifelse(
vals$norm_feature_4 == "",
'',
paste(
'normalized-to-',
vals$norm_feature_4,
'-',
sep = ''
)
),
"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$render_download_agg_chromPlot_plot <- renderUI({
req(vals$chr_2)
downloadButton("download_agg_chromPlot_plot", "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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