R/BSAvis_shiny.R
In EG-lisy/BSAvis: Bulk Segregant Analysis - Visualisation Package
Defines functions
BSAvis_shiny
Documented in
BSAvis_shiny
#Run BSAvis - interactive BSA visualisation tool
#' @title Run BSAvis
#' @description Run the interactive BSA visualisation tool.
#'
#' @param vcf.list object containing meta information and vcf data frame
#'
#' @importFrom dplyr %>%
#' @export BSAvis_shiny
#'
#' @examples
#' BSAvis_shiny(vcf.list=vcf_list)
BSAvis_shiny <- function(vcf.list){
#User Interface
ui <-
fluidPage(useShinyalert(),
# ==============================================================================
# HOME
# ==============================================================================
fluidRow(
id = "body",
column(width = 12, hr(),
h1("BSAvis", align="center"),
br(),
#HTML('<center><img src="www/BSAvis_logo.png" width="200"></center>'),
#shiny::img(src="www/BSAvis_small_logo.png"),
h5("Welcome to BSAvis, an interactive Bulk Segregant Analysis (BSA) tool.",
align ="center")
),
column(width = 12, hr())
),
# ==============================================================================
# FIRST METHOD
# SNP-index Method
# ==============================================================================
#Title
titlePanel(strong("BSAvis")),
tags$h5("SNP-index Method"),
br(),
sidebarLayout(
sidebarPanel(
#Select Chromosome
selectInput(
inputId = "chrMethod1",
label = "Chromosome Number:",
choices = (BSAvis::extract_chrIDs(vcf.list$meta))[!grepl("0$", BSAvis::extract_chrIDs(vcf.list$meta))] #remove chromosome ID if ends with 0 (chromosome 0)
),
hr(),
#Select pool names
selectInput(
inputId = "wtMethod1",
label = "Wild-type bulk:",
choices = unique((vcf.list$df)$Indiv),
selected = unique((vcf.list$df)$Indiv)[grep("*minus", unique((vcf.list$df)$Indiv))]
),
selectInput(
inputId = "mMethod1",
label = "Mutant bulk:",
choices = unique((vcf.list$df)$Indiv),
selected = unique((vcf.list$df)$Indiv)[grep("*plus", unique((vcf.list$df)$Indiv))]
),
hr(),
radioButtons(
inputId = "bulk",
label = "Bulk:",
choices = list("Both" = 0,
"Wild-type bulk" = 1,
"Mutant bulk" = 2),
selected = 0
),
radioButtons(
inputId = "variants_snpindex",
label = "Variants:",
choices = list("SNPs" = 1,
"SNPs+InDels" = 2),
selected = 1
),
hr(),
#Set Window Size
sliderInput(
inputId = "window",
label = "Window Size:",
min = 500000,
max = 3000000,
value = 1000000,
step = 500000
),
#Set Step Size
sliderInput(
inputId = "step",
label = "Step Size:",
min = 5000,
max = 10000,
value = 10000,
step = 1000
),
hr(),
#Filtering
#min SNP-index
numericInput(
inputId = "min_snpindex",
label = "Min SNP-index:",
min = 0,
max = 1,
step = 0.1,
value = 0.3
),
#max SNP-index
numericInput(
inputId = "max_snpindex",
label = "Max SNP-index:",
min = 0,
max = 1,
step = 0.1,
value = 0.9
),
#min DP
numericInput(
inputId = "min_DP1",
label = "Min DP:",
min = 0,
max = 80,
step = 1,
value = 50
),
#max DP
numericInput(
inputId = "max_DP1",
label = "Max DP:",
min = 0,
max = 500,
step = 1,
value = 200
),
#min GQ
numericInput(
inputId = "min_GQ",
label = "Min GQ:",
min = 0,
max = 100,
step = 1,
value = 99
)
),
#SNP-index - plot panels
mainPanel(tabsetPanel(type = "tabs",
tabPanel("SNP-index",
#loading spinner before generating the plot
withSpinner(plotOutput("snp_index",
dblclick = "plot1_dblclick", #add double-click event
brush = brushOpts( #enable brush
id = "plot1_brush",
resetOnNew = TRUE))),
#add save button
actionButton("save1", "Save Plot")),
tabPanel("delta(SNP-index)",
#loading spinner before generating the plot
withSpinner(plotOutput("delta_snp_index",
dblclick = "plot2_dblclick", #add double-click event
brush = brushOpts( #enable brush
id = "plot2_brush",
resetOnNew = TRUE))),
#add save button
actionButton("save2", "Save Plot"))
))
),
# ==============================================================================
# SECOND METHOD
# SNP-ratio Method
# ==============================================================================
titlePanel(strong("BSAvis")),
tags$h5("SNP-ratio Method"),
br(),
sidebarLayout(
sidebarPanel(
#Select Chromosome
selectInput(
inputId = "chrMethod2",
label = "Chromosome Number:",
choices = (BSAvis::extract_chrIDs(vcf.list$meta))[!grepl("0$", BSAvis::extract_chrIDs(vcf.list$meta))]
),
hr(),
#Select pool names
selectInput(
inputId = "wtMethod2",
label = "Wild-type bulk:",
choices = unique((vcf.list$df)$Indiv),
selected = unique((vcf.list$df)$Indiv)[grep("*minus", unique((vcf.list$df)$Indiv))]
),
selectInput(
inputId = "mMethod2",
label = "Mutant bulk:",
choices = unique((vcf.list$df)$Indiv),
selected = unique((vcf.list$df)$Indiv)[grep("*plus", unique((vcf.list$df)$Indiv))]
),
hr(),
radioButtons(
inputId = "variants_snpratio",
label = "Variants:",
choices = list("SNPs" = 1,
"SNPs+InDels" = 2),
selected = 1
),
hr(),
#Min SNP-ratio value to consider
numericInput(
inputId = "min_snpratio",
label = "Min SNP-ratio:",
min = 0,
step = 0.1,
value = 0.1
),
#min DP
numericInput(
inputId = "min_DP2",
label = "Min DP:",
min = 0,
max = 80,
step = 1,
value = 50
),
#max DP
numericInput(
inputId = "max_DP2",
label = "Max DP:",
min = 0,
max = 500,
step = 1,
value = 200
),
hr(),
#LOESS Smoothing - Degree
radioButtons(
inputId = "degree",
label = "Degree:",
choices = list("0" = 0,
"1" = 1,
"2" = 2),
selected = 2
),
#LOESS Smoothing - Span
numericInput(
inputId = "span",
label = "Span:",
min = 0,
value = 0.07,
step = 0.01
)
),
#SNP-ratio - plot panel
mainPanel(
tabsetPanel(
type = "tabs",
tabPanel("SNP-ratio",
#loading spinner before generating the plot
withSpinner(plotOutput("snp_ratio",
dblclick = "plot3_dblclick", #add double-click event
brush = brushOpts( #enable brush
id = "plot3_brush",
resetOnNew = TRUE))),
#add action button
actionButton("save3", "Save Plot"))
))
)
)
#Server
server <- function(input, output) {
#Create objects to store brush bounds for each of the plots
ranges1 <- reactiveValues(x = NULL, y = NULL)
ranges2 <- reactiveValues(x = NULL, y = NULL)
ranges3 <- reactiveValues(x = NULL, y = NULL)
# ==============================================================================
# FIRST METHOD
# SNP-index Method
# ==============================================================================
# -------------------------------- SNP-Index -----------------------------------
#Create reactive expression to plot SNP-index
SNPindexPlot <- reactive({
#Assign value to chosenVariants based on user input regarding the type of variants to show
chosenVariants <- ifelse(input$variants_snpindex == 1, "SNP", "all")
#Assign value to chosenBulk based on user input regarding which bulk's SNP-index plot to visualise
if (input$bulk==0) {
chosenBulk <- 0
}
else if (input$bulk==1) {
chosenBulk <- 1
}
else if (input$bulk==2) {
chosenBulk <- 2
}
#Call SNP-index plot function
BSAvis::shiny_SNPindex(vcf.list = vcf.list,
wtBulk = input$wtMethod1,
mBulk = input$mMethod1,
variants = chosenVariants,
min.SNPindex = input$min_snpindex,
max.SNPindex = input$max_snpindex,
min.DP = input$min_DP1,
max.DP = input$max_DP1,
min.GQ = input$min_GQ,
chrID = input$chrMethod1,
chr = input$chrMethod1,
windowSize = as.numeric(input$window),
windowStep = as.numeric(input$step),
bulk = chosenBulk,
ranges = ranges1)
})
#Add SNP-index plot to its corresponding place in the UI
output$snp_index <- renderPlot({
SNPindexPlot()
})
# -------------------------------- delta(SNP-Index) -----------------------------------
#Create reactive expression to plot delta(SNP-index)
deltaSNPindexPlot <- reactive({
chosenVariants <- ifelse(input$variants_snpindex == 1, "SNP", "all")
BSAvis::shiny_deltaSNPindex(vcf.list = vcf.list,
wtBulk = input$wtMethod1,
mBulk = input$mMethod1,
variants = chosenVariants,
min.SNPindex = input$min_snpindex,
max.SNPindex = input$max_snpindex,
min.DP = input$min_DP1,
max.DP = input$max_DP1,
min.GQ = input$min_GQ,
chrID = input$chrMethod1,
chr = input$chrMethod1,
windowSize = as.numeric(input$window),
windowStep = as.numeric(input$step),
ranges = ranges2)
})
#Add delta(SNP-index) plot to its corresponding place in the UI
output$delta_snp_index <- renderPlot({
deltaSNPindexPlot()
})
# ==============================================================================
# SECOND METHOD
# SNP-ratio PLOT
# ==============================================================================
#Create reactive expression to plot SNP-ratio
SNPratioPlot <- reactive({
chosenVariants <- ifelse(input$variants_snpratio == 1, "SNP", "all")
BSAvis::shiny_SNPratio(vcf.list = vcf.list,
wtBulk = input$wtMethod2,
mBulk = input$mMethod2,
variants = chosenVariants,
min.SNPratio = input$min_snpratio,
min.DP = input$min_DP2,
max.DP = input$max_DP2,
chrID = input$chrMethod2,
chr = input$chrMethod2,
degree = input$degree,
span = input$span,
ranges = ranges3)
})
#Add SNP-ratio plot to its corresponding place in the UI
output$snp_ratio <- renderPlot({
SNPratioPlot()
})
# ==============================================================================
#
# Save plots
# ==============================================================================
#Save SNP-index plot when the corresponding button is clicked.
#First, show pop-up window allowing the user to set saving parameters
observeEvent(input$save1, {
shinyalert(inputId="savingInfoAlert1", html = TRUE, text = tagList(
helpText(h6("Default values are being shown. Please, type to customise the parameters.")),
br(),
textInput("directory1", "Directory to save the plot", getwd()),
textInput("filename1", "File name (without file extesion)", paste0("plot_SNPindex_ch", input$chrMethod1)),
numericInput("dpi1", "DPI", 1200),
numericInput("width1", "Width (inches)", 7.5),
numericInput("height1", "Height (inches)", 5)
))
})
observeEvent(input$savingInfoAlert1, {
ggplot2::ggsave(filename=paste0(input$filename1, ".tiff"), path=input$directory1, plot=SNPindexPlot(), device = "tiff", dpi = input$dpi1, width = input$width1, height = input$height1)
})
#Save delta(SNP-index) plot when the corresponding button is clicked.
#First, show pop-up window allowing the user to set saving parameters
observeEvent(input$save2, {
shinyalert(inputId="savingInfoAlert2", html = TRUE, text = tagList(
helpText(h6("Default values are being shown. Please, type to customise the parameters.")),
br(),
textInput("directory2", "Directory to save the plot", getwd()),
textInput("filename2", "File name (without file extesion)", paste0("plot_deltaSNPindex_ch", input$chrMethod1)),
numericInput("dpi2", "DPI", 1200),
numericInput("width2", "Width (inches)", 7.5),
numericInput("height2", "Height (inches)", 5)
))
})
observeEvent(input$savingInfoAlert2, {
ggplot2::ggsave(filename=paste0(input$filename2, ".tiff"), path=input$directory2, plot=deltaSNPindexPlot(), device = "tiff", dpi = input$dpi2, width = input$width2, height = input$height2)
})
#Save SNP-ratio plot when the corresponding button is clicked.
#First, show pop-up window allowing the user to set saving parameters
observeEvent(input$save3, {
shinyalert(inputId="savingInfoAlert3", html = TRUE, text = tagList(
helpText(h6("Default values are being shown. Please, type to customise the parameters.")),
br(),
textInput("directory3", "Directory to save the plot", getwd()),
textInput("filename3", "File name (without file extesion)", paste0("plot_SNPratio_ch", input$chrMethod2)),
numericInput("dpi3", "DPI", 1200),
numericInput("width3", "Width (inches)", 7.5),
numericInput("height3", "Height (inches)", 5)
))
})
observeEvent(input$savingInfoAlert3, {
ggplot2::ggsave(filename=paste0(input$filename3, ".tiff"), path=input$directory3, plot=SNPratioPlot(), device = "tiff", dpi = input$dpi3, width = input$width3, height = input$height3)
})
# ==============================================================================
#
# Zoom functionality
# ==============================================================================
#For each of the plots, check if there is a brush when a double-click happens. If so, zoom to the brush bounds; if not, reset the zoom.
#Implement double-click to zoom in SNP-index plot
observeEvent(input$plot1_dblclick, {
brush <- input$plot1_brush
if (!is.null(brush)) {
ranges1$x <- c(brush$xmin, brush$xmax)
ranges1$y <- c(brush$ymin, brush$ymax)
} else {
ranges1$x <- NULL
ranges1$y <- NULL
}
})
#Implement double-click to zoom in delta(SNP-index) plot
observeEvent(input$plot2_dblclick, {
brush <- input$plot2_brush
if (!is.null(brush)) {
ranges2$x <- c(brush$xmin, brush$xmax)
ranges2$y <- c(brush$ymin, brush$ymax)
} else {
ranges2$x <- NULL
ranges2$y <- NULL
}
})
#Implement double-click to zoom in SNP-ratio plot
observeEvent(input$plot3_dblclick, {
brush <- input$plot3_brush
if (!is.null(brush)) {
ranges3$x <- c(brush$xmin, brush$xmax)
ranges3$y <- c(brush$ymin, brush$ymax)
} else {
ranges3$x <- NULL
ranges3$y <- NULL
}
})
}
shinyApp(ui, server)
}
EG-lisy/BSAvis documentation built on Dec. 17, 2021, 5:38 p.m.
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Defines functions BSAvis_shiny
Documented in BSAvis_shiny
#Run BSAvis - interactive BSA visualisation tool
#' @title Run BSAvis
#' @description Run the interactive BSA visualisation tool.
#'
#' @param vcf.list object containing meta information and vcf data frame
#'
#' @importFrom dplyr %>%
#' @export BSAvis_shiny
#'
#' @examples
#' BSAvis_shiny(vcf.list=vcf_list)
BSAvis_shiny <- function(vcf.list){
#User Interface
ui <-
fluidPage(useShinyalert(),
# ==============================================================================
# HOME
# ==============================================================================
fluidRow(
id = "body",
column(width = 12, hr(),
h1("BSAvis", align="center"),
br(),
#HTML('<center><img src="www/BSAvis_logo.png" width="200"></center>'),
#shiny::img(src="www/BSAvis_small_logo.png"),
h5("Welcome to BSAvis, an interactive Bulk Segregant Analysis (BSA) tool.",
align ="center")
),
column(width = 12, hr())
),
# ==============================================================================
# FIRST METHOD
# SNP-index Method
# ==============================================================================
#Title
titlePanel(strong("BSAvis")),
tags$h5("SNP-index Method"),
br(),
sidebarLayout(
sidebarPanel(
#Select Chromosome
selectInput(
inputId = "chrMethod1",
label = "Chromosome Number:",
choices = (BSAvis::extract_chrIDs(vcf.list$meta))[!grepl("0$", BSAvis::extract_chrIDs(vcf.list$meta))] #remove chromosome ID if ends with 0 (chromosome 0)
),
hr(),
#Select pool names
selectInput(
inputId = "wtMethod1",
label = "Wild-type bulk:",
choices = unique((vcf.list$df)$Indiv),
selected = unique((vcf.list$df)$Indiv)[grep("*minus", unique((vcf.list$df)$Indiv))]
),
selectInput(
inputId = "mMethod1",
label = "Mutant bulk:",
choices = unique((vcf.list$df)$Indiv),
selected = unique((vcf.list$df)$Indiv)[grep("*plus", unique((vcf.list$df)$Indiv))]
),
hr(),
radioButtons(
inputId = "bulk",
label = "Bulk:",
choices = list("Both" = 0,
"Wild-type bulk" = 1,
"Mutant bulk" = 2),
selected = 0
),
radioButtons(
inputId = "variants_snpindex",
label = "Variants:",
choices = list("SNPs" = 1,
"SNPs+InDels" = 2),
selected = 1
),
hr(),
#Set Window Size
sliderInput(
inputId = "window",
label = "Window Size:",
min = 500000,
max = 3000000,
value = 1000000,
step = 500000
),
#Set Step Size
sliderInput(
inputId = "step",
label = "Step Size:",
min = 5000,
max = 10000,
value = 10000,
step = 1000
),
hr(),
#Filtering
#min SNP-index
numericInput(
inputId = "min_snpindex",
label = "Min SNP-index:",
min = 0,
max = 1,
step = 0.1,
value = 0.3
),
#max SNP-index
numericInput(
inputId = "max_snpindex",
label = "Max SNP-index:",
min = 0,
max = 1,
step = 0.1,
value = 0.9
),
#min DP
numericInput(
inputId = "min_DP1",
label = "Min DP:",
min = 0,
max = 80,
step = 1,
value = 50
),
#max DP
numericInput(
inputId = "max_DP1",
label = "Max DP:",
min = 0,
max = 500,
step = 1,
value = 200
),
#min GQ
numericInput(
inputId = "min_GQ",
label = "Min GQ:",
min = 0,
max = 100,
step = 1,
value = 99
)
),
#SNP-index - plot panels
mainPanel(tabsetPanel(type = "tabs",
tabPanel("SNP-index",
#loading spinner before generating the plot
withSpinner(plotOutput("snp_index",
dblclick = "plot1_dblclick", #add double-click event
brush = brushOpts( #enable brush
id = "plot1_brush",
resetOnNew = TRUE))),
#add save button
actionButton("save1", "Save Plot")),
tabPanel("delta(SNP-index)",
#loading spinner before generating the plot
withSpinner(plotOutput("delta_snp_index",
dblclick = "plot2_dblclick", #add double-click event
brush = brushOpts( #enable brush
id = "plot2_brush",
resetOnNew = TRUE))),
#add save button
actionButton("save2", "Save Plot"))
))
),
# ==============================================================================
# SECOND METHOD
# SNP-ratio Method
# ==============================================================================
titlePanel(strong("BSAvis")),
tags$h5("SNP-ratio Method"),
br(),
sidebarLayout(
sidebarPanel(
#Select Chromosome
selectInput(
inputId = "chrMethod2",
label = "Chromosome Number:",
choices = (BSAvis::extract_chrIDs(vcf.list$meta))[!grepl("0$", BSAvis::extract_chrIDs(vcf.list$meta))]
),
hr(),
#Select pool names
selectInput(
inputId = "wtMethod2",
label = "Wild-type bulk:",
choices = unique((vcf.list$df)$Indiv),
selected = unique((vcf.list$df)$Indiv)[grep("*minus", unique((vcf.list$df)$Indiv))]
),
selectInput(
inputId = "mMethod2",
label = "Mutant bulk:",
choices = unique((vcf.list$df)$Indiv),
selected = unique((vcf.list$df)$Indiv)[grep("*plus", unique((vcf.list$df)$Indiv))]
),
hr(),
radioButtons(
inputId = "variants_snpratio",
label = "Variants:",
choices = list("SNPs" = 1,
"SNPs+InDels" = 2),
selected = 1
),
hr(),
#Min SNP-ratio value to consider
numericInput(
inputId = "min_snpratio",
label = "Min SNP-ratio:",
min = 0,
step = 0.1,
value = 0.1
),
#min DP
numericInput(
inputId = "min_DP2",
label = "Min DP:",
min = 0,
max = 80,
step = 1,
value = 50
),
#max DP
numericInput(
inputId = "max_DP2",
label = "Max DP:",
min = 0,
max = 500,
step = 1,
value = 200
),
hr(),
#LOESS Smoothing - Degree
radioButtons(
inputId = "degree",
label = "Degree:",
choices = list("0" = 0,
"1" = 1,
"2" = 2),
selected = 2
),
#LOESS Smoothing - Span
numericInput(
inputId = "span",
label = "Span:",
min = 0,
value = 0.07,
step = 0.01
)
),
#SNP-ratio - plot panel
mainPanel(
tabsetPanel(
type = "tabs",
tabPanel("SNP-ratio",
#loading spinner before generating the plot
withSpinner(plotOutput("snp_ratio",
dblclick = "plot3_dblclick", #add double-click event
brush = brushOpts( #enable brush
id = "plot3_brush",
resetOnNew = TRUE))),
#add action button
actionButton("save3", "Save Plot"))
))
)
)
#Server
server <- function(input, output) {
#Create objects to store brush bounds for each of the plots
ranges1 <- reactiveValues(x = NULL, y = NULL)
ranges2 <- reactiveValues(x = NULL, y = NULL)
ranges3 <- reactiveValues(x = NULL, y = NULL)
# ==============================================================================
# FIRST METHOD
# SNP-index Method
# ==============================================================================
# -------------------------------- SNP-Index -----------------------------------
#Create reactive expression to plot SNP-index
SNPindexPlot <- reactive({
#Assign value to chosenVariants based on user input regarding the type of variants to show
chosenVariants <- ifelse(input$variants_snpindex == 1, "SNP", "all")
#Assign value to chosenBulk based on user input regarding which bulk's SNP-index plot to visualise
if (input$bulk==0) {
chosenBulk <- 0
}
else if (input$bulk==1) {
chosenBulk <- 1
}
else if (input$bulk==2) {
chosenBulk <- 2
}
#Call SNP-index plot function
BSAvis::shiny_SNPindex(vcf.list = vcf.list,
wtBulk = input$wtMethod1,
mBulk = input$mMethod1,
variants = chosenVariants,
min.SNPindex = input$min_snpindex,
max.SNPindex = input$max_snpindex,
min.DP = input$min_DP1,
max.DP = input$max_DP1,
min.GQ = input$min_GQ,
chrID = input$chrMethod1,
chr = input$chrMethod1,
windowSize = as.numeric(input$window),
windowStep = as.numeric(input$step),
bulk = chosenBulk,
ranges = ranges1)
})
#Add SNP-index plot to its corresponding place in the UI
output$snp_index <- renderPlot({
SNPindexPlot()
})
# -------------------------------- delta(SNP-Index) -----------------------------------
#Create reactive expression to plot delta(SNP-index)
deltaSNPindexPlot <- reactive({
chosenVariants <- ifelse(input$variants_snpindex == 1, "SNP", "all")
BSAvis::shiny_deltaSNPindex(vcf.list = vcf.list,
wtBulk = input$wtMethod1,
mBulk = input$mMethod1,
variants = chosenVariants,
min.SNPindex = input$min_snpindex,
max.SNPindex = input$max_snpindex,
min.DP = input$min_DP1,
max.DP = input$max_DP1,
min.GQ = input$min_GQ,
chrID = input$chrMethod1,
chr = input$chrMethod1,
windowSize = as.numeric(input$window),
windowStep = as.numeric(input$step),
ranges = ranges2)
})
#Add delta(SNP-index) plot to its corresponding place in the UI
output$delta_snp_index <- renderPlot({
deltaSNPindexPlot()
})
# ==============================================================================
# SECOND METHOD
# SNP-ratio PLOT
# ==============================================================================
#Create reactive expression to plot SNP-ratio
SNPratioPlot <- reactive({
chosenVariants <- ifelse(input$variants_snpratio == 1, "SNP", "all")
BSAvis::shiny_SNPratio(vcf.list = vcf.list,
wtBulk = input$wtMethod2,
mBulk = input$mMethod2,
variants = chosenVariants,
min.SNPratio = input$min_snpratio,
min.DP = input$min_DP2,
max.DP = input$max_DP2,
chrID = input$chrMethod2,
chr = input$chrMethod2,
degree = input$degree,
span = input$span,
ranges = ranges3)
})
#Add SNP-ratio plot to its corresponding place in the UI
output$snp_ratio <- renderPlot({
SNPratioPlot()
})
# ==============================================================================
#
# Save plots
# ==============================================================================
#Save SNP-index plot when the corresponding button is clicked.
#First, show pop-up window allowing the user to set saving parameters
observeEvent(input$save1, {
shinyalert(inputId="savingInfoAlert1", html = TRUE, text = tagList(
helpText(h6("Default values are being shown. Please, type to customise the parameters.")),
br(),
textInput("directory1", "Directory to save the plot", getwd()),
textInput("filename1", "File name (without file extesion)", paste0("plot_SNPindex_ch", input$chrMethod1)),
numericInput("dpi1", "DPI", 1200),
numericInput("width1", "Width (inches)", 7.5),
numericInput("height1", "Height (inches)", 5)
))
})
observeEvent(input$savingInfoAlert1, {
ggplot2::ggsave(filename=paste0(input$filename1, ".tiff"), path=input$directory1, plot=SNPindexPlot(), device = "tiff", dpi = input$dpi1, width = input$width1, height = input$height1)
})
#Save delta(SNP-index) plot when the corresponding button is clicked.
#First, show pop-up window allowing the user to set saving parameters
observeEvent(input$save2, {
shinyalert(inputId="savingInfoAlert2", html = TRUE, text = tagList(
helpText(h6("Default values are being shown. Please, type to customise the parameters.")),
br(),
textInput("directory2", "Directory to save the plot", getwd()),
textInput("filename2", "File name (without file extesion)", paste0("plot_deltaSNPindex_ch", input$chrMethod1)),
numericInput("dpi2", "DPI", 1200),
numericInput("width2", "Width (inches)", 7.5),
numericInput("height2", "Height (inches)", 5)
))
})
observeEvent(input$savingInfoAlert2, {
ggplot2::ggsave(filename=paste0(input$filename2, ".tiff"), path=input$directory2, plot=deltaSNPindexPlot(), device = "tiff", dpi = input$dpi2, width = input$width2, height = input$height2)
})
#Save SNP-ratio plot when the corresponding button is clicked.
#First, show pop-up window allowing the user to set saving parameters
observeEvent(input$save3, {
shinyalert(inputId="savingInfoAlert3", html = TRUE, text = tagList(
helpText(h6("Default values are being shown. Please, type to customise the parameters.")),
br(),
textInput("directory3", "Directory to save the plot", getwd()),
textInput("filename3", "File name (without file extesion)", paste0("plot_SNPratio_ch", input$chrMethod2)),
numericInput("dpi3", "DPI", 1200),
numericInput("width3", "Width (inches)", 7.5),
numericInput("height3", "Height (inches)", 5)
))
})
observeEvent(input$savingInfoAlert3, {
ggplot2::ggsave(filename=paste0(input$filename3, ".tiff"), path=input$directory3, plot=SNPratioPlot(), device = "tiff", dpi = input$dpi3, width = input$width3, height = input$height3)
})
# ==============================================================================
#
# Zoom functionality
# ==============================================================================
#For each of the plots, check if there is a brush when a double-click happens. If so, zoom to the brush bounds; if not, reset the zoom.
#Implement double-click to zoom in SNP-index plot
observeEvent(input$plot1_dblclick, {
brush <- input$plot1_brush
if (!is.null(brush)) {
ranges1$x <- c(brush$xmin, brush$xmax)
ranges1$y <- c(brush$ymin, brush$ymax)
} else {
ranges1$x <- NULL
ranges1$y <- NULL
}
})
#Implement double-click to zoom in delta(SNP-index) plot
observeEvent(input$plot2_dblclick, {
brush <- input$plot2_brush
if (!is.null(brush)) {
ranges2$x <- c(brush$xmin, brush$xmax)
ranges2$y <- c(brush$ymin, brush$ymax)
} else {
ranges2$x <- NULL
ranges2$y <- NULL
}
})
#Implement double-click to zoom in SNP-ratio plot
observeEvent(input$plot3_dblclick, {
brush <- input$plot3_brush
if (!is.null(brush)) {
ranges3$x <- c(brush$xmin, brush$xmax)
ranges3$y <- c(brush$ymin, brush$ymax)
} else {
ranges3$x <- NULL
ranges3$y <- NULL
}
})
}
shinyApp(ui, server)
}
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