R/app2.R
In stamara6/LeanTopDown: Post Processing of Top-Down Data
#
# This is a Shiny web application. You can run the application by clicking
# the 'Run App' button above.
#
# Find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com/
#
# source("C:\\Users\\stama\\OneDrive\\Documents\\R\\Projects\\LeanTopDown\\R/helpers.R", local = TRUE)
# source("C:\\Users\\stama\\OneDrive\\Documents\\R\\Projects\\LeanTopDown\\R/spectrum annotator.R", local = TRUE)
# source("C:\\Users\\stama\\OneDrive\\Documents\\R\\Projects\\LeanTopDown\\R/freqflyers.R", local = TRUE)
# source("C:\\Users\\stama\\OneDrive\\Documents\\R\\Projects\\LeanTopDown\\R/frgmntstats.R", local = TRUE)
library(stringr)
library(shiny)
library(ggplot2)
library(reshape2)
library(ggcorrplot)
library(shinyjs)
library(logging)
library(shinycssloaders)
library(shinydashboard)
#library(LeanTopDown)
library(gridExtra)
ui <- dashboardPage(
dashboardHeader(title = "LeanTopDown"),
dashboardSidebar(
sidebarMenu(
conditionalPanel(condition = "input.conditionedPanels == 'mir'"
#checkboxInput("masslists", "Process Masslists", FALSE),
),
conditionalPanel(condition = "input.conditionedPanels == 'cor'"
#checkboxInput("masslists2", "Process Masslists", FALSE),
),
conditionalPanel(condition = "input.conditionedPanels == 'spa'"
),
conditionalPanel(condition = "input.conditionedPanels == 'frm'"
),
conditionalPanel(condition = "input.conditionedPanels == 'frf'",
fileInput("freqfile", "Frequent Flyers File", FALSE)),
conditionalPanel(condition = "input.conditionedPanels == 'frs'"
),
conditionalPanel(condition = "input.conditionedPanels == 'erp'"
),
actionButton("plot", "Plot"),
downloadButton("saveplot", "Save Plot"),
numericInput("width", "Plot Width", 480, 320, 5120, 160),
numericInput("height", "Plot Height", 400, 320, 5120, 160),
radioButtons("filetype", "Save as:",
choices = c("pdf", "png")),
textInput("filename", "File name:", ""),
uiOutput("mzRange"),
numericInput("ppm", "Accuracy", 3.5, 0.5, 20, 0.5),
checkboxInput("masslists", "Combine Masslists", FALSE),
fileInput("fileIn", "Upload Masslists", TRUE),
actionLink("selectall","Select All"),
checkboxGroupInput("selectFiles", "Select Spectra", c("1" = "1"))
)),
dashboardBody(
tabsetPanel(
tabPanel("mirRaw Plot", withSpinner(plotOutput("mirPlot", hover = "plotHover",
brush = brushOpts("plotBrush", resetOnNew = TRUE),
dblclick = "plotDC")),
value = "mir"),
tabPanel("Correlation Plot", withSpinner(plotOutput("corPlot")), value = "cor"),
tabPanel("Spectrum Annotation", withSpinner(plotOutput("spectrum", hover = "spechover",
brush = brushOpts("specBrush", resetOnNew = TRUE),
dblclick = "specDC")),
box(checkboxInput("facet", "Facetting", FALSE)),
value = "spa"),
tabPanel("Fragment Maps", withSpinner(plotOutput("fragmap", hover = "fmhover",
brush = brushOpts("fmBrush", resetOnNew = TRUE),
dblclick = "fmDC")),
box(checkboxInput("facet2", "Facetting", FALSE),
textInput("seq", "Sequence", "MKSVITTVVSAADAAGRFPSNSDLESIQGNIQRSAARLEAAEKLAGNHEAVVKEAGDACFAKYAYLKNPGEAGENQEKINKCYRDVDHYMRLVNYCLVVGGTGPLDEWGIAGAREVYRTLNLPTSAYVASIAYTRDRLCVPRDMSAQAGVEFSAYLDYLINALS"),
#checkboxInput("septerm", "Separate Termini Processing", TRUE),
numericInput("modnum", "Number of Modifications", 0, 0, 5, 1)
#checkboxInput("bound", "Binding of Masslist", TRUE),
),value = "frm"),
tabPanel("Frequent Flyers", withSpinner(plotOutput("freqfls", hover = "ffhover",
brush = brushOpts("ffBrush", resetOnNew = TRUE),
dblclick = "ffDC")),
value = "frf"),
tabPanel("Fragmentation Stats", withSpinner(plotOutput("fragtypes", hover = "fthover",
brush = brushOpts("ftBrush", resetOnNew = TRUE),
dblclick = "ftDC")),
withSpinner(plotOutput("zplot", hover = "zphover",
brush = brushOpts("zpBrush", resetOnNew = TRUE),
dblclick = "zpDC")),
box(checkboxInput("facet3", "Facetting", FALSE),
textInput("seq3", "Sequence", "MKSVITTVVSAADAAGRFPSNSDLESIQGNIQRSAARLEAAEKLAGNHEAVVKEAGDACFAKYAYLKNPGEAGENQEKINKCYRDVDHYMRLVNYCLVVGGTGPLDEWGIAGAREVYRTLNLPTSAYVASIAYTRDRLCVPRDMSAQAGVEFSAYLDYLINALS"),
numericInput("modnum2", "Number of Modifications", 0, 0, 5, 1)
),
value = "frs"),
tabPanel("Energy Resolved Tracing", withSpinner(plotOutput("erplot", hover = "erhover",
brush = brushOpts("erBrush", resetOnNew = TRUE),
dblclick = "erDC")),
box(fileInput("spectra", "Upload Spectra", TRUE),
checkboxInput("facet4", "Facetting", FALSE),
textInput("seq4", "Sequence", ""),
checkboxInput("septerm4", "Separate Termini Processing", TRUE),
numericInput("modnum4", "Number of Modifications", 0, 0, 5, 1),
checkboxInput("bound4", "Binding of Masslist", TRUE)
),
value = "erp"),
id = "conditionedPanels"
),
verbatimTextOutput("info")
)
)
#basicConfig()
#options(shiny.error = browser)
server <- function(input, output, session) {
df <- reactive({
inFiles <- input$fileIn
df <- list()
if (is.null(inFiles))
return(NULL)
for (i in seq_along(inFiles$datapath)) {
if(!grepl(".txt|.masslist|.csv",inFiles$datapath[i])) next
df[[i]] <- read.table(inFiles$datapath[i], header = TRUE, sep = "\t", stringsAsFactors = FALSE)
if("Intensity" %in% colnames(df[[i]]))df[[i]]$modInt <- 100/max(df[[i]]$Intensity)*df[[i]]$Intensity
}
df <- df[!sapply(df, is.null)]
names <- lapply(inFiles$name[grepl(".txt|.masslist|.csv", inFiles$name)], function(x){
str <- strsplit(gsub("_"," ", x), " ")[[1]][grep("[[:alpha:]]", strsplit(gsub("_"," ", x), " ")[[1]])]
if(grepl("STO|TSO|TS", x)) id <- str[2] else id <- str[1]
term <- str_extract(x, "C|N")
mod <- str_split(str_extract(x,"(\\d{1}).masslist"),"\\.")[[1]][1]
energy <- str_extract_all(x, "hcd\\d+|etd\\d+|et\\d?hcd|ethcd\\d?|ethcd\\d+|uvpd\\d+|sf\\d+|iso\\d+|rep\\d+")[[1]]
paste(id, paste(energy, collapse = ""), term, mod, sep = "_")
})
if(length(names) > length(unique(unlist(names)))) {
names <- unlist(names)
names[which(duplicated(names))] <- paste0(names[which(duplicated(names))],"_1")
names
}
if(length(names) > length(unique(names))) {
names[which(duplicated(names))] <- paste0(names[which(duplicated(names))],"_1")
names
}
names(df) <- names
if(input$masslists == TRUE) {
inFiles <<- input$fileIn
df <- combine_masslists(shiny = TRUE)
}
df
})
observe({
# browser()
spectra <- names(df())
updateCheckboxGroupInput(session, "selectFiles", "Select Spectra", choices = spectra,
selected = "")
})
width <- reactive({width <- input$width})
height <- reactive({height <- input$height})
observe({
if(input$selectall == 0) return(NULL)
else if (input$selectall%%2 == 0)
{
updateCheckboxGroupInput(session, "selectFiles", "Select Spectra", choices = names(df()))
} else
{
updateCheckboxGroupInput(session, "selectFiles", "Select Spectra", choices = names(df()), selected = names(df()))
}
})
ranges <- reactiveValues(x = NULL, y = NULL)
observeEvent(input$plotDC, {
brush <- input$plotBrush
if(!is.null(brush)) {
ranges$x <- c(brush$xmin, brush$xmax)
ranges$y <- c(brush$ymin, brush$ymax)
} else {
ranges$x <- NULL
ranges$y <- NULL
}
})
output$mzRange <- renderUI({
data <- df()
data <- data[names(data) %in% chosenspectra()]
minmz <- min(bind_rows(data)$m.z)
maxmz <- max(bind_rows(data)$m.z)
#data <- do.call("rbind", data)
#if(exists(data$Mz)) colnames(data)[colnames(data) == "Mz"] <- "m.z"
if(is.null(ranges$x)) sliderInput("range", "m/z Range:",
min = 0, max = maxmz, value = c(0, round(maxmz, 2)))
else sliderInput("range", "m/z Range:",
min = 0, max = maxmz, value = c(input$range[1], input$range[2]))
})
inputPlotMir <- function() {
mirplot
}
inputPlotCor <- function() {
corplot
}
inputPlotSpa <- function() {
spaplot
}
inputPlotFrm <- function() {
frmplot
}
inputPlotFrf <- function() {
frfplot
}
inputPlotFrs <- function() {
grid.arrange(frtplot, zplot)
}
inputPlotErp <- function() {
erpplot
}
#browser()
output$saveplot <- downloadHandler(filename = function() {if(input$filename != "") {fn <- paste0("_", input$filename)} else {fn <- ""}
paste0(input$conditionedPanels,
fn,".",
input$filetype)},
content = function(file) {
if(input$conditionedPanels == "mir") inputPlot <<- inputPlotMir()
else if(input$conditionedPanels == "cor") inputPlot <<- inputPlotCor()
else if(input$conditionedPanels == "spa") inputPlot <<- inputPlotSpa()
else if(input$conditionedPanels == "frm") inputPlot <<- inputPlotFrm()
else if(input$conditionedPanels == "frf") inputPlot <<- inputPlotFrf()
else if(input$conditionedPanels == "frs") inputPlot <<- inputPlotFrs()
else if(input$conditionedPanels == "erp") inputPlot <<- inputPlotErp()
ggsave(file, plot = inputPlot, device = input$filetype, width = input$width*0.01, height = input$height*0.01)})
chosenspectra <- eventReactive(input$plot, {
ranges$x <<- c(input$range[1], input$range[2])
subspectra <- input$selectFiles
})
output$mirPlot <- renderPlot({
#browser()
data <- df()
ranges$x <- c(input$range[1], input$range[2])
ranges$y <- c(-100, 100)
subspectra <- chosenspectra()
raw1 <- data[[subspectra[1]]]
raw2 <- data[[subspectra[2]]]
#colnames(raw1)[grepl("m.z|Mz|M.z|M.Z")] <- "Mz"
mirplot <<- ggplot(raw1[raw1$m.z <= input$range[2] & raw1$m.z >= input$range[1],],
aes(x = m.z, y = Intensity/max(Intensity)*100)) +
theme_bw() +
geom_histogram(stat = "identity", color = "black") +
geom_histogram(data = raw2[raw2$m.z <= input$range[2] & raw2$m.z >= input$range[1],],
aes(x = m.z, y = -Intensity/max(Intensity)*100), stat = "identity", color = "red") +
geom_hline(yintercept = 0) +
scale_y_continuous(limits = ranges$y) +
scale_x_continuous(limits = ranges$x) +
xlab("m/z") +
ylab("Normalized Intensities")
print(mirplot)
}, width = function(){width()}, height = function(){height()}
)
output$info <- renderText({
mzInt <- function(e) {
if(is.null(e)) return("NULL\n")
paste0("m/z = ", e$x, "\n")
}
mzInt(input$plotHover)
})
output$corPlot <- renderPlot({
data <- df()
subspectra <- chosenspectra()
ranges <<- seq(input$range[1], input$range[2], by = 0.1)
subdataList <- lapply(subspectra, function(x)
{
df <- data[[x]]
#df$exp <- names(data[x])
df <- tapply(df$Intensity, cut(df$m.z, ranges), sum, na.rm = TRUE)
})
subdataDf <- do.call("cbind", subdataList)
colnames(subdataDf) <- subspectra
corMatrix <- cor(subdataDf, use = "pairwise.complete.obs", method = "pearson")
corplot <<- ggcorrplot(corMatrix, method = "square", hc.order = TRUE, lab = TRUE)
print(corplot)
}, width = function(){width()}, height = function(){height()}
)
output$spectrum <- renderPlot({
data <- df()
subspectra <- chosenspectra()
#browser()
inFiles <- input$fileIn
gList <- data[subspectra]
ranges$x <<- c(input$range[1], input$range[2])
ranges$y <<- c(0, 100)
gList <<- lapply(names(gList), function(x) {
df <- gList[[x]]
df <- df[df$m.z <= input$range[2] & df$m.z >= input$range[1],]
df$Intensity <- df$Intensity/max(df$Intensity)*100
df
})
names(gList) <<- subspectra
spaplot <<- annotate_spectrum(data = gList, ranges = ranges, ppm = input$ppm)
print(spaplot)
}, width = function(){width()}, height = function(){height()}
)
output$fragmap <- renderPlot({
#data <- chosenspectra()
inFiles <- input$fileIn[input$fileIn$name %in% chosenspectra(),]
seq <- input$seq
rm("data_merged", "Data_list", pos = ".GlobalEnv")
#gList <- data
#browser()
if(!input$masslists) Data_list <- import_masslists(bound = TRUE, mod.number = input$modnum, shiny = TRUE, files = inFiles)
else Data_list <- df()[names(df()) %in% chosenspectra()]
data_merged <- process_masslists(data = Data_list, ppm = input$ppm, tint = FALSE,
seq = seq, bound = input$masslists)
frmplot <<- fragment_map(data = data_merged, seq = seq)
print(frmplot)
}, width = function(){width()}, height = function(){height()})
output$freqfls <- renderPlot({
file <- input$freqfile
frfplot <<- frqfls(file = file$datapath)
frfplot
}, width = function(){width()}, height = function(){height()})
output$zplot <- renderPlot(
{
inFiles <- input$fileIn[input$fileIn$name %in% chosenspectra(),]
seq <- input$seq
rm("data_merged", "Data_list", pos = ".GlobalEnv")
#browser()
if(!input$masslists) Data_list <- import_masslists(bound = TRUE, mod.number = input$modnum, shiny = TRUE, files = inFiles)
else Data_list <- df()[names(df()) %in% chosenspectra()]
data_merged <- process_masslists(data = Data_list, ppm = input$ppm,
tint = FALSE, seq = seq,
bound = input$masslists)
if(length(unique(data_merged$Charge)) == 1) return()
zplot <<- fragment_charges(data = data_merged, seq = seq)
zplot
}, width = function(){width()}, height = function(){height()}
)
output$fragtypes <- renderPlot(
{
inFiles <- input$fileIn[input$fileIn$name %in% chosenspectra(),]
seq <- input$seq
rm("data_merged", "Data_list", pos = ".GlobalEnv")
#browser()
if(!input$masslists) Data_list <- import_masslists(bound = TRUE, mod.number = input$modnum, shiny = TRUE, files = inFiles)
else Data_list <- df()[names(df()) %in% chosenspectra()]
data_merged <- process_masslists(data = Data_list, ppm = input$ppm,
tint = FALSE, seq = seq,
bound = input$masslists)
frtplot <<- fragment_types(data = data_merged)
frtplot
}, width = function(){width()}, height = function(){height()}
)
output$tscplot <- renderPlot(
{
inFiles <- input$fileIn[input$fileIn$name %in% chosenspectra(),]
seq <- input$seq
rm("data_merged", "Data_list", pos = ".GlobalEnv")
#browser()
Data_list <<- import_masslists(bound = TRUE, mod.number = input$modnum, shiny = TRUE, files = inFiles)
data_merged <<- prepare_data_frame_term_sep_aa_all(sep_term = TRUE,
mod.number = input$modnum,
ppm = input$ppm, tint = FALSE, seq = seq)
tscplot <<- termini_sequence_coverage(data = data_merged, ppm = input$ppm)
tscplot
}, width = function(){width()}, height = function(){height()}
)
}
shinyApp(ui = ui, server = server)
stamara6/LeanTopDown documentation built on May 7, 2019, 1:31 p.m.
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#
# This is a Shiny web application. You can run the application by clicking
# the 'Run App' button above.
#
# Find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com/
#
# source("C:\\Users\\stama\\OneDrive\\Documents\\R\\Projects\\LeanTopDown\\R/helpers.R", local = TRUE)
# source("C:\\Users\\stama\\OneDrive\\Documents\\R\\Projects\\LeanTopDown\\R/spectrum annotator.R", local = TRUE)
# source("C:\\Users\\stama\\OneDrive\\Documents\\R\\Projects\\LeanTopDown\\R/freqflyers.R", local = TRUE)
# source("C:\\Users\\stama\\OneDrive\\Documents\\R\\Projects\\LeanTopDown\\R/frgmntstats.R", local = TRUE)
library(stringr)
library(shiny)
library(ggplot2)
library(reshape2)
library(ggcorrplot)
library(shinyjs)
library(logging)
library(shinycssloaders)
library(shinydashboard)
#library(LeanTopDown)
library(gridExtra)
ui <- dashboardPage(
dashboardHeader(title = "LeanTopDown"),
dashboardSidebar(
sidebarMenu(
conditionalPanel(condition = "input.conditionedPanels == 'mir'"
#checkboxInput("masslists", "Process Masslists", FALSE),
),
conditionalPanel(condition = "input.conditionedPanels == 'cor'"
#checkboxInput("masslists2", "Process Masslists", FALSE),
),
conditionalPanel(condition = "input.conditionedPanels == 'spa'"
),
conditionalPanel(condition = "input.conditionedPanels == 'frm'"
),
conditionalPanel(condition = "input.conditionedPanels == 'frf'",
fileInput("freqfile", "Frequent Flyers File", FALSE)),
conditionalPanel(condition = "input.conditionedPanels == 'frs'"
),
conditionalPanel(condition = "input.conditionedPanels == 'erp'"
),
actionButton("plot", "Plot"),
downloadButton("saveplot", "Save Plot"),
numericInput("width", "Plot Width", 480, 320, 5120, 160),
numericInput("height", "Plot Height", 400, 320, 5120, 160),
radioButtons("filetype", "Save as:",
choices = c("pdf", "png")),
textInput("filename", "File name:", ""),
uiOutput("mzRange"),
numericInput("ppm", "Accuracy", 3.5, 0.5, 20, 0.5),
checkboxInput("masslists", "Combine Masslists", FALSE),
fileInput("fileIn", "Upload Masslists", TRUE),
actionLink("selectall","Select All"),
checkboxGroupInput("selectFiles", "Select Spectra", c("1" = "1"))
)),
dashboardBody(
tabsetPanel(
tabPanel("mirRaw Plot", withSpinner(plotOutput("mirPlot", hover = "plotHover",
brush = brushOpts("plotBrush", resetOnNew = TRUE),
dblclick = "plotDC")),
value = "mir"),
tabPanel("Correlation Plot", withSpinner(plotOutput("corPlot")), value = "cor"),
tabPanel("Spectrum Annotation", withSpinner(plotOutput("spectrum", hover = "spechover",
brush = brushOpts("specBrush", resetOnNew = TRUE),
dblclick = "specDC")),
box(checkboxInput("facet", "Facetting", FALSE)),
value = "spa"),
tabPanel("Fragment Maps", withSpinner(plotOutput("fragmap", hover = "fmhover",
brush = brushOpts("fmBrush", resetOnNew = TRUE),
dblclick = "fmDC")),
box(checkboxInput("facet2", "Facetting", FALSE),
textInput("seq", "Sequence", "MKSVITTVVSAADAAGRFPSNSDLESIQGNIQRSAARLEAAEKLAGNHEAVVKEAGDACFAKYAYLKNPGEAGENQEKINKCYRDVDHYMRLVNYCLVVGGTGPLDEWGIAGAREVYRTLNLPTSAYVASIAYTRDRLCVPRDMSAQAGVEFSAYLDYLINALS"),
#checkboxInput("septerm", "Separate Termini Processing", TRUE),
numericInput("modnum", "Number of Modifications", 0, 0, 5, 1)
#checkboxInput("bound", "Binding of Masslist", TRUE),
),value = "frm"),
tabPanel("Frequent Flyers", withSpinner(plotOutput("freqfls", hover = "ffhover",
brush = brushOpts("ffBrush", resetOnNew = TRUE),
dblclick = "ffDC")),
value = "frf"),
tabPanel("Fragmentation Stats", withSpinner(plotOutput("fragtypes", hover = "fthover",
brush = brushOpts("ftBrush", resetOnNew = TRUE),
dblclick = "ftDC")),
withSpinner(plotOutput("zplot", hover = "zphover",
brush = brushOpts("zpBrush", resetOnNew = TRUE),
dblclick = "zpDC")),
box(checkboxInput("facet3", "Facetting", FALSE),
textInput("seq3", "Sequence", "MKSVITTVVSAADAAGRFPSNSDLESIQGNIQRSAARLEAAEKLAGNHEAVVKEAGDACFAKYAYLKNPGEAGENQEKINKCYRDVDHYMRLVNYCLVVGGTGPLDEWGIAGAREVYRTLNLPTSAYVASIAYTRDRLCVPRDMSAQAGVEFSAYLDYLINALS"),
numericInput("modnum2", "Number of Modifications", 0, 0, 5, 1)
),
value = "frs"),
tabPanel("Energy Resolved Tracing", withSpinner(plotOutput("erplot", hover = "erhover",
brush = brushOpts("erBrush", resetOnNew = TRUE),
dblclick = "erDC")),
box(fileInput("spectra", "Upload Spectra", TRUE),
checkboxInput("facet4", "Facetting", FALSE),
textInput("seq4", "Sequence", ""),
checkboxInput("septerm4", "Separate Termini Processing", TRUE),
numericInput("modnum4", "Number of Modifications", 0, 0, 5, 1),
checkboxInput("bound4", "Binding of Masslist", TRUE)
),
value = "erp"),
id = "conditionedPanels"
),
verbatimTextOutput("info")
)
)
#basicConfig()
#options(shiny.error = browser)
server <- function(input, output, session) {
df <- reactive({
inFiles <- input$fileIn
df <- list()
if (is.null(inFiles))
return(NULL)
for (i in seq_along(inFiles$datapath)) {
if(!grepl(".txt|.masslist|.csv",inFiles$datapath[i])) next
df[[i]] <- read.table(inFiles$datapath[i], header = TRUE, sep = "\t", stringsAsFactors = FALSE)
if("Intensity" %in% colnames(df[[i]]))df[[i]]$modInt <- 100/max(df[[i]]$Intensity)*df[[i]]$Intensity
}
df <- df[!sapply(df, is.null)]
names <- lapply(inFiles$name[grepl(".txt|.masslist|.csv", inFiles$name)], function(x){
str <- strsplit(gsub("_"," ", x), " ")[[1]][grep("[[:alpha:]]", strsplit(gsub("_"," ", x), " ")[[1]])]
if(grepl("STO|TSO|TS", x)) id <- str[2] else id <- str[1]
term <- str_extract(x, "C|N")
mod <- str_split(str_extract(x,"(\\d{1}).masslist"),"\\.")[[1]][1]
energy <- str_extract_all(x, "hcd\\d+|etd\\d+|et\\d?hcd|ethcd\\d?|ethcd\\d+|uvpd\\d+|sf\\d+|iso\\d+|rep\\d+")[[1]]
paste(id, paste(energy, collapse = ""), term, mod, sep = "_")
})
if(length(names) > length(unique(unlist(names)))) {
names <- unlist(names)
names[which(duplicated(names))] <- paste0(names[which(duplicated(names))],"_1")
names
}
if(length(names) > length(unique(names))) {
names[which(duplicated(names))] <- paste0(names[which(duplicated(names))],"_1")
names
}
names(df) <- names
if(input$masslists == TRUE) {
inFiles <<- input$fileIn
df <- combine_masslists(shiny = TRUE)
}
df
})
observe({
# browser()
spectra <- names(df())
updateCheckboxGroupInput(session, "selectFiles", "Select Spectra", choices = spectra,
selected = "")
})
width <- reactive({width <- input$width})
height <- reactive({height <- input$height})
observe({
if(input$selectall == 0) return(NULL)
else if (input$selectall%%2 == 0)
{
updateCheckboxGroupInput(session, "selectFiles", "Select Spectra", choices = names(df()))
} else
{
updateCheckboxGroupInput(session, "selectFiles", "Select Spectra", choices = names(df()), selected = names(df()))
}
})
ranges <- reactiveValues(x = NULL, y = NULL)
observeEvent(input$plotDC, {
brush <- input$plotBrush
if(!is.null(brush)) {
ranges$x <- c(brush$xmin, brush$xmax)
ranges$y <- c(brush$ymin, brush$ymax)
} else {
ranges$x <- NULL
ranges$y <- NULL
}
})
output$mzRange <- renderUI({
data <- df()
data <- data[names(data) %in% chosenspectra()]
minmz <- min(bind_rows(data)$m.z)
maxmz <- max(bind_rows(data)$m.z)
#data <- do.call("rbind", data)
#if(exists(data$Mz)) colnames(data)[colnames(data) == "Mz"] <- "m.z"
if(is.null(ranges$x)) sliderInput("range", "m/z Range:",
min = 0, max = maxmz, value = c(0, round(maxmz, 2)))
else sliderInput("range", "m/z Range:",
min = 0, max = maxmz, value = c(input$range[1], input$range[2]))
})
inputPlotMir <- function() {
mirplot
}
inputPlotCor <- function() {
corplot
}
inputPlotSpa <- function() {
spaplot
}
inputPlotFrm <- function() {
frmplot
}
inputPlotFrf <- function() {
frfplot
}
inputPlotFrs <- function() {
grid.arrange(frtplot, zplot)
}
inputPlotErp <- function() {
erpplot
}
#browser()
output$saveplot <- downloadHandler(filename = function() {if(input$filename != "") {fn <- paste0("_", input$filename)} else {fn <- ""}
paste0(input$conditionedPanels,
fn,".",
input$filetype)},
content = function(file) {
if(input$conditionedPanels == "mir") inputPlot <<- inputPlotMir()
else if(input$conditionedPanels == "cor") inputPlot <<- inputPlotCor()
else if(input$conditionedPanels == "spa") inputPlot <<- inputPlotSpa()
else if(input$conditionedPanels == "frm") inputPlot <<- inputPlotFrm()
else if(input$conditionedPanels == "frf") inputPlot <<- inputPlotFrf()
else if(input$conditionedPanels == "frs") inputPlot <<- inputPlotFrs()
else if(input$conditionedPanels == "erp") inputPlot <<- inputPlotErp()
ggsave(file, plot = inputPlot, device = input$filetype, width = input$width*0.01, height = input$height*0.01)})
chosenspectra <- eventReactive(input$plot, {
ranges$x <<- c(input$range[1], input$range[2])
subspectra <- input$selectFiles
})
output$mirPlot <- renderPlot({
#browser()
data <- df()
ranges$x <- c(input$range[1], input$range[2])
ranges$y <- c(-100, 100)
subspectra <- chosenspectra()
raw1 <- data[[subspectra[1]]]
raw2 <- data[[subspectra[2]]]
#colnames(raw1)[grepl("m.z|Mz|M.z|M.Z")] <- "Mz"
mirplot <<- ggplot(raw1[raw1$m.z <= input$range[2] & raw1$m.z >= input$range[1],],
aes(x = m.z, y = Intensity/max(Intensity)*100)) +
theme_bw() +
geom_histogram(stat = "identity", color = "black") +
geom_histogram(data = raw2[raw2$m.z <= input$range[2] & raw2$m.z >= input$range[1],],
aes(x = m.z, y = -Intensity/max(Intensity)*100), stat = "identity", color = "red") +
geom_hline(yintercept = 0) +
scale_y_continuous(limits = ranges$y) +
scale_x_continuous(limits = ranges$x) +
xlab("m/z") +
ylab("Normalized Intensities")
print(mirplot)
}, width = function(){width()}, height = function(){height()}
)
output$info <- renderText({
mzInt <- function(e) {
if(is.null(e)) return("NULL\n")
paste0("m/z = ", e$x, "\n")
}
mzInt(input$plotHover)
})
output$corPlot <- renderPlot({
data <- df()
subspectra <- chosenspectra()
ranges <<- seq(input$range[1], input$range[2], by = 0.1)
subdataList <- lapply(subspectra, function(x)
{
df <- data[[x]]
#df$exp <- names(data[x])
df <- tapply(df$Intensity, cut(df$m.z, ranges), sum, na.rm = TRUE)
})
subdataDf <- do.call("cbind", subdataList)
colnames(subdataDf) <- subspectra
corMatrix <- cor(subdataDf, use = "pairwise.complete.obs", method = "pearson")
corplot <<- ggcorrplot(corMatrix, method = "square", hc.order = TRUE, lab = TRUE)
print(corplot)
}, width = function(){width()}, height = function(){height()}
)
output$spectrum <- renderPlot({
data <- df()
subspectra <- chosenspectra()
#browser()
inFiles <- input$fileIn
gList <- data[subspectra]
ranges$x <<- c(input$range[1], input$range[2])
ranges$y <<- c(0, 100)
gList <<- lapply(names(gList), function(x) {
df <- gList[[x]]
df <- df[df$m.z <= input$range[2] & df$m.z >= input$range[1],]
df$Intensity <- df$Intensity/max(df$Intensity)*100
df
})
names(gList) <<- subspectra
spaplot <<- annotate_spectrum(data = gList, ranges = ranges, ppm = input$ppm)
print(spaplot)
}, width = function(){width()}, height = function(){height()}
)
output$fragmap <- renderPlot({
#data <- chosenspectra()
inFiles <- input$fileIn[input$fileIn$name %in% chosenspectra(),]
seq <- input$seq
rm("data_merged", "Data_list", pos = ".GlobalEnv")
#gList <- data
#browser()
if(!input$masslists) Data_list <- import_masslists(bound = TRUE, mod.number = input$modnum, shiny = TRUE, files = inFiles)
else Data_list <- df()[names(df()) %in% chosenspectra()]
data_merged <- process_masslists(data = Data_list, ppm = input$ppm, tint = FALSE,
seq = seq, bound = input$masslists)
frmplot <<- fragment_map(data = data_merged, seq = seq)
print(frmplot)
}, width = function(){width()}, height = function(){height()})
output$freqfls <- renderPlot({
file <- input$freqfile
frfplot <<- frqfls(file = file$datapath)
frfplot
}, width = function(){width()}, height = function(){height()})
output$zplot <- renderPlot(
{
inFiles <- input$fileIn[input$fileIn$name %in% chosenspectra(),]
seq <- input$seq
rm("data_merged", "Data_list", pos = ".GlobalEnv")
#browser()
if(!input$masslists) Data_list <- import_masslists(bound = TRUE, mod.number = input$modnum, shiny = TRUE, files = inFiles)
else Data_list <- df()[names(df()) %in% chosenspectra()]
data_merged <- process_masslists(data = Data_list, ppm = input$ppm,
tint = FALSE, seq = seq,
bound = input$masslists)
if(length(unique(data_merged$Charge)) == 1) return()
zplot <<- fragment_charges(data = data_merged, seq = seq)
zplot
}, width = function(){width()}, height = function(){height()}
)
output$fragtypes <- renderPlot(
{
inFiles <- input$fileIn[input$fileIn$name %in% chosenspectra(),]
seq <- input$seq
rm("data_merged", "Data_list", pos = ".GlobalEnv")
#browser()
if(!input$masslists) Data_list <- import_masslists(bound = TRUE, mod.number = input$modnum, shiny = TRUE, files = inFiles)
else Data_list <- df()[names(df()) %in% chosenspectra()]
data_merged <- process_masslists(data = Data_list, ppm = input$ppm,
tint = FALSE, seq = seq,
bound = input$masslists)
frtplot <<- fragment_types(data = data_merged)
frtplot
}, width = function(){width()}, height = function(){height()}
)
output$tscplot <- renderPlot(
{
inFiles <- input$fileIn[input$fileIn$name %in% chosenspectra(),]
seq <- input$seq
rm("data_merged", "Data_list", pos = ".GlobalEnv")
#browser()
Data_list <<- import_masslists(bound = TRUE, mod.number = input$modnum, shiny = TRUE, files = inFiles)
data_merged <<- prepare_data_frame_term_sep_aa_all(sep_term = TRUE,
mod.number = input$modnum,
ppm = input$ppm, tint = FALSE, seq = seq)
tscplot <<- termini_sequence_coverage(data = data_merged, ppm = input$ppm)
tscplot
}, width = function(){width()}, height = function(){height()}
)
}
shinyApp(ui = ui, server = server)
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