R/LOB_viewdata.R
In hholm/LOB_tools: Additional Data Screening And Cleaning Tools For LOBSTAHS
Defines functions
LOB_viewdata
Documented in
LOB_viewdata
LOB_viewdata <- function(peakdata, rawSpec = NULL){
#Make sure we have our librarys loaded
#library(shiny)
#library(tidyverse)
#library(RColorBrewer)
#library(ggplot2)
# Example
if (!class(peakdata) %in% c("data.frame","LOBSet")) {
stop("Input peakdata is neither a 'data.frame' nor 'LOBSet'.")
}
#Rename our peak list so we can modify it and keep the complete one
if (is.data.frame(peakdata)) {
run <- peakdata
}else{
run <- LOBSTAHS::peakdata(peakdata)
}
# Set up our large color pallete
palette <-c("#E41A1C","#377EB8","#4DAF4A", "#984EA3", "#FF7F00", "#FFFF33", "#A65628", "#F781BF",
"#999999", "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#FFFF33", "#A65628",
"#F781BF", "#999999", "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#FFFF33",
"#A65628", "#F781BF", "#999999", "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00",
"#FFFF33", "#A65628", "#F781BF", "#999999", "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3",
"#FF7F00", "#FFFF33", "#A65628", "#F781BF", "#999999", "#E41A1C", "#377EB8", "#4DAF4A",
"#984EA3", "#FF7F00", "#FFFF33", "#A65628", "#F781BF", "#999999", "#E41A1C", "#377EB8",
"#4DAF4A", "#984EA3", "#FF7F00", "#FFFF33", "#A65628", "#F781BF", "#999999", "#E41A1C",
"#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#FFFF33", "#A65628", "#F781BF", "#999999",
"#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#FFFF33", "#A65628", "#F781BF",
"#999999", "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#FFFF33", "#A65628",
"#F781BF", "#999999", "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#FFFF33",
"#A65628", "#F781BF", "#999999")
# Define the app
app=shinyApp(
ui = fluidPage(
title = "Lipid Data Viewer",
tabsetPanel(
tabPanel(
plotOutput('plot',height = "800px",click = "plot_click"),
title = "M/Z vs RT",
br(),
column(3,
h4("Lipid Data Viewer"),
checkboxInput('x_auto', 'Auto X-Axis',value = TRUE),
sliderInput('rt', 'X-Axis Limits (Retention Time)',
min=floor(min(run$peakgroup_rt)),
max=ceiling(max(run$peakgroup_rt)),
value = c(floor(min(run$peakgroup_rt)),ceiling(max(run$peakgroup_rt))),
step=10, round=1),
checkboxInput('y_auto', 'Auto Y-Axis',value = TRUE),
sliderInput('mz', 'Y-Axis Limits (m/z)',
min=floor(min(run$LOBdbase_mz,na.rm = TRUE)),
max=ceiling(max(run$LOBdbase_mz,na.rm = TRUE)),
value = c(floor(min(run$LOBdbase_mz,na.rm = TRUE)),ceiling(max(run$LOBdbase_mz,na.rm = TRUE))),
step=10, round=1),
checkboxInput('text', 'Display Names'),
checkboxInput('oxy', 'Toggle Oxidized Compounds '),
checkboxInput('false', 'Toggle False Assignments ')
),
column(3,
selectInput('class', 'Select Lipid Class', c("All", as.character(unique(run$species))), multiple = TRUE, selected = "All"),
selectInput('color', 'Point Color', c('None','Carbon','Double Bonds', 'Degree Oxidation','Species', 'Lipid Class', 'lpSolve Fitted', 'RF_Window', 'Lipid Class','Adduct Summary','Final Code', 'PosNeg Match')),
selectInput('total_carbon', 'Acyl Carbon', c('All',unique(run$FA_total_no_C)), multiple = TRUE, selected = "All"),
selectInput('total_db', 'Doubled Bonds', c('All',unique(run$FA_total_no_DB)), multiple = TRUE, selected = "All"),
selectInput('deg_ox', 'Degree Oxidation', c('All',unique(run$degree_oxidation)), multiple = TRUE, selected = "All"),
selectInput('sizebysample', 'Size by Sample', c("None", colnames(run[13:(length(run)-29)])), multiple = FALSE, selected = "None"
),
selectInput('plot_extras', 'Plot Extras', c("RTF_Window", "Labels", "Oxidized Labels"), multiple = TRUE)),
column(6,
tableOutput(outputId = "info"),
actionButton(inputId = "Find_ms2",label = "Check for MS2"),
actionButton(inputId = "Plot_ms2",label = "Plot MS2"),
textInput(inputId = "ms2_file",label = "File for MS2",value = "most_scans"),
numericInput(inputId = "ppm",label = "ppm",value = 100,min = 0.5,step = 1),
numericInput(inputId = "rtspan",label = "Retention Time Window (s)",value = 200,min = 0,step = 30),
textOutput(outputId = 'no_sel'),
tableOutput(outputId = 'ms2_table')
)),
tabPanel(
plotOutput('ms2'),
title = "Chromatogram and MS2",
column(4,
selectInput('species', 'Select Species', c("All",as.character(unique(run$species))),multiple = FALSE),
selectInput('xaxis', 'X_Variable', c('None','Carbon','Double Bonds','lpSolve Fitted','Lipid Class'), selected = 'Carbon'),
selectInput('fill_colors', 'Fill_Colors', c('Carbon', 'Double Bonds', 'Species'))
),
column(4,
selectInput('flag', "Flag?", c("All", as.character(unique(run$Flag))), multiple = TRUE, selected = "All"))
),
tabPanel(
plotOutput('bar'),
title = "Distributions",
column(4,
selectInput('species', 'Select Species', c("All",as.character(unique(run$species))),multiple = FALSE),
selectInput('xaxis', 'X_Variable', c('None','Carbon','Double Bonds','lpSolve Fitted','Lipid Class'), selected = 'Carbon'),
selectInput('fill_colors', 'Fill_Colors', c('Carbon', 'Double Bonds', 'Species'))
),
column(4,
selectInput('flag', "Flag?", c("All", as.character(unique(run$Flag))), multiple = TRUE, selected = "All"))
)
)
),
# Define server logic to draw our plot
server = function(input, output) {
#Set object as NULL to prevent crashing
run_table <- NULL
# Will update as variables change
output$plot <- renderPlot({
data <- run #so we dont change our intial data
# To plot all data
if("All"%in%input$class!=TRUE){
data <- data[which(data$species %in% input$class),]
}
# To elimate oxy compounds if desired
if(input$oxy){
data <- data[data$degree_oxidation=="0",]
}
# To elimate false assignments if desired
if(input$false){
data <- data[data$code!="False_Assignment",]
}
# only look at certain acyl lengths
if("All" %in% input$total_carbon != TRUE){
data <- data[data$FA_total_no_C %in% as.numeric(input$total_carbon),]
}
# Look at certain DB lengths
if("All" %in% input$total_db != TRUE){
data <- data[data$FA_total_no_DB %in% as.numeric(input$total_db),]
}
# Look at certain degrees of oxidation
if("All" %in% input$deg_ox != TRUE){
data <- data[data$degree_oxidation %in% as.numeric(input$deg_ox),]
}
# Construct inital plot with limits and points
g <- ggplot(data = data,mapping = aes(x = peakgroup_rt, y = LOBdbase_mz)) +
geom_point(size = 3) +
xlab("Retention Time (sec)") +
ylab("m/z")
if(input$x_auto==FALSE){
g <- g + xlim(c(input$rt[1],input$rt[2]))
}
if(input$y_auto==FALSE){
g <- g + ylim(c(input$mz[1],input$mz[2]))
}
#adding labels to each point
if(!is.null(input$plot_extras)){
if("Labels" %in% input$plot_extras){
g <- g +
geom_text(aes(x = peakgroup_rt, y = LOBdbase_mz,
label = paste0(FA_total_no_C,":", FA_total_no_DB),
hjust = 1, vjust = 2))
}}
#adding oxidation labels to each point
if(!is.null(input$plot_extras)){
if("Oxidized Labels" %in% input$plot_extras){
g <- g +
geom_text(aes(x = peakgroup_rt, y = LOBdbase_mz,
label = paste0(FA_total_no_C,":",FA_total_no_DB,":",degree_oxidation),
hjust = 1, vjust = 2))
}}
# change point size by sample
if (input$sizebysample != "None"){
g <- g +
geom_point(data = data, mapping = aes(x = peakgroup_rt, y = LOBdbase_mz))+
geom_point(aes(size = !!as.symbol(input$sizebysample)))
}
# Add colors for carbon number
if(input$color=="Carbon"){
g <- g + geom_point(aes(color=as.character(FA_total_no_C), fill = as.character(FA_total_no_C)), size =3) +
scale_color_manual(values = palette)
}
# Add color for DB number
if(input$color=="Double Bonds"){
g <- g + geom_point(aes(color=as.character(FA_total_no_DB), fill = as.character(FA_total_no_DB)),size=3) +
scale_color_manual(values = palette)
}
# Add color for degree oxidation
if(input$color=="Degree Oxidation"){
g <- g + geom_point(aes(color=as.character(degree_oxidation), fill = as.character(degree_oxidation)),size=3) +
scale_color_manual(values = palette)
}
# Add color for species
if(input$color=="Species"){
g <- g + geom_point(aes(color=species, fill = species),size=3) +
scale_color_manual(values = palette)
}
# Add color for lipid class
if(input$color=="Lipid Class"){
g <- g + geom_point(aes(color=lipid_class, fill = lipid_class),size=3) +
scale_color_manual(values = palette)
}
#Add color for final code
if(input$color=="Final Code"){
g <- g + geom_point(aes(color=as.character(code), fill = as.character(code)),size=3) +
scale_color_manual(values = c("LP_Solve_Confirmed"="#66CD00", "10%_rtv"="#66CD00","False_Assignment"="#FF3030", "Red"="#FF3030","RTF_Confirmed"="#2aff00", "ms2v"="#0000FF", "5%_rtv"="#2aff00","LP_Solve_Maybe"="#ff9e44", "Double_Peak?"="#ff9e44", "Double Check"="#ff9e44","Unknown"="#000000", "LP_Solve_Failure"="#B22222", "RTF_Failure"="#B22222"))
}
#Add color for final code
if(input$color=="PosNeg Match"){
g <- g + geom_point(aes(color=as.character(posneg_check), fill = as.character(posneg_check)),size=3) +
scale_color_manual(values = c("No Match" = "#FF3030", "PosNeg Match" = "#2aff00", "Check Multiple Matches" = "#ff9e44", "Unknown" = "#000000"))
}
#Add color for adduct summary
if(input$color=="Adduct Summary"){
g <- g + geom_point(aes(color=as.character(adduct_summary), fill = as.character(adduct_summary)),size=3) +
scale_color_manual(values = c("Completely_satisfied"="#2aff00","Somewhat_satisfied"="#ff9e44","No_other_adducts"="#B22222"))
}
# Add colors for lpSolve solutions
if(input$color=="lpSolve Fitted"){
g <- g + geom_point(aes(color=as.character(lpSolve), fill = as.character(lpSolve)),size=3) +
scale_color_manual(values = c("#E8DA1E","#FF3030","#B6EEA6"))
}
# Add colors for RF windows
if(input$color=="RF_Window"){
g <- g +
geom_point(aes(color=as.character(Flag), fill = as.character(Flag)),size=3) +
scale_color_manual(values = c("LP_Solve_Confirmed"="#66CD00", "10%_rtv"="#66CD00","False_Assignment"="#FF3030", "Red"="#FF3030","RTF_Confirmed"="#2aff00", "ms2v"="#0000FF", "5%_rtv"="#2aff00","LP_Solve_Maybe"="#ff9e44", "Double_Peak?"="#ff9e44", "Double Check"="#ff9e44","Unknown"="#000000", "LP_Solve_Failure"="#B22222", "RTF_Failure"="#B22222"))
}
if(!is.null(input$plot_extras)){
if("RTF_Window" %in% input$plot_extras){
g <- g +
geom_point(aes(x = peakgroup_rt/DNPPE_Factor*DBase_DNPPE_RF, y = LOBdbase_mz, color = as.character(Flag)), shape = 3)+
geom_errorbarh(aes(xmax = peakgroup_rt/DNPPE_Factor*DBase_DNPPE_RF*1.1, xmin = peakgroup_rt/DNPPE_Factor*DBase_DNPPE_RF*0.9, height = 0.2, y = LOBdbase_mz, color = as.character(Flag)))
}}
# Add colors for classes
if(input$color=="Lipid Class"){
g <- g + geom_point(aes(color=as.character(species), fill = as.character(species)),size=3) +
scale_color_manual(values = palette)
}
# Add compound names
if (input$text){
g <- g + geom_text(aes(label=compound_name),hjust=1,vjust=2,size=3)
}
output$info <- renderTable({
# With ggplot2, no need to tell it what the x and y variables are.
# threshold: set max distance, in pixels
# maxpoints: maximum number of rows to return
# addDist: add column with distance, in pixels
run_table <- nearPoints(data, input$plot_click, threshold = 20, maxpoints = 1,
addDist = TRUE)
columns <- c("match_ID","xcms_peakgroup","compound_name","LOBdbase_mz","peakgroup_rt","Flag","lpSolve","code", "posneg_check")
run[which(run$xcms_peakgroup == run_table$xcms_peakgroup),columns[which(columns %in% colnames(run))]]
}, digits = 5)
observeEvent(eventExpr = input$Find_ms2, {
if (is.null(rawSpec)) {
output$no_sel <- renderText(paste("No rawSpec objected loaded to read MS2 from."))
}else{
run_table <- nearPoints(data, input$plot_click, threshold = 20, maxpoints = 1,
addDist = TRUE)
withProgress(expr = {
incProgress(amount = 0.5,message = "Working...")
if(nrow(run_table)==0){
output$no_sel <- renderText(
"Please click a feature on the plot to select it first.")
}else{
output$no_sel <- renderText(
paste("Searching for ms2 data for mass",as.character(run_table$LOBdbase_mz),"... please wait."))
ms2 <- LOB_findMS2(XCMSnExp = rawSpec,
mz = run_table$LOBdbase_mz,
rt = run_table$peakgroup_rt,
ppm_pre = input$ppm,
rtspan = input$rtspan)
output$ms2_table <- renderTable({
ms2[[1]]
})
if (class(ms2[[1]]) == "data.frame") {
output$no_sel <- renderText(
paste("Searching for ms2 data for mass",as.character(run_table$LOBdbase_mz),"... Done. First file with most scans:",as.character(names(which(table(ms2[[1]][,'file']) == max(table(ms2[[1]][,'file']))))[1]))
)}
# output$no_sel <- renderText("Searching for ms2 data... Done!")
}})
}})
observeEvent(eventExpr = input$Plot_ms2, {
if (is.null(rawSpec)) {
output$no_sel <- renderText(paste("No rawSpec objected loaded to read MS2 from."))
}else{
run_table <- nearPoints(data, input$plot_click, threshold = 20, maxpoints = 1,
addDist = TRUE)
withProgress(expr = {
incProgress(amount = 0.5,message = "Working...")
if(nrow(run_table)==0){
output$no_sel <- renderText(
"Please click a feature on the plot to select it first.")
}else{
output$no_sel <- renderText(
paste("Plotting ms2 data for mass",as.character(run_table$LOBdbase_mz),"... please wait."))
ms2plot <- LOB_plotMS2(XCMSnExp = rawSpec,
mz = run_table$LOBdbase_mz,
rt = run_table$peakgroup_rt,
ppm_pre = input$ppm,
rtspan = input$rtspan,
plot_file = input$ms2_file)
output$ms2plot <- renderImage({
ms2plot[[1]]
})
if (class(ms2plot[[1]]) == "data.frame") {
output$no_sel <- renderText(
paste("Searching for ms2 data for mass",as.character(run_table$LOBdbase_mz),"... Done. First file with most scans:",as.character(names(which(table(ms2[[1]][,'file']) == max(table(ms2[[1]][,'file']))))[1]))
)}
# output$no_sel <- renderText("Searching for ms2 data... Done!")
}})
}})
g
})
# output$bar <- renderPlot({
# tidy_run <- run %>%
# gather(key = Sample_ID,
# value = Peak_Size,
# -species, -compound_name, -LOBdbase_mz,
# -peakgroup_rt, -degree_oxidation,
# -FA_total_no_C, -FA_total_no_DB, -Flag)
# tidy_data <- tidy_run %>%
# filter(is.na(FA_total_no_C) != TRUE)
# tidy_subset <- tidy_data[tidy_data$species==input$species,]
#
# # further subset for specific flags
# if(input$flag != "All"){
# tidy_subset <- tidy_subset[tidy_subset$Flag == as.character(input$flag),]
# }
#
# # if("All"%in%input$species!=TRUE){
# # tidy_data <- tidy_data[tidy_data$species==input$species,]
# # }
#
# # To elimate oxy compounds if desired
# # if(input$oxy){
# # tidy_data <- tidy_data[tidy_data$degree_oxidation=="0",]
# # }
#
# # Construct inital plot with limits and points
# b <- ggplot(data = tidy_subset, aes(x = FA_total_no_C,y = Peak_Size))+
# geom_bar(stat = "identity", position = "stack") +
# scale_color_manual(values = palette)+# Add colors for carbon number
# xlab("as.character(input$xaxis)") +
# ylab("Peak Size")+
# theme(
# axis.text.x = element_blank(),
# axis.text.y = element_blank(),
# axis.ticks = element_blank())
#
# if(input$xaxis=="Carbon"){
# b <- ggplot(data = tidy_subset, aes(FA_total_no_C,y = Peak_Size)) +
# geom_bar(stat = "identity", position = "stack") +
# scale_color_manual(values = palette)+
# xlab(paste(input$xaxis)) +
# ylab("Peak Size")# Add colors for carbon number
#
# }
#
# # Add color for DB number
# if(input$xaxis=="Double Bonds"){
# b <- ggplot(data = tidy_subset, aes(FA_total_no_DB, y = Peak_Size)) +
# geom_bar(stat = "identity", position = "stack") +
# scale_color_manual(values = palette)+
# xlab(paste(input$xaxis)) +
# ylab("Peak Size")# Add colors for carbon number
# }
#
# # Add colors
# if(input$fill_colors=="Double Bonds"){
# b <- b + geom_point(aes(fill=FA_total_no_DB)) +
# scale_color_manual(values = palette)
# }
#
#
#
# print(b)
#
# })
}
)
runApp(app)
}
hholm/LOB_tools documentation built on Jan. 10, 2025, 7:14 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions LOB_viewdata
Documented in LOB_viewdata
LOB_viewdata <- function(peakdata, rawSpec = NULL){
#Make sure we have our librarys loaded
#library(shiny)
#library(tidyverse)
#library(RColorBrewer)
#library(ggplot2)
# Example
if (!class(peakdata) %in% c("data.frame","LOBSet")) {
stop("Input peakdata is neither a 'data.frame' nor 'LOBSet'.")
}
#Rename our peak list so we can modify it and keep the complete one
if (is.data.frame(peakdata)) {
run <- peakdata
}else{
run <- LOBSTAHS::peakdata(peakdata)
}
# Set up our large color pallete
palette <-c("#E41A1C","#377EB8","#4DAF4A", "#984EA3", "#FF7F00", "#FFFF33", "#A65628", "#F781BF",
"#999999", "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#FFFF33", "#A65628",
"#F781BF", "#999999", "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#FFFF33",
"#A65628", "#F781BF", "#999999", "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00",
"#FFFF33", "#A65628", "#F781BF", "#999999", "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3",
"#FF7F00", "#FFFF33", "#A65628", "#F781BF", "#999999", "#E41A1C", "#377EB8", "#4DAF4A",
"#984EA3", "#FF7F00", "#FFFF33", "#A65628", "#F781BF", "#999999", "#E41A1C", "#377EB8",
"#4DAF4A", "#984EA3", "#FF7F00", "#FFFF33", "#A65628", "#F781BF", "#999999", "#E41A1C",
"#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#FFFF33", "#A65628", "#F781BF", "#999999",
"#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#FFFF33", "#A65628", "#F781BF",
"#999999", "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#FFFF33", "#A65628",
"#F781BF", "#999999", "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#FFFF33",
"#A65628", "#F781BF", "#999999")
# Define the app
app=shinyApp(
ui = fluidPage(
title = "Lipid Data Viewer",
tabsetPanel(
tabPanel(
plotOutput('plot',height = "800px",click = "plot_click"),
title = "M/Z vs RT",
br(),
column(3,
h4("Lipid Data Viewer"),
checkboxInput('x_auto', 'Auto X-Axis',value = TRUE),
sliderInput('rt', 'X-Axis Limits (Retention Time)',
min=floor(min(run$peakgroup_rt)),
max=ceiling(max(run$peakgroup_rt)),
value = c(floor(min(run$peakgroup_rt)),ceiling(max(run$peakgroup_rt))),
step=10, round=1),
checkboxInput('y_auto', 'Auto Y-Axis',value = TRUE),
sliderInput('mz', 'Y-Axis Limits (m/z)',
min=floor(min(run$LOBdbase_mz,na.rm = TRUE)),
max=ceiling(max(run$LOBdbase_mz,na.rm = TRUE)),
value = c(floor(min(run$LOBdbase_mz,na.rm = TRUE)),ceiling(max(run$LOBdbase_mz,na.rm = TRUE))),
step=10, round=1),
checkboxInput('text', 'Display Names'),
checkboxInput('oxy', 'Toggle Oxidized Compounds '),
checkboxInput('false', 'Toggle False Assignments ')
),
column(3,
selectInput('class', 'Select Lipid Class', c("All", as.character(unique(run$species))), multiple = TRUE, selected = "All"),
selectInput('color', 'Point Color', c('None','Carbon','Double Bonds', 'Degree Oxidation','Species', 'Lipid Class', 'lpSolve Fitted', 'RF_Window', 'Lipid Class','Adduct Summary','Final Code', 'PosNeg Match')),
selectInput('total_carbon', 'Acyl Carbon', c('All',unique(run$FA_total_no_C)), multiple = TRUE, selected = "All"),
selectInput('total_db', 'Doubled Bonds', c('All',unique(run$FA_total_no_DB)), multiple = TRUE, selected = "All"),
selectInput('deg_ox', 'Degree Oxidation', c('All',unique(run$degree_oxidation)), multiple = TRUE, selected = "All"),
selectInput('sizebysample', 'Size by Sample', c("None", colnames(run[13:(length(run)-29)])), multiple = FALSE, selected = "None"
),
selectInput('plot_extras', 'Plot Extras', c("RTF_Window", "Labels", "Oxidized Labels"), multiple = TRUE)),
column(6,
tableOutput(outputId = "info"),
actionButton(inputId = "Find_ms2",label = "Check for MS2"),
actionButton(inputId = "Plot_ms2",label = "Plot MS2"),
textInput(inputId = "ms2_file",label = "File for MS2",value = "most_scans"),
numericInput(inputId = "ppm",label = "ppm",value = 100,min = 0.5,step = 1),
numericInput(inputId = "rtspan",label = "Retention Time Window (s)",value = 200,min = 0,step = 30),
textOutput(outputId = 'no_sel'),
tableOutput(outputId = 'ms2_table')
)),
tabPanel(
plotOutput('ms2'),
title = "Chromatogram and MS2",
column(4,
selectInput('species', 'Select Species', c("All",as.character(unique(run$species))),multiple = FALSE),
selectInput('xaxis', 'X_Variable', c('None','Carbon','Double Bonds','lpSolve Fitted','Lipid Class'), selected = 'Carbon'),
selectInput('fill_colors', 'Fill_Colors', c('Carbon', 'Double Bonds', 'Species'))
),
column(4,
selectInput('flag', "Flag?", c("All", as.character(unique(run$Flag))), multiple = TRUE, selected = "All"))
),
tabPanel(
plotOutput('bar'),
title = "Distributions",
column(4,
selectInput('species', 'Select Species', c("All",as.character(unique(run$species))),multiple = FALSE),
selectInput('xaxis', 'X_Variable', c('None','Carbon','Double Bonds','lpSolve Fitted','Lipid Class'), selected = 'Carbon'),
selectInput('fill_colors', 'Fill_Colors', c('Carbon', 'Double Bonds', 'Species'))
),
column(4,
selectInput('flag', "Flag?", c("All", as.character(unique(run$Flag))), multiple = TRUE, selected = "All"))
)
)
),
# Define server logic to draw our plot
server = function(input, output) {
#Set object as NULL to prevent crashing
run_table <- NULL
# Will update as variables change
output$plot <- renderPlot({
data <- run #so we dont change our intial data
# To plot all data
if("All"%in%input$class!=TRUE){
data <- data[which(data$species %in% input$class),]
}
# To elimate oxy compounds if desired
if(input$oxy){
data <- data[data$degree_oxidation=="0",]
}
# To elimate false assignments if desired
if(input$false){
data <- data[data$code!="False_Assignment",]
}
# only look at certain acyl lengths
if("All" %in% input$total_carbon != TRUE){
data <- data[data$FA_total_no_C %in% as.numeric(input$total_carbon),]
}
# Look at certain DB lengths
if("All" %in% input$total_db != TRUE){
data <- data[data$FA_total_no_DB %in% as.numeric(input$total_db),]
}
# Look at certain degrees of oxidation
if("All" %in% input$deg_ox != TRUE){
data <- data[data$degree_oxidation %in% as.numeric(input$deg_ox),]
}
# Construct inital plot with limits and points
g <- ggplot(data = data,mapping = aes(x = peakgroup_rt, y = LOBdbase_mz)) +
geom_point(size = 3) +
xlab("Retention Time (sec)") +
ylab("m/z")
if(input$x_auto==FALSE){
g <- g + xlim(c(input$rt[1],input$rt[2]))
}
if(input$y_auto==FALSE){
g <- g + ylim(c(input$mz[1],input$mz[2]))
}
#adding labels to each point
if(!is.null(input$plot_extras)){
if("Labels" %in% input$plot_extras){
g <- g +
geom_text(aes(x = peakgroup_rt, y = LOBdbase_mz,
label = paste0(FA_total_no_C,":", FA_total_no_DB),
hjust = 1, vjust = 2))
}}
#adding oxidation labels to each point
if(!is.null(input$plot_extras)){
if("Oxidized Labels" %in% input$plot_extras){
g <- g +
geom_text(aes(x = peakgroup_rt, y = LOBdbase_mz,
label = paste0(FA_total_no_C,":",FA_total_no_DB,":",degree_oxidation),
hjust = 1, vjust = 2))
}}
# change point size by sample
if (input$sizebysample != "None"){
g <- g +
geom_point(data = data, mapping = aes(x = peakgroup_rt, y = LOBdbase_mz))+
geom_point(aes(size = !!as.symbol(input$sizebysample)))
}
# Add colors for carbon number
if(input$color=="Carbon"){
g <- g + geom_point(aes(color=as.character(FA_total_no_C), fill = as.character(FA_total_no_C)), size =3) +
scale_color_manual(values = palette)
}
# Add color for DB number
if(input$color=="Double Bonds"){
g <- g + geom_point(aes(color=as.character(FA_total_no_DB), fill = as.character(FA_total_no_DB)),size=3) +
scale_color_manual(values = palette)
}
# Add color for degree oxidation
if(input$color=="Degree Oxidation"){
g <- g + geom_point(aes(color=as.character(degree_oxidation), fill = as.character(degree_oxidation)),size=3) +
scale_color_manual(values = palette)
}
# Add color for species
if(input$color=="Species"){
g <- g + geom_point(aes(color=species, fill = species),size=3) +
scale_color_manual(values = palette)
}
# Add color for lipid class
if(input$color=="Lipid Class"){
g <- g + geom_point(aes(color=lipid_class, fill = lipid_class),size=3) +
scale_color_manual(values = palette)
}
#Add color for final code
if(input$color=="Final Code"){
g <- g + geom_point(aes(color=as.character(code), fill = as.character(code)),size=3) +
scale_color_manual(values = c("LP_Solve_Confirmed"="#66CD00", "10%_rtv"="#66CD00","False_Assignment"="#FF3030", "Red"="#FF3030","RTF_Confirmed"="#2aff00", "ms2v"="#0000FF", "5%_rtv"="#2aff00","LP_Solve_Maybe"="#ff9e44", "Double_Peak?"="#ff9e44", "Double Check"="#ff9e44","Unknown"="#000000", "LP_Solve_Failure"="#B22222", "RTF_Failure"="#B22222"))
}
#Add color for final code
if(input$color=="PosNeg Match"){
g <- g + geom_point(aes(color=as.character(posneg_check), fill = as.character(posneg_check)),size=3) +
scale_color_manual(values = c("No Match" = "#FF3030", "PosNeg Match" = "#2aff00", "Check Multiple Matches" = "#ff9e44", "Unknown" = "#000000"))
}
#Add color for adduct summary
if(input$color=="Adduct Summary"){
g <- g + geom_point(aes(color=as.character(adduct_summary), fill = as.character(adduct_summary)),size=3) +
scale_color_manual(values = c("Completely_satisfied"="#2aff00","Somewhat_satisfied"="#ff9e44","No_other_adducts"="#B22222"))
}
# Add colors for lpSolve solutions
if(input$color=="lpSolve Fitted"){
g <- g + geom_point(aes(color=as.character(lpSolve), fill = as.character(lpSolve)),size=3) +
scale_color_manual(values = c("#E8DA1E","#FF3030","#B6EEA6"))
}
# Add colors for RF windows
if(input$color=="RF_Window"){
g <- g +
geom_point(aes(color=as.character(Flag), fill = as.character(Flag)),size=3) +
scale_color_manual(values = c("LP_Solve_Confirmed"="#66CD00", "10%_rtv"="#66CD00","False_Assignment"="#FF3030", "Red"="#FF3030","RTF_Confirmed"="#2aff00", "ms2v"="#0000FF", "5%_rtv"="#2aff00","LP_Solve_Maybe"="#ff9e44", "Double_Peak?"="#ff9e44", "Double Check"="#ff9e44","Unknown"="#000000", "LP_Solve_Failure"="#B22222", "RTF_Failure"="#B22222"))
}
if(!is.null(input$plot_extras)){
if("RTF_Window" %in% input$plot_extras){
g <- g +
geom_point(aes(x = peakgroup_rt/DNPPE_Factor*DBase_DNPPE_RF, y = LOBdbase_mz, color = as.character(Flag)), shape = 3)+
geom_errorbarh(aes(xmax = peakgroup_rt/DNPPE_Factor*DBase_DNPPE_RF*1.1, xmin = peakgroup_rt/DNPPE_Factor*DBase_DNPPE_RF*0.9, height = 0.2, y = LOBdbase_mz, color = as.character(Flag)))
}}
# Add colors for classes
if(input$color=="Lipid Class"){
g <- g + geom_point(aes(color=as.character(species), fill = as.character(species)),size=3) +
scale_color_manual(values = palette)
}
# Add compound names
if (input$text){
g <- g + geom_text(aes(label=compound_name),hjust=1,vjust=2,size=3)
}
output$info <- renderTable({
# With ggplot2, no need to tell it what the x and y variables are.
# threshold: set max distance, in pixels
# maxpoints: maximum number of rows to return
# addDist: add column with distance, in pixels
run_table <- nearPoints(data, input$plot_click, threshold = 20, maxpoints = 1,
addDist = TRUE)
columns <- c("match_ID","xcms_peakgroup","compound_name","LOBdbase_mz","peakgroup_rt","Flag","lpSolve","code", "posneg_check")
run[which(run$xcms_peakgroup == run_table$xcms_peakgroup),columns[which(columns %in% colnames(run))]]
}, digits = 5)
observeEvent(eventExpr = input$Find_ms2, {
if (is.null(rawSpec)) {
output$no_sel <- renderText(paste("No rawSpec objected loaded to read MS2 from."))
}else{
run_table <- nearPoints(data, input$plot_click, threshold = 20, maxpoints = 1,
addDist = TRUE)
withProgress(expr = {
incProgress(amount = 0.5,message = "Working...")
if(nrow(run_table)==0){
output$no_sel <- renderText(
"Please click a feature on the plot to select it first.")
}else{
output$no_sel <- renderText(
paste("Searching for ms2 data for mass",as.character(run_table$LOBdbase_mz),"... please wait."))
ms2 <- LOB_findMS2(XCMSnExp = rawSpec,
mz = run_table$LOBdbase_mz,
rt = run_table$peakgroup_rt,
ppm_pre = input$ppm,
rtspan = input$rtspan)
output$ms2_table <- renderTable({
ms2[[1]]
})
if (class(ms2[[1]]) == "data.frame") {
output$no_sel <- renderText(
paste("Searching for ms2 data for mass",as.character(run_table$LOBdbase_mz),"... Done. First file with most scans:",as.character(names(which(table(ms2[[1]][,'file']) == max(table(ms2[[1]][,'file']))))[1]))
)}
# output$no_sel <- renderText("Searching for ms2 data... Done!")
}})
}})
observeEvent(eventExpr = input$Plot_ms2, {
if (is.null(rawSpec)) {
output$no_sel <- renderText(paste("No rawSpec objected loaded to read MS2 from."))
}else{
run_table <- nearPoints(data, input$plot_click, threshold = 20, maxpoints = 1,
addDist = TRUE)
withProgress(expr = {
incProgress(amount = 0.5,message = "Working...")
if(nrow(run_table)==0){
output$no_sel <- renderText(
"Please click a feature on the plot to select it first.")
}else{
output$no_sel <- renderText(
paste("Plotting ms2 data for mass",as.character(run_table$LOBdbase_mz),"... please wait."))
ms2plot <- LOB_plotMS2(XCMSnExp = rawSpec,
mz = run_table$LOBdbase_mz,
rt = run_table$peakgroup_rt,
ppm_pre = input$ppm,
rtspan = input$rtspan,
plot_file = input$ms2_file)
output$ms2plot <- renderImage({
ms2plot[[1]]
})
if (class(ms2plot[[1]]) == "data.frame") {
output$no_sel <- renderText(
paste("Searching for ms2 data for mass",as.character(run_table$LOBdbase_mz),"... Done. First file with most scans:",as.character(names(which(table(ms2[[1]][,'file']) == max(table(ms2[[1]][,'file']))))[1]))
)}
# output$no_sel <- renderText("Searching for ms2 data... Done!")
}})
}})
g
})
# output$bar <- renderPlot({
# tidy_run <- run %>%
# gather(key = Sample_ID,
# value = Peak_Size,
# -species, -compound_name, -LOBdbase_mz,
# -peakgroup_rt, -degree_oxidation,
# -FA_total_no_C, -FA_total_no_DB, -Flag)
# tidy_data <- tidy_run %>%
# filter(is.na(FA_total_no_C) != TRUE)
# tidy_subset <- tidy_data[tidy_data$species==input$species,]
#
# # further subset for specific flags
# if(input$flag != "All"){
# tidy_subset <- tidy_subset[tidy_subset$Flag == as.character(input$flag),]
# }
#
# # if("All"%in%input$species!=TRUE){
# # tidy_data <- tidy_data[tidy_data$species==input$species,]
# # }
#
# # To elimate oxy compounds if desired
# # if(input$oxy){
# # tidy_data <- tidy_data[tidy_data$degree_oxidation=="0",]
# # }
#
# # Construct inital plot with limits and points
# b <- ggplot(data = tidy_subset, aes(x = FA_total_no_C,y = Peak_Size))+
# geom_bar(stat = "identity", position = "stack") +
# scale_color_manual(values = palette)+# Add colors for carbon number
# xlab("as.character(input$xaxis)") +
# ylab("Peak Size")+
# theme(
# axis.text.x = element_blank(),
# axis.text.y = element_blank(),
# axis.ticks = element_blank())
#
# if(input$xaxis=="Carbon"){
# b <- ggplot(data = tidy_subset, aes(FA_total_no_C,y = Peak_Size)) +
# geom_bar(stat = "identity", position = "stack") +
# scale_color_manual(values = palette)+
# xlab(paste(input$xaxis)) +
# ylab("Peak Size")# Add colors for carbon number
#
# }
#
# # Add color for DB number
# if(input$xaxis=="Double Bonds"){
# b <- ggplot(data = tidy_subset, aes(FA_total_no_DB, y = Peak_Size)) +
# geom_bar(stat = "identity", position = "stack") +
# scale_color_manual(values = palette)+
# xlab(paste(input$xaxis)) +
# ylab("Peak Size")# Add colors for carbon number
# }
#
# # Add colors
# if(input$fill_colors=="Double Bonds"){
# b <- b + geom_point(aes(fill=FA_total_no_DB)) +
# scale_color_manual(values = palette)
# }
#
#
#
# print(b)
#
# })
}
)
runApp(app)
}
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.