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diff --git a/cmml/18-0008_Eva_Maleckova/GC-MS/180219_Eva_Maleckova.xlsx b/cmml/18-0008_Eva_Maleckova/GC-MS/180219_Eva_Maleckova.xlsx
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diff --git a/cmml/18-0008_Eva_Maleckova/GC-MS/181204_DoubleChecked/.Rhistory b/cmml/18-0008_Eva_Maleckova/GC-MS/181204_DoubleChecked/.Rhistory
new file mode 100755
index 0000000000000000000000000000000000000000..ae6dba55493a809698fc07c5a45dd470029816c2
--- /dev/null
+++ b/cmml/18-0008_Eva_Maleckova/GC-MS/181204_DoubleChecked/.Rhistory
@@ -0,0 +1,167 @@
+rm(list = ls())
+### Mac dir tree or ### PC dir tree
+if(dir.exists('/Volumes/data/')){setwd('/Volumes/data/')}; if(dir.exists('M:/MSlab/')){setwd('M:/')}
+source('MSlab/17_Dominik_Brilhaus/00_CustomR_Functions/01_MSLab.R')
+wd <- 'MSlab/05_projects/18-0008_Eva_Maleckova/GC-MS/'
+setwd(wd)
+required.packages <- c("Rmisc", "plyr", "ggplot2", "reshape2", "gridExtra", 'openxlsx')
+for(package in required.packages)
+{
+print(package)
+## Check if package is installed. If not, install
+if(!package %in% row.names(installed.packages())){install.packages(package, repos ="https://cran.uni-muenster.de/")}
+# ## Check if package is up to date. If not, update
+# update.packages(package, repos = "https://cran.uni-muenster.de/")
+## Load package
+library(package, character.only = T)
+}
+theme_dominik <-
+theme(panel.grid = element_blank(), panel.background = element_blank(), panel.border = element_rect(fill = NA)) +
+theme(axis.text = element_text(color = "black"), axis.ticks = element_line(color = "black"), axis.title = element_text(color = "black")) +
+theme(plot.title = element_text(face= "bold")) +
+theme(aspect.ratio = 1) +
+theme(strip.background = element_blank(), strip.text = element_text(size = 10, face = "bold")) +
+theme(legend.position = "right",  legend.title = element_blank()) #legend.direction = "vertical",
+nice.date <- format(Sys.time(), "%y%m%d")
+report.xlsx <- dir(pattern = 'QuantReport')
+report.xlsx <- grep('xlsx', value = T, report.xlsx)
+report.xlsx
+rm(list = ls())
+### Mac dir tree or ### PC dir tree
+if(dir.exists('/Volumes/data/')){setwd('/Volumes/data/')}; if(dir.exists('M:/MSlab/')){setwd('M:/')}
+source('MSlab/17_Dominik_Brilhaus/00_CustomR_Functions/01_MSLab.R')
+wd <- 'MSlab/05_projects/18-0008_Eva_Maleckova/GC-MS/181204_DoubleChecked/'
+setwd(wd)
+#################################################
+required.packages <- c("Rmisc", "plyr", "ggplot2", "reshape2", "gridExtra", 'openxlsx')
+for(package in required.packages)
+{
+print(package)
+## Check if package is installed. If not, install
+if(!package %in% row.names(installed.packages())){install.packages(package, repos ="https://cran.uni-muenster.de/")}
+# ## Check if package is up to date. If not, update
+# update.packages(package, repos = "https://cran.uni-muenster.de/")
+## Load package
+library(package, character.only = T)
+}
+theme_dominik <-
+theme(panel.grid = element_blank(), panel.background = element_blank(), panel.border = element_rect(fill = NA)) +
+theme(axis.text = element_text(color = "black"), axis.ticks = element_line(color = "black"), axis.title = element_text(color = "black")) +
+theme(plot.title = element_text(face= "bold")) +
+theme(aspect.ratio = 1) +
+theme(strip.background = element_blank(), strip.text = element_text(size = 10, face = "bold")) +
+theme(legend.position = "right",  legend.title = element_blank()) #legend.direction = "vertical",
+nice.date <- format(Sys.time(), "%y%m%d")
+#################################################
+### Identify quant report
+report.xlsx <- dir(pattern = 'QuantReport')
+report.xlsx <- grep('xlsx', value = T, report.xlsx)
+collect.reports <- list()
+pdf(paste(nice.date, "QC_QuantReport.pdf", sep = '_'), width = 15, height = 15)
+for(report.name in report.xlsx)
+{
+## Load QuantReport book
+GC.report <- read.xlsx(report.name, "Summary")
+clean.report <- report.extract(GC.report)
+clean.report$data.source <- report.name
+colnames(clean.report) <- gsub(' ', '.', colnames(clean.report))
+### Rename compounds
+clean.report$Compound <- gsub("Gaba", "GABA", clean.report$Compound)
+clean.report$Compound <- gsub("a ", "alpha-", clean.report$Compound)
+clean.report$Compound <- gsub("b ", "beta-", clean.report$Compound)
+clean.report$Compound <- gsub("ic Acid", "ate", clean.report$Compound)
+clean.report$Compound <- gsub(" 2TMS", "", clean.report$Compound)
+# clean.report$Compound <- gsub(" 3TMS", "", clean.report$Compound)
+clean.report[!grepl("alpha-", clean.report$Compound) & !grepl("beta-", clean.report$Compound), "Compound"] <- paste("'", clean.report[!grepl("alpha-", clean.report$Compound) & !grepl("beta-", clean.report$Compound), "Compound"], "'", sep = "")
+colnames(clean.report) <- gsub(" ", ".", colnames(clean.report))
+#### Distinguish between split and splitless
+#### and keep only those compounds that passed the manual qc
+split.df <- data.frame(Acq.Method.File = unique(clean.report$Acq.Method.File))
+split.df[grepl("split", unique(split.df$Acq.Method.File), ignore.case = T) & !grepl("splitles", unique(split.df$Acq.Method.File), ignore.case = T), "Acq.Method.Condensed"] <- "split"
+split.df[grepl("splitles", unique(split.df$Acq.Method.File), ignore.case = T), "Acq.Method.Condensed"] <- "splitless"
+###
+warning("Double-check correct assignment of split / splitless")
+print(split.df)
+clean.report <- merge(clean.report, split.df, "Acq.Method.File")
+unique(clean.report[, c('Sample.Type','Sample.Name')])
+clean.report[clean.report$Sample.Name == 'Ara.Mix', 'Sample.Type'] <- 'QC.Standard'
+collect.reports[[report.name]] <- clean.report
+#
+# ################################################################################################################
+# ### Plot the response of all samples against the response in blank
+# ################################################################################################################
+#
+# pdf(paste(nice.date, "QC_ComparisonBlankIndividual.pdf", sep = '_'), width = 9, height = 6)
+#
+# for(i in sort(unique(clean.report$Compound)))
+# {
+#
+#   compound.sub <- subset(clean.report,  Sample.Type != 'Standard' & Compound == i)
+#   t.tests <- c()
+#   for(m in unique(compound.sub$Acq.Method.Condensed))
+#   {
+#
+#     x <- subset(compound.sub, Acq.Method.Condensed == m)
+#
+#     blank <- subset(x, Sample.Type == 'Blank', Resp, drop = T)
+#     samples <- subset(x, Sample.Type == 'Sample', Resp, drop = T)
+#
+#     FC <- round(mean(samples) / mean(blank), 1)
+#
+#     if(length(blank) > 2 & length(samples) > 2){p <- signif(t.test(blank, samples)$p.value, 3)}else{p <- ''}
+#
+#
+#     t.tests <- rbind(t.tests, data.frame(FC, p, Acq.Method.Condensed = m, Resp = (max(samples))))
+#   }
+#
+#
+#   print(
+#     ggplot(compound.sub, aes(x = Sample.Type, y = Resp)) +
+#       geom_boxplot() +
+#       geom_text(data = t.tests, x = 1 , vjust = 1, aes(label = paste(FC, 'x \np: ', p, sep = ''))) +
+#       theme_dominik +
+#       facet_wrap(~Acq.Method.Condensed, scales = "free", labeller = label_parsed) +
+#       labs(y = 'non-normalized response',   caption = wd) +
+#       # scale_color_brewer(palette = "Dark2") +
+#       ggtitle(parse(text = i))
+#   )
+#
+# }
+#
+# dev.off()
+#
+#
+scaled.within.compound <- c()
+for(i in unique(clean.report$Compound))
+{
+sub <- subset(clean.report, Compound == i)
+sub$sResp <- sub$Resp / max(sub$Resp)
+scaled.within.compound <- rbind(scaled.within.compound, sub)
+}
+scaled.within.compound$Compound <- factor(scaled.within.compound$Compound, levels = sort(unique(scaled.within.compound$Compound)))
+print(ggplot(subset(scaled.within.compound, Sample.Type != 'Standard'), aes(x = Compound, y = Resp)) +
+geom_boxplot(aes(fill = Sample.Type)) +
+theme_dominik +
+facet_wrap(~Acq.Method.Condensed, scales = "free_y", ncol = 1) +
+labs(y = 'non-normalized response\nscaled by compound', caption = wd) +
+theme(aspect.ratio = 0.5, axis.text.x = element_text(angle = 45, hjust = 1)) +
+scale_x_discrete(labels = parse(text = as.character(levels(scaled.within.compound$Compound)))) +
+scale_fill_brewer(palette = "Dark2"))
+a <- dcast(subset(clean.report, Sample.Type == 'Sample'), Sample.Name~Compound, value.var = 'Resp')
+clean.report$Compound <- factor(clean.report$Compound, levels = names(sort(apply(a[, 2 : ncol(a)], 2, max))))
+print(
+ggplot(subset(clean.report, Sample.Type == 'Sample'), aes(x = Compound, y = Resp, label = Sample.Name)) +
+geom_text(size = 4) +
+theme_dominik +
+facet_wrap(~Acq.Method.Condensed, scales = "free_y", ncol = 1) +
+labs(y = 'non-normalized response', caption = wd) +
+theme(aspect.ratio = 1, axis.text.x = element_text(angle = 45, hjust = 1)) +
+scale_x_discrete(labels = parse(text = as.character(levels(clean.report$Compound)))) +
+scale_fill_brewer(palette = "Dark2")
+)
+clean.report$Compound <- gsub("'", "", clean.report$Compound, fixed = T)
+collect.reports[[report.name]] <- clean.report
+}
+dev.off()
+names(collect.reports) <- paste0('Report', 1:length(collect.reports))
+write.xlsx(collect.reports, asTable = T,  file = paste(nice.date, "CleanReports.xlsx", sep = '_'))
diff --git a/cmml/18-0008_Eva_Maleckova/GC-MS/181204_DoubleChecked/181204_CleanReport.xlsx b/cmml/18-0008_Eva_Maleckova/GC-MS/181204_DoubleChecked/181204_CleanReport.xlsx
new file mode 100755
index 0000000000000000000000000000000000000000..a49d7aa864976dfcccb630ddd9cf8fe2f11f3aa3
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diff --git a/cmml/18-0008_Eva_Maleckova/GC-MS/181204_DoubleChecked/181204_QC_QuantReport.R b/cmml/18-0008_Eva_Maleckova/GC-MS/181204_DoubleChecked/181204_QC_QuantReport.R
new file mode 100755
index 0000000000000000000000000000000000000000..d9ae9bfc957e661d22cbaa800e123e6f46106440
--- /dev/null
+++ b/cmml/18-0008_Eva_Maleckova/GC-MS/181204_DoubleChecked/181204_QC_QuantReport.R
@@ -0,0 +1,201 @@
+ 
+rm(list = ls())
+
+### Mac dir tree or ### PC dir tree
+if(dir.exists('/Volumes/data/')){setwd('/Volumes/data/')}; if(dir.exists('M:/MSlab/')){setwd('M:/')}
+
+source('MSlab/19_MS-Team/05_Dominik_Brilhaus/00_CustomR_Functions/01_MSLab.R')
+
+wd <- 'MSlab/21_projects/18-0008_Eva_Maleckova/GC-MS/181204_DoubleChecked/'
+setwd(wd)
+
+#################################################
+
+required.packages <- c("Rmisc", "plyr", "ggplot2", "reshape2", "gridExtra", 'openxlsx')
+
+for(package in required.packages)
+{
+ print(package)
+ ## Check if package is installed. If not, install
+ if(!package %in% row.names(installed.packages())){install.packages(package, repos ="https://cran.uni-muenster.de/")}
+ # ## Check if package is up to date. If not, update
+ # update.packages(package, repos = "https://cran.uni-muenster.de/")
+ ## Load package
+ library(package, character.only = T)
+}
+
+
+theme_dominik <- 
+  theme(panel.grid = element_blank(), panel.background = element_blank(), panel.border = element_rect(fill = NA)) + 
+  theme(axis.text = element_text(color = "black"), axis.ticks = element_line(color = "black"), axis.title = element_text(color = "black")) +
+  theme(plot.title = element_text(face= "bold")) +
+  theme(aspect.ratio = 1) +
+  theme(strip.background = element_blank(), strip.text = element_text(size = 10, face = "bold")) + 
+  theme(legend.position = "right",  legend.title = element_blank()) #legend.direction = "vertical",
+
+nice.date <- format(Sys.time(), "%y%m%d")
+
+
+################################################# 
+### Identify quant report
+
+report.xlsx <- dir(pattern = 'QuantReport')
+report.xlsx <- grep('xlsx', value = T, report.xlsx)
+
+collect.reports <- list()
+
+pdf(paste(nice.date, "QC_QuantReport.pdf", sep = '_'), width = 15, height = 15)
+for(report.name in report.xlsx)
+{
+  
+  ## Load QuantReport book
+  
+    
+  GC.report <- read.xlsx(report.name, "Summary")
+  clean.report <- report.extract(GC.report)
+  clean.report$data.source <- report.name
+  
+  colnames(clean.report) <- gsub(' ', '.', colnames(clean.report))
+  
+  
+  ### Rename compounds
+  clean.report$Compound <- gsub("Gaba", "GABA", clean.report$Compound)
+  clean.report$Compound <- gsub("a ", "alpha-", clean.report$Compound)
+  clean.report$Compound <- gsub("b ", "beta-", clean.report$Compound)
+  clean.report$Compound <- gsub("ic Acid", "ate", clean.report$Compound)
+  clean.report$Compound <- gsub(" 2TMS", "", clean.report$Compound)
+  # clean.report$Compound <- gsub(" 3TMS", "", clean.report$Compound)
+  
+  clean.report[!grepl("alpha-", clean.report$Compound) & !grepl("beta-", clean.report$Compound), "Compound"] <- paste("'", clean.report[!grepl("alpha-", clean.report$Compound) & !grepl("beta-", clean.report$Compound), "Compound"], "'", sep = "")
+  
+  colnames(clean.report) <- gsub(" ", ".", colnames(clean.report))
+  
+  
+  #### Distinguish between split and splitless 
+  #### and keep only those compounds that passed the manual qc
+  
+  split.df <- data.frame(Acq.Method.File = unique(clean.report$Acq.Method.File))
+  split.df[grepl("split", unique(split.df$Acq.Method.File), ignore.case = T) & !grepl("splitles", unique(split.df$Acq.Method.File), ignore.case = T), "Acq.Method.Condensed"] <- "split"
+  split.df[grepl("splitles", unique(split.df$Acq.Method.File), ignore.case = T), "Acq.Method.Condensed"] <- "splitless"
+  
+  ### 
+  warning("Double-check correct assignment of split / splitless")
+  print(split.df)
+  
+  clean.report <- merge(clean.report, split.df, "Acq.Method.File")
+  
+  
+  unique(clean.report[, c('Sample.Type','Sample.Name')])
+  
+  clean.report[clean.report$Sample.Name == 'Ara.Mix', 'Sample.Type'] <- 'QC.Standard'
+  
+  
+  
+  collect.reports[[report.name]] <- clean.report
+  
+  
+  
+  
+  # 
+  # ################################################################################################################
+  # ### Plot the response of all samples against the response in blank
+  # ################################################################################################################
+  # 
+  # pdf(paste(nice.date, "QC_ComparisonBlankIndividual.pdf", sep = '_'), width = 9, height = 6)
+  # 
+  # for(i in sort(unique(clean.report$Compound)))
+  # {
+  #   
+  #   compound.sub <- subset(clean.report,  Sample.Type != 'Standard' & Compound == i)
+  #   t.tests <- c()
+  #   for(m in unique(compound.sub$Acq.Method.Condensed))
+  #   {
+  #     
+  #     x <- subset(compound.sub, Acq.Method.Condensed == m)
+  #     
+  #     blank <- subset(x, Sample.Type == 'Blank', Resp, drop = T)
+  #     samples <- subset(x, Sample.Type == 'Sample', Resp, drop = T)
+  #     
+  #     FC <- round(mean(samples) / mean(blank), 1)
+  #     
+  #     if(length(blank) > 2 & length(samples) > 2){p <- signif(t.test(blank, samples)$p.value, 3)}else{p <- ''}
+  #     
+  #     
+  #     t.tests <- rbind(t.tests, data.frame(FC, p, Acq.Method.Condensed = m, Resp = (max(samples))))
+  #   }
+  #   
+  #   
+  #   print(
+  #     ggplot(compound.sub, aes(x = Sample.Type, y = Resp)) +
+  #       geom_boxplot() +
+  #       geom_text(data = t.tests, x = 1 , vjust = 1, aes(label = paste(FC, 'x \np: ', p, sep = ''))) + 
+  #       theme_dominik +
+  #       facet_wrap(~Acq.Method.Condensed, scales = "free", labeller = label_parsed) +
+  #       labs(y = 'non-normalized response',   caption = wd) +
+  #       # scale_color_brewer(palette = "Dark2") + 
+  #       ggtitle(parse(text = i))
+  #   )
+  #   
+  # }
+  # 
+  # dev.off()
+  # 
+  # 
+  
+  
+  scaled.within.compound <- c()
+  for(i in unique(clean.report$Compound))
+  {
+    sub <- subset(clean.report, Compound == i)
+    
+    
+    sub$sResp <- sub$Resp / max(sub$Resp)  
+    
+    scaled.within.compound <- rbind(scaled.within.compound, sub)
+    
+  }
+  
+  scaled.within.compound$Compound <- factor(scaled.within.compound$Compound, levels = sort(unique(scaled.within.compound$Compound)))
+  
+  
+  print(ggplot(subset(scaled.within.compound, Sample.Type != 'Standard'), aes(x = Compound, y = Resp)) + 
+    geom_boxplot(aes(fill = Sample.Type)) +
+    theme_dominik +
+    facet_wrap(~Acq.Method.Condensed, scales = "free_y", ncol = 1) +
+    labs(y = 'non-normalized response\nscaled by compound', caption = wd) +
+    theme(aspect.ratio = 0.5, axis.text.x = element_text(angle = 45, hjust = 1)) + 
+    scale_x_discrete(labels = parse(text = as.character(levels(scaled.within.compound$Compound)))) +
+    scale_fill_brewer(palette = "Dark2"))
+  
+  
+  a <- dcast(subset(clean.report, Sample.Type == 'Sample'), Sample.Name~Compound, value.var = 'Resp')
+  clean.report$Compound <- factor(clean.report$Compound, levels = names(sort(apply(a[, 2 : ncol(a)], 2, max))))
+  
+  
+  
+  print(
+  ggplot(subset(clean.report, Sample.Type == 'Sample'), aes(x = Compound, y = Resp, label = Sample.Name)) + 
+    geom_text(size = 4) + 
+    theme_dominik +
+    facet_wrap(~Acq.Method.Condensed, scales = "free_y", ncol = 1) +
+    labs(y = 'non-normalized response', caption = wd) +
+    theme(aspect.ratio = 1, axis.text.x = element_text(angle = 45, hjust = 1)) + 
+    scale_x_discrete(labels = parse(text = as.character(levels(clean.report$Compound)))) +
+    scale_fill_brewer(palette = "Dark2")
+  )
+  
+  clean.report$Compound <- gsub("'", "", clean.report$Compound, fixed = T)
+  collect.reports[[report.name]] <- clean.report
+  
+  
+}
+dev.off()
+
+
+names(collect.reports) <- paste0('Report', 1:length(collect.reports))
+
+write.xlsx(collect.reports, asTable = T,  file = paste(nice.date, "CleanReports.xlsx", sep = '_'))
+
+
+
+
diff --git a/cmml/18-0008_Eva_Maleckova/GC-MS/181204_DoubleChecked/181204_QC_QuantReport.pdf b/cmml/18-0008_Eva_Maleckova/GC-MS/181204_DoubleChecked/181204_QC_QuantReport.pdf
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diff --git a/cmml/18-0008_Eva_Maleckova/LC-QTof/180621_Eva_02.xls b/cmml/18-0008_Eva_Maleckova/LC-QTof/180621_Eva_02.xls
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diff --git a/cmml/18-0008_Eva_Maleckova/LC-QTof/180628_QuantReport_ISTD_ResultsSummary_B_06_00.xlsx b/cmml/18-0008_Eva_Maleckova/LC-QTof/180628_QuantReport_ISTD_ResultsSummary_B_06_00.xlsx
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diff --git a/cmml/18-0008_Eva_Maleckova/UHPLC-DAD/.Rhistory b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD/.Rhistory
new file mode 100755
index 0000000000000000000000000000000000000000..870d1c284a05fbad44fca0f4417f486f3eee4b3a
--- /dev/null
+++ b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD/.Rhistory
@@ -0,0 +1,151 @@
+setwd("/Volumes/data/MSlab/05_projects/18-0008_Eva_Maleckova/UHPLC-DAD/")
+rm(list = ls())
+library(readxl)
+lc.report <- "180612-EvaReport.xlsx"
+report.summmary <- list()
+for(i in excel_sheets(lc.report))
+{
+current.sheet <- as.data.frame(read_xlsx(lc.report, sheet = i, col_names = F))
+if(!current.sheet[1, 2] %in% c("Blank", "blank"))
+{
+info.table <- c()
+for(row in 1:(which(current.sheet[, 1] == 'Name')-1) )
+{
+x <- current.sheet[row, 1:5]
+y <- x[!is.na(x)]
+if(length(y) == 2){info.table <- c(info.table, y)}
+if(length(y) == 1){info.table <- c(info.table, c(y, 'NA'))}
+x <- current.sheet[row, 6:ncol(current.sheet)]
+y <- x[!is.na(x)]
+if(length(y) == 2){info.table <- c(info.table, y)}
+if(length(y) == 1){info.table <- c(info.table, c(y, 'NA'))}
+}
+info <- t(data.frame('a' = info.table[seq(1, length(info.table), 2)], 'b' = info.table[seq(2, length(info.table), 2)]))
+type <- info['b', 8]
+sample.data <- current.sheet[which(current.sheet[, 1] == 'Name'):(nrow(current.sheet)-1), ]
+colnames(sample.data) <- sample.data[1,]
+sample.data <- sample.data[-1, !is.na(colnames(sample.data))]
+sample.data <- sample.data[, apply(sample.data, 2, function(x){sum(is.na(x)) != nrow(sample.data)})]
+colnames(sample.data)[c(1, 5, 6)] <- c("Compound", "Amount_pmol", "Concentration_pmol.µl")
+sample.data[,2:6] <- apply(sample.data[,2:6], 2, function(x){as.numeric(x)})
+duplicated.info <- data.frame(matrix(NA, ncol = ncol(info)))
+colnames(duplicated.info) <- gsub(":", "", info[1,])
+for(j in 1:nrow(sample.data))
+{
+duplicated.info <- rbind(duplicated.info, info[2,])
+}
+duplicated.info <- duplicated.info[-1,]
+all.data <- cbind.data.frame(duplicated.info, sample.data)
+colnames(all.data) <- gsub(" ", ".", colnames(all.data))
+report.summmary[[type]][[i]] <- all.data
+}
+}
+excel_sheets(lc.report)
+View(all.data)
+report.summmary <- list()
+for(i in excel_sheets(lc.report))
+{
+print(i)
+current.sheet <- as.data.frame(read_xlsx(lc.report, sheet = i, col_names = F))
+if(!current.sheet[1, 2] %in% c("Blank", "blank"))
+{
+info.table <- c()
+for(row in 1:(which(current.sheet[, 1] == 'Name')-1) )
+{
+x <- current.sheet[row, 1:5]
+y <- x[!is.na(x)]
+if(length(y) == 2){info.table <- c(info.table, y)}
+if(length(y) == 1){info.table <- c(info.table, c(y, 'NA'))}
+x <- current.sheet[row, 6:ncol(current.sheet)]
+y <- x[!is.na(x)]
+if(length(y) == 2){info.table <- c(info.table, y)}
+if(length(y) == 1){info.table <- c(info.table, c(y, 'NA'))}
+}
+info <- t(data.frame('a' = info.table[seq(1, length(info.table), 2)], 'b' = info.table[seq(2, length(info.table), 2)]))
+type <- info['b', 8]
+sample.data <- current.sheet[which(current.sheet[, 1] == 'Name'):(nrow(current.sheet)-1), ]
+colnames(sample.data) <- sample.data[1,]
+sample.data <- sample.data[-1, !is.na(colnames(sample.data))]
+sample.data <- sample.data[, apply(sample.data, 2, function(x){sum(is.na(x)) != nrow(sample.data)})]
+colnames(sample.data)[c(1, 5, 6)] <- c("Compound", "Amount_pmol", "Concentration_pmol.µl")
+sample.data[,2:6] <- apply(sample.data[,2:6], 2, function(x){as.numeric(x)})
+duplicated.info <- data.frame(matrix(NA, ncol = ncol(info)))
+colnames(duplicated.info) <- gsub(":", "", info[1,])
+for(j in 1:nrow(sample.data))
+{
+duplicated.info <- rbind(duplicated.info, info[2,])
+}
+duplicated.info <- duplicated.info[-1,]
+all.data <- cbind.data.frame(duplicated.info, sample.data)
+colnames(all.data) <- gsub(" ", ".", colnames(all.data))
+report.summmary[[type]][[i]] <- all.data
+}
+}
+current.sheet <- as.data.frame(read_xlsx(lc.report, sheet = i, col_names = F))
+View(current.sheet)
+!current.sheet[1, 2] %in% c("Blank", "blank")
+current.sheet[1, 2]
+which(current.sheet[, 1] == 'Name')
+current.sheet[, 1] == 'Name'
+length(which(current.sheet[, 1] == 'Name'))
+length(which(current.sheet[, 1] == 'Name')) != 0
+report.summmary <- list()
+for(i in excel_sheets(lc.report))
+{
+print(i)
+current.sheet <- as.data.frame(read_xlsx(lc.report, sheet = i, col_names = F))
+if(!current.sheet[1, 2] %in% c("Blank", "blank") & length(which(current.sheet[, 1] == 'Name')) != 0 )
+{
+info.table <- c()
+for(row in 1:(which(current.sheet[, 1] == 'Name')-1) )
+{
+x <- current.sheet[row, 1:5]
+y <- x[!is.na(x)]
+if(length(y) == 2){info.table <- c(info.table, y)}
+if(length(y) == 1){info.table <- c(info.table, c(y, 'NA'))}
+x <- current.sheet[row, 6:ncol(current.sheet)]
+y <- x[!is.na(x)]
+if(length(y) == 2){info.table <- c(info.table, y)}
+if(length(y) == 1){info.table <- c(info.table, c(y, 'NA'))}
+}
+info <- t(data.frame('a' = info.table[seq(1, length(info.table), 2)], 'b' = info.table[seq(2, length(info.table), 2)]))
+type <- info['b', 8]
+sample.data <- current.sheet[which(current.sheet[, 1] == 'Name'):(nrow(current.sheet)-1), ]
+colnames(sample.data) <- sample.data[1,]
+sample.data <- sample.data[-1, !is.na(colnames(sample.data))]
+sample.data <- sample.data[, apply(sample.data, 2, function(x){sum(is.na(x)) != nrow(sample.data)})]
+colnames(sample.data)[c(1, 5, 6)] <- c("Compound", "Amount_pmol", "Concentration_pmol.µl")
+sample.data[,2:6] <- apply(sample.data[,2:6], 2, function(x){as.numeric(x)})
+duplicated.info <- data.frame(matrix(NA, ncol = ncol(info)))
+colnames(duplicated.info) <- gsub(":", "", info[1,])
+for(j in 1:nrow(sample.data))
+{
+duplicated.info <- rbind(duplicated.info, info[2,])
+}
+duplicated.info <- duplicated.info[-1,]
+all.data <- cbind.data.frame(duplicated.info, sample.data)
+colnames(all.data) <- gsub(" ", ".", colnames(all.data))
+report.summmary[[type]][[i]] <- all.data
+}
+}
+final.summary <- list()
+for(type in names(report.summmary))
+{
+final.summary[[type]] <- do.call(rbind, report.summmary[[type]])
+}
+View(final.summary)
+View(final.summary$Sample)
+View(final.summary$Calibration)
+current.sheet <- as.data.frame(read.xlsx(lc.report, sheet = i, colNames = F))
+library(openxlsx)
+current.sheet <- as.data.frame(read.xlsx(lc.report, sheet = i, colNames = F))
+print(i)
+i
+lc.report
+i <-  'Page 3'
+read.xlsx(lc.report, sheet = i, colNames = F)
+library(readxl)
+library(openxlsx)
+nice.date <- format(Sys.time(), "%y%m%d")
+nice.date
+write.xlsx(final.summary, file = paste(nice.date,'HPLC_DAD_AA_Data.xlsx', sep = '_'), asTable = F, colNames = T, creator = 'dominik.brilhaus@hhu.de')
diff --git a/cmml/18-0008_Eva_Maleckova/UHPLC-DAD/01UHPLC-DAD_Scram.R b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD/01UHPLC-DAD_Scram.R
new file mode 100755
index 0000000000000000000000000000000000000000..81fbfd7451f4d231a3458a06e05185bc8e9e887b
--- /dev/null
+++ b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD/01UHPLC-DAD_Scram.R
@@ -0,0 +1,89 @@
+
+
+
+setwd("/Volumes/data/MSlab/21_projects/18-0008_Eva_Maleckova/UHPLC-DAD/")
+rm(list = ls())
+
+library(readxl)    
+library(openxlsx)    
+
+nice.date <- format(Sys.time(), "%y%m%d")
+
+lc.report <- "180612-EvaReport.xlsx"
+
+
+report.summmary <- list()
+for(i in excel_sheets(lc.report))
+{
+  print(i)
+  
+  current.sheet <- as.data.frame(read_xlsx(lc.report, sheet = i, col_names = F))
+  
+  if(!current.sheet[1, 2] %in% c("Blank", "blank") & length(which(current.sheet[, 1] == 'Name')) != 0 )
+  {
+    
+    info.table <- c()
+    for(row in 1:(which(current.sheet[, 1] == 'Name')-1) )
+    {
+    
+      x <- current.sheet[row, 1:5]
+      y <- x[!is.na(x)]
+      if(length(y) == 2){info.table <- c(info.table, y)}
+      if(length(y) == 1){info.table <- c(info.table, c(y, 'NA'))}
+      
+      x <- current.sheet[row, 6:ncol(current.sheet)]
+      y <- x[!is.na(x)]
+      if(length(y) == 2){info.table <- c(info.table, y)}
+      if(length(y) == 1){info.table <- c(info.table, c(y, 'NA'))}
+      
+    }
+    
+    info <- t(data.frame('a' = info.table[seq(1, length(info.table), 2)], 'b' = info.table[seq(2, length(info.table), 2)]))
+    
+    type <- info['b', 8]
+    
+    sample.data <- current.sheet[which(current.sheet[, 1] == 'Name'):(nrow(current.sheet)-1), ]
+    colnames(sample.data) <- sample.data[1,]
+    sample.data <- sample.data[-1, !is.na(colnames(sample.data))]
+    
+    sample.data <- sample.data[, apply(sample.data, 2, function(x){sum(is.na(x)) != nrow(sample.data)})]
+    
+    colnames(sample.data)[c(1, 5, 6)] <- c("Compound", "Amount_pmol", "Concentration_pmol.µl")
+    
+    sample.data[,2:6] <- apply(sample.data[,2:6], 2, function(x){as.numeric(x)})
+    
+    duplicated.info <- data.frame(matrix(NA, ncol = ncol(info)))
+    colnames(duplicated.info) <- gsub(":", "", info[1,])
+    for(j in 1:nrow(sample.data))
+    {
+      duplicated.info <- rbind(duplicated.info, info[2,])
+    }
+    duplicated.info <- duplicated.info[-1,]
+    
+    all.data <- cbind.data.frame(duplicated.info, sample.data)
+    colnames(all.data) <- gsub(" ", ".", colnames(all.data))
+    
+    report.summmary[[type]][[i]] <- all.data
+    
+  }
+    
+}
+
+
+final.summary <- list()
+for(type in names(report.summmary))
+{
+  final.summary[[type]] <- do.call(rbind, report.summmary[[type]])
+
+  
+}
+
+
+save(final.summary, file = "01.UHPLC.RData")
+
+
+
+write.xlsx(final.summary, file = paste(nice.date,'HPLC_DAD_AA_Data.xlsx', sep = '_'), asTable = F, colNames = T, creator = 'dominik.brilhaus@hhu.de')
+
+
+
diff --git a/cmml/18-0008_Eva_Maleckova/UHPLC-DAD/180612-EvaReport.pdf b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD/180612-EvaReport.pdf
new file mode 100755
index 0000000000000000000000000000000000000000..3754d304540837f1ab0e53390d10e1ca13be60f8
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diff --git a/cmml/18-0008_Eva_Maleckova/UHPLC-DAD/180612-EvaReport.xlsx b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD/180612-EvaReport.xlsx
new file mode 100755
index 0000000000000000000000000000000000000000..1a001e0530aaec719c20a55c5c26c29cbb4652d9
Binary files /dev/null and b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD/180612-EvaReport.xlsx differ
diff --git a/cmml/18-0008_Eva_Maleckova/UHPLC-DAD/180612_HPLC_DAD_AA_Data.xlsx b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD/180612_HPLC_DAD_AA_Data.xlsx
new file mode 100755
index 0000000000000000000000000000000000000000..792eb613360bebdf63ac50d8d6f8853928512e98
Binary files /dev/null and b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD/180612_HPLC_DAD_AA_Data.xlsx differ
diff --git a/cmml/18-0008_Eva_Maleckova/UHPLC-DAD/Maleckova-AminoAcidsProjectSheet-2018_05_11-complete.xlsx b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD/Maleckova-AminoAcidsProjectSheet-2018_05_11-complete.xlsx
new file mode 100755
index 0000000000000000000000000000000000000000..084f94f67dbe7046820cfee81724fc7aaf215740
Binary files /dev/null and b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD/Maleckova-AminoAcidsProjectSheet-2018_05_11-complete.xlsx differ
diff --git a/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/.DS_Store b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/.DS_Store
new file mode 100755
index 0000000000000000000000000000000000000000..f00bc04480797b44d5eefd69bcd942f3057be2ea
Binary files /dev/null and b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/.DS_Store differ
diff --git a/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/.Rhistory b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/.Rhistory
new file mode 100755
index 0000000000000000000000000000000000000000..59a2aba1c0d772311563dffc08a88d2172eed0c3
--- /dev/null
+++ b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/.Rhistory
@@ -0,0 +1,512 @@
+calib$Amount <- as.numeric(calib$Amount)
+p1 <- ggplot(calib, aes(x = std.amount, y = Amount)) +
+geom_point() +
+facet_wrap(~Compound) +
+theme_classic()
+sample.data <- merge(final.summary$Sample, sample.list, by.x = "Sample.name", by.y = "Sample.label.on.tube")
+condi.colnames <- c("Condition.1", "Condition.2")
+### Create a group variable based on sample list (e.g. different species, conditions, treatments, etc.)
+if(length(condi.colnames) > 1)
+{sample.data$GroupVar <- apply(sample.data[,condi.colnames], 1, function(x){paste(x, collapse = "\n")})
+}else{
+sample.data$GroupVar <- sample.data[,condi.colnames]
+}
+sample.data$GroupVar <- factor(sample.data$GroupVar, levels = unique(sample.data[order(sample.data[,condi.colnames[1]]),  "GroupVar"]))
+p2 <- ggplot(sample.data, aes(x = GroupVar, y = Amount)) +
+geom_point() +
+facet_wrap(~Compound) +
+theme_classic()
+pdf("Test.pdf",width = 12, height = 12)
+p2
+dev.off()
+sample.data$Amount <- as.numeric(sample.data$Amount)
+p2 <- ggplot(sample.data, aes(x = GroupVar, y = Amount)) +
+geom_point() +
+facet_wrap(~Compound) +
+theme_classic()
+pdf("Test.pdf",width = 12, height = 12)
+p2
+dev.off()
+p2 <- ggplot(sample.data, aes(x = GroupVar, y = Amount)) +
+geom_point() +
+facet_wrap(~Compound, scales = "free") +
+theme_classic()
+pdf("Test.pdf",width = 12, height = 12)
+p2
+dev.off()
+p2 <- ggplot(sample.data, aes(x = GroupVar, y = Amount)) +
+geom_point() +
+facet_wrap(~Compound, scales = "free") +
+theme_dominik
+pdf("Test.pdf",width = 12, height = 12)
+p2
+dev.off()
+sample.data$pmol.mg.FW <- sample.data$Amount / sample.data$Sample.weight..mg.
+sample.data$pmol.mg.FW
+sample.data$pmol.g.FW <- sample.data$Amount / sample.data$Sample.weight..mg. * 1000
+sample.data$pmol.g.FW
+sample.data$pmol.mg.FW <- sample.data$Amount / sample.data$Sample.weight..mg.
+sample.data$µmol.g.FW <- sample.data$Amount / sample.data$Sample.weight..mg.
+sample.data$µmol.g.FW
+sample.data$µmol.mg.FW <- sample.data$Amount / sample.data$Sample.weight..mg. * 1000
+sample.data$µmol.mg.FW
+p2 <- ggplot(sample.data, aes(x = GroupVar, y = µmol.mg.FW)) +
+geom_point() +
+facet_wrap(~Compound, scales = "free") +
+theme_dominik
+pdf("Test.pdf",width = 12, height = 12)
+p2
+dev.off()
+pdf("EvaAA.pdf",width = 12, height = 12)
+p2
+dev.off()
+setwd("/Volumes/data/MSlab/05_projects/18-0008_Eva_Maleckova/UHPLC-DAD/")
+rm(list = ls())
+library(XLConnect)
+lc.report <- loadWorkbook("2018-03-14_EvaReport.xlsx")
+report.summmary <- list()
+for(i in getSheets(lc.report))
+{
+current.sheet <- readWorksheet(lc.report, i, header = F)
+info1 <- current.sheet[1:6, c(2, 5)]
+info2 <- current.sheet[3:5, c(9, 11)]
+info3 <- current.sheet[13, c(1, 3)]
+colnames(info1) <- colnames(info2) <- colnames(info3) <- c("a", "b")
+info <- t(rbind(info1, info2, info3))
+type <- info2$b[3]
+sample.data <- current.sheet[14:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]
+if(type == "Calibration"){sample.data <- current.sheet[13:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]}
+colnames(sample.data) <- sample.data[1,]
+sample.data <- sample.data[-1,]
+colnames(sample.data)[c(1, 5:6)] <- c("Compound", "Amount", "Concentration")
+duplicated.info <- data.frame(matrix(NA, ncol = ncol(info)))
+colnames(duplicated.info) <- gsub(":", "", info[1,])
+for(j in 1:nrow(sample.data))
+{
+duplicated.info <- rbind(duplicated.info, info[2,])
+}
+duplicated.info <- duplicated.info[-1,]
+all.data <- cbind.data.frame(duplicated.info, sample.data)
+colnames(all.data) <- gsub(" ", ".", colnames(all.data))
+report.summmary[[type]][[i]] <- all.data
+}
+sample.data
+type
+i
+i <- "Page 2"
+getSheets(lc.report)
+current.sheet <- readWorksheet(lc.report, i, header = F)
+info1 <- current.sheet[1:6, c(2, 5)]
+info2 <- current.sheet[3:5, c(9, 11)]
+info3 <- current.sheet[13, c(1, 3)]
+colnames(info1) <- colnames(info2) <- colnames(info3) <- c("a", "b")
+info <- t(rbind(info1, info2, info3))
+type <- info2$b[3]
+type
+i <- "Page 14"
+current.sheet <- readWorksheet(lc.report, i, header = F)
+info1 <- current.sheet[1:6, c(2, 5)]
+info2 <- current.sheet[3:5, c(9, 11)]
+info3 <- current.sheet[13, c(1, 3)]
+colnames(info1) <- colnames(info2) <- colnames(info3) <- c("a", "b")
+info <- t(rbind(info1, info2, info3))
+type <- info2$b[3]
+sample.data <- current.sheet[14:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]
+if(type == "Calibration"){sample.data <- current.sheet[13:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]}
+colnames(sample.data) <- sample.data[1,]
+sample.data <- sample.data[-1,]
+colnames(sample.data)[c(1, 5:6)] <- c("Compound", "Amount", "Concentration")
+sample.data
+sample.data[,2:6]
+as.matrix(sample.data[,2:6])
+as.numeric(sample.data[,2:6])
+apply(sample.data[,2:6], 2, function(x){as.numeric(x)})
+sample.data[,2:6] <- apply(sample.data[,2:6], 2, function(x){as.numeric(x)})
+sample.data[,2:6]
+sample.data$Concentration
+lc.report <- loadWorkbook("2018-03-14_EvaReport.xlsx")
+report.summmary <- list()
+for(i in getSheets(lc.report))
+{
+current.sheet <- readWorksheet(lc.report, i, header = F)
+info1 <- current.sheet[1:6, c(2, 5)]
+info2 <- current.sheet[3:5, c(9, 11)]
+info3 <- current.sheet[13, c(1, 3)]
+colnames(info1) <- colnames(info2) <- colnames(info3) <- c("a", "b")
+info <- t(rbind(info1, info2, info3))
+type <- info2$b[3]
+sample.data <- current.sheet[14:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]
+if(type == "Calibration"){sample.data <- current.sheet[13:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]}
+colnames(sample.data) <- sample.data[1,]
+sample.data <- sample.data[-1,]
+colnames(sample.data)[c(1, 5:6)] <- c("Compound", "Amount", "Concentration")
+sample.data[,2:6] <- apply(sample.data[,2:6], 2, function(x){as.numeric(x)})
+duplicated.info <- data.frame(matrix(NA, ncol = ncol(info)))
+colnames(duplicated.info) <- gsub(":", "", info[1,])
+for(j in 1:nrow(sample.data))
+{
+duplicated.info <- rbind(duplicated.info, info[2,])
+}
+duplicated.info <- duplicated.info[-1,]
+all.data <- cbind.data.frame(duplicated.info, sample.data)
+colnames(all.data) <- gsub(" ", ".", colnames(all.data))
+report.summmary[[type]][[i]] <- all.data
+}
+current.sheet <- readWorksheet(lc.report, i, header = F)
+info1 <- current.sheet[1:6, c(2, 5)]
+info2 <- current.sheet[3:5, c(9, 11)]
+info3 <- current.sheet[13, c(1, 3)]
+info2 <- current.sheet[3:5, c(9, 11)]
+current.sheet
+report.summmary <- list()
+for(i in getSheets(lc.report))
+{
+current.sheet <- readWorksheet(lc.report, i, header = F)
+info1 <- current.sheet[1:6, c(2, 5)]
+info2 <- current.sheet[3:5, c(9, 11)]
+info3 <- current.sheet[13, c(1, 3)]
+colnames(info1) <- colnames(info2) <- colnames(info3) <- c("a", "b")
+info <- t(rbind(info1, info2, info3))
+type <- info2$b[3]
+sample.data <- current.sheet[14:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]
+if(type == "Calibration"){sample.data <- current.sheet[13:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]}
+colnames(sample.data) <- sample.data[1,]
+sample.data <- sample.data[-1,]
+colnames(sample.data)[c(1, 5:6)] <- c("Compound", "Amount", "Concentration")
+sample.data[,2:6] <- apply(sample.data[,2:6], 2, function(x){as.numeric(x)})
+duplicated.info <- data.frame(matrix(NA, ncol = ncol(info)))
+colnames(duplicated.info) <- gsub(":", "", info[1,])
+for(j in 1:nrow(sample.data))
+{
+duplicated.info <- rbind(duplicated.info, info[2,])
+}
+duplicated.info <- duplicated.info[-1,]
+all.data <- cbind.data.frame(duplicated.info, sample.data)
+colnames(all.data) <- gsub(" ", ".", colnames(all.data))
+report.summmary[[type]][[i]] <- all.data
+}
+final.summary <- list()
+for(type in names(report.summmary))
+{
+final.summary[[type]] <- do.call(rbind, report.summmary[[type]])
+}
+############################
+#### Export data
+xlcFreeMemory()
+Data.xlsx <- loadWorkbook(paste(Sys.Date(), "01.Data.xlsx", sep = "_"), create = TRUE)
+createSheet(Data.xlsx, "SampleData")
+writeWorksheet(Data.xlsx, final.summary$Sample, "SampleData")
+saveWorkbook(Data.xlsx)
+createSheet(Data.xlsx, "Calibration")
+writeWorksheet(Data.xlsx, final.summary$Calibration, "Calibration")
+saveWorkbook(Data.xlsx)
+createSheet(Data.xlsx, "Blank")
+writeWorksheet(Data.xlsx, final.summary$Blank, "Blank")
+saveWorkbook(Data.xlsx)
+save(final.summary, file = "01.UHPLC.RData")
+setwd("/Volumes/data/MSlab/05_projects/18-0008_Eva_Maleckova/UHPLC-DAD/")
+rm(list = ls())
+required.packages <- c("Rmisc", "plyr", "ggplot2", "XLConnect","reshape2", "gridExtra")
+for(package in required.packages)
+{
+print(package)
+## Check if package is installed. If not, install
+if(!package %in% row.names(installed.packages())){install.packages(package, repos ="https://cran.uni-muenster.de/")}
+# ## Check if package is up to date. If not, update
+# update.packages(package, repos = "https://cran.uni-muenster.de/")
+## Load package
+library(package, character.only = T)
+}
+theme_dominik <-
+theme(panel.grid = element_blank(), panel.background = element_blank(), panel.border = element_rect(fill = NA)) +
+theme(axis.text = element_text(color = "black"), axis.ticks = element_line(color = "black"), axis.title = element_text(color = "black")) +
+theme(plot.title = element_text(face= "bold")) +
+theme(aspect.ratio = 1) +
+theme(strip.background = element_blank(), strip.text = element_text(size = 10, face = "bold")) +
+theme(legend.position = "bottom", legend.direction = "horizontal", legend.title = element_blank())
+load("01.UHPLC.RData")
+calib <- final.summary$Calibration
+calib$std.amount <- as.numeric(do.call(rbind, strsplit(calib$Sample.name, split = " "))[,1])
+p1 <- ggplot(calib, aes(x = std.amount, y = Amount)) +
+geom_point() +
+facet_wrap(~Compound) +
+theme_classic()
+sample.list <- readWorksheetFromFile("AAs-HPLC-test-2018_02_21.xlsx", "Sample info")
+sample.data <- merge(final.summary$Sample, sample.list, by.x = "Sample.name", by.y = "Sample.label.on.tube")
+pdf("02.1CalibrationCurves.pdf",width = 12, height = 12)
+p2
+dev.off()
+p1 <- ggplot(calib, aes(x = std.amount, y = Amount)) +
+geom_point() +
+facet_wrap(~Compound) +
+theme_classic()
+pdf("02.1CalibrationCurves.pdf",width = 12, height = 12)
+p1
+dev.off()
+p1 <- ggplot(calib, aes(x = std.amount, y = Amount)) +
+geom_point() +
+facet_wrap(~Compound) +
+theme_dominik
+pdf("02.1CalibrationCurves.pdf",width = 12, height = 12)
+p1
+dev.off()
+theme_dominik <-
+theme(panel.background = element_blank(), panel.border = element_rect(fill = NA)) +
+theme(axis.text = element_text(color = "black"), axis.ticks = element_line(color = "black"), axis.title = element_text(color = "black")) +
+theme(plot.title = element_text(face= "bold")) +
+theme(aspect.ratio = 1) +
+theme(strip.background = element_blank(), strip.text = element_text(size = 10, face = "bold")) +
+theme(legend.position = "bottom", legend.direction = "horizontal", legend.title = element_blank())
+p1 <- ggplot(calib, aes(x = std.amount, y = Amount)) +
+geom_point() +
+facet_wrap(~Compound) +
+theme_dominik
+pdf("02.1CalibrationCurves.pdf",width = 12, height = 12)
+p1
+dev.off()
+theme_dominik <-
+theme(panel.background = element_blank(), panel.border = element_rect(fill = NA)) +
+theme(axis.text = element_text(color = "black"), axis.ticks = element_line(color = "black"), axis.title = element_text(color = "black")) +
+theme(plot.title = element_text(face= "bold")) +
+theme(aspect.ratio = 1) +
+theme(strip.background = element_blank(), strip.text = element_text(size = 10, face = "bold")) +
+theme(legend.position = "bottom", legend.direction = "horizontal", legend.title = element_blank())
+p1 <- ggplot(calib, aes(x = std.amount, y = Amount)) +
+geom_point() +
+facet_wrap(~Compound) +
+theme_dominik
+pdf("02.1CalibrationCurves.pdf",width = 12, height = 12)
+p1
+dev.off()
+p1 <- ggplot(calib, aes(x = std.amount, y = Amount)) +
+geom_point() +
+facet_wrap(~Compound) +
+theme_dominik + theme(panel.grid.major = element_line(colour = "grey"))
+pdf("02.1CalibrationCurves.pdf",width = 12, height = 12)
+p1
+dev.off()
+ggplotRegression <- function (fit) {
+ggplot(fit$model, aes_string(x = names(fit$model)[2], y = names(fit$model)[1])) +
+stat_smooth(method = "lm", col = "firebrick") +
+geom_point() +
+annotate("text", x= 0, y = 0.5, hjust = 0, vjust = 1, label = paste("Adj R2 = ",signif(summary(fit)$adj.r.squared, 2),
+"\nIntercept =",signif(fit$coef[[1]],2 ),
+"\nSlope =",signif(fit$coef[[2]], 2),
+"\nP =",signif(summary(fit)$coef[2,4], 2)), size = 2) +
+theme_dominik
+}
+calib
+ggplotRegression(subset(calib, Compound == "Serine"))
+subset(calib, Compound == "Serine")
+lm(std.amount ~ Amount, data = subset(calib, Compound == "Serine"))
+ggplotRegression(lm(std.amount ~ Amount, data = subset(calib, Compound == "Serine")))
+ggplotRegression <- function (fit) {
+ggplot(fit$model, aes_string(x = names(fit$model)[2], y = names(fit$model)[1])) +
+stat_smooth(method = "lm", col = "firebrick") +
+geom_point() +
+ggtitle(label = paste("Adj R2 = ",signif(summary(fit)$adj.r.squared, 4),
+"Intercept =",signif(fit$coef[[1]],2 ),
+"Slope =",signif(fit$coef[[2]], 2),
+"P =",signif(summary(fit)$coef[2,4], 2), sep = "\n")) +
+theme_dominik
+}
+ggplotRegression(lm(std.amount ~ Amount, data = subset(calib, Compound == "Serine")))
+ggplot(fit$model, aes_string(x = names(fit$model)[2], y = names(fit$model)[1])) +
+stat_smooth(method = "lm", col = "firebrick") +
+geom_point() +
+ggtitle(label = paste("Adj R2 = ",signif(summary(fit)$adj.r.squared, 4),
+"\nIntercept =",signif(fit$coef[[1]],2 ),
+"\nSlope =",signif(fit$coef[[2]], 2),
+"\nP =",signif(summary(fit)$coef[2,4], 2))) +
+theme_dominik
+ggplotRegression <- function (fit) {
+ggplot(fit$model, aes_string(x = names(fit$model)[2], y = names(fit$model)[1])) +
+stat_smooth(method = "lm", col = "firebrick") +
+geom_point() +
+ggtitle(label = paste("Adj R2 = ",signif(summary(fit)$adj.r.squared, 4),
+"\nIntercept =",signif(fit$coef[[1]],2 ),
+"\nSlope =",signif(fit$coef[[2]], 2),
+"\nP =",signif(summary(fit)$coef[2,4], 2))) +
+theme_dominik
+}
+ggplotRegression(lm(std.amount ~ Amount, data = subset(calib, Compound == "Serine")))
+}
+}
+ggplotRegression <- function (fit) {
+ggplot(fit$model, aes_string(x = names(fit$model)[2], y = names(fit$model)[1])) +
+stat_smooth(method = "lm", col = "firebrick") +
+geom_point() +
+ggtitle(label = paste("Adj R2 = ",signif(summary(fit)$adj.r.squared, 4),
+# "\nIntercept =",signif(fit$coef[[1]],2 ),
+"\nSlope =",signif(fit$coef[[2]], 2))
+# "\nP =",signif(summary(fit)$coef[2,4], 2))
+) +
+theme_dominik
+}
+ggplotRegression(lm(std.amount ~ Amount, data = subset(calib, Compound == "Serine")))
+ggplotRegression <- function (fit) {
+ggplot(fit$model, aes_string(x = names(fit$model)[2], y = names(fit$model)[1])) +
+stat_smooth(method = "lm", col = "firebrick") +
+geom_point(size = 2) +
+ggtitle(label = paste("Adj R2 = ",signif(summary(fit)$adj.r.squared, 4),
+# "\nIntercept =",signif(fit$coef[[1]],2 ),
+"\nSlope =",signif(fit$coef[[2]], 2))
+# "\nP =",signif(summary(fit)$coef[2,4], 2))
+) +
+theme_dominik
+}
+ggplotRegression(lm(std.amount ~ Amount, data = subset(calib, Compound == "Serine")))
+lm(std.amount ~ Amount, data = subset(calib, Compound == "Serine"))
+fit <- lm(std.amount ~ Amount, data = subset(calib, Compound == "Serine"))
+fit
+fit$model
+max(fit$model[,1])
+ggplotRegression <- function (fit) {
+ggplot(fit$model, aes_string(x = names(fit$model)[2], y = names(fit$model)[1])) +
+stat_smooth(method = "lm", col = "firebrick") +
+geom_point(size = 2) +
+annotate("text", x = min(fit$model[,2]), y = max(fit$model[,1]), label = paste("Adj R2 = ",signif(summary(fit)$adj.r.squared, 4),
+# "\nIntercept =",signif(fit$coef[[1]],2 ),
+"\nSlope =",signif(fit$coef[[2]], 2))
+# "\nP =",signif(summary(fit)$coef[2,4], 2))
+) +
+theme_dominik
+}
+ggplotRegression(lm(std.amount ~ Amount, data = subset(calib, Compound == "Serine")))
+ggplot(fit$model, aes_string(x = names(fit$model)[2], y = names(fit$model)[1])) +
+stat_smooth(method = "lm", col = "firebrick") +
+geom_point(size = 2) +
+annotate("text", x = min(fit$model[,2]), y = max(fit$model[,1]), hjust = 0, label = paste("Adj R2 = ",signif(summary(fit)$adj.r.squared, 4),
+# "\nIntercept =",signif(fit$coef[[1]],2 ),
+"\nSlope =",signif(fit$coef[[2]], 2))
+# "\nP =",signif(summary(fit)$coef[2,4], 2))
+) +
+theme_dominik
+ggplot(fit$model, aes_string(x = names(fit$model)[2], y = names(fit$model)[1])) +
+stat_smooth(method = "lm", col = "firebrick") +
+geom_point(size = 2) +
+annotate("text", x = min(fit$model[,2]), y = max(fit$model[,1]), hjust = 0, label = paste("Adj R2 = ",signif(summary(fit)$adj.r.squared, 4),
+"\nIntercept =",signif(fit$coef[[1]],2 ),
+"\nSlope =",signif(fit$coef[[2]], 2))
+"\nP =",signif(summary(fit)$coef[2,4], 2))
+ggplot(fit$model, aes_string(x = names(fit$model)[2], y = names(fit$model)[1])) +
+stat_smooth(method = "lm", col = "firebrick") +
+geom_point(size = 2) +
+annotate("text", x = min(fit$model[,2]), y = max(fit$model[,1]), hjust = 0, label = paste("Adj R2 = ",signif(summary(fit)$adj.r.squared, 4),
+"\nIntercept =",signif(fit$coef[[1]],2 ),
+"\nSlope =",signif(fit$coef[[2]], 2),
+"\nP =",signif(summary(fit)$coef[2,4], 2))
+) +
+theme_dominik
+ggplot(fit$model, aes_string(x = names(fit$model)[2], y = names(fit$model)[1])) +
+stat_smooth(method = "lm", col = "firebrick") +
+geom_point(size = 2) +
+annotate("text", x = min(fit$model[,2]), y = max(fit$model[,1]), hjust = 0,  vjust = 0, label = paste("Adj R2 = ",signif(summary(fit)$adj.r.squared, 4),
+"\nIntercept =",signif(fit$coef[[1]],2 ),
+"\nSlope =",signif(fit$coef[[2]], 2),
+"\nP =",signif(summary(fit)$coef[2,4], 2))
+) +
+theme_dominik
+ggplot(fit$model, aes_string(x = names(fit$model)[2], y = names(fit$model)[1])) +
+stat_smooth(method = "lm", col = "firebrick") +
+geom_point(size = 2) +
+annotate("text", x = min(fit$model[,2]), y = max(fit$model[,1]), hjust = 0,  vjust = 1, label = paste("Adj R2 = ",signif(summary(fit)$adj.r.squared, 4),
+"\nIntercept =",signif(fit$coef[[1]],2 ),
+"\nSlope =",signif(fit$coef[[2]], 2),
+"\nP =",signif(summary(fit)$coef[2,4], 2))
+) +
+theme_dominik
+ggplotRegression <- function (fit) {
+ggplot(fit$model, aes_string(x = names(fit$model)[2], y = names(fit$model)[1])) +
+stat_smooth(method = "lm", col = "firebrick") +
+geom_point(size = 2) +
+annotate("text", x = min(fit$model[,2]), y = max(fit$model[,1]), hjust = 0,  vjust = 1, label = paste("Adj R2 = ",signif(summary(fit)$adj.r.squared, 4),
+"\nIntercept =",signif(fit$coef[[1]],2 ),
+"\nSlope =",signif(fit$coef[[2]], 2),
+"\nP =",signif(summary(fit)$coef[2,4], 2))
+) +
+theme_dominik
+}
+calib.list <- list()
+calib.list <- list()
+for(cc in unique(calib$Compound))
+{
+calib.list[[cc]] <- ggplotRegression(lm(std.amount ~ Amount, data = subset(calib, Compound == cc)))
+}
+cc
+calib.list
+calib$Amount
+count(calib$Compound)
+View(calib)
+calib <- subset(calib, !is.na(Amount))
+count(calib$Compound)
+calib.list <- list()
+for(cc in unique(calib$Compound))
+{
+calib.list[[cc]] <- ggplotRegression(lm(std.amount ~ Amount, data = subset(calib, Compound == cc)))
+}
+cc
+View(calib)
+calib <- subset(calib, Sample.name == "200 pmol Mix")
+count(calib$Compound)
+calib <- final.summary$Calibration
+calib$std.amount <- as.numeric(do.call(rbind, strsplit(calib$Sample.name, split = " "))[,1])
+calib <- subset(calib, !is.na(Amount))
+calib <- subset(calib, Sample.name != "200 pmol Mix")
+count(calib$Compound)
+View(calib)
+calib.list <- list()
+for(cc in unique(calib$Compound))
+{
+calib.list[[cc]] <- ggplotRegression(lm(std.amount ~ Amount, data = subset(calib, Compound == cc)))
+}
+calib <- subset(calib, Compound == "Histidine")
+count(calib$Compound)
+calib <- final.summary$Calibration
+calib$std.amount <- as.numeric(do.call(rbind, strsplit(calib$Sample.name, split = " "))[,1])
+calib <- subset(calib, !is.na(Amount))
+calib <- subset(calib, Sample.name != "200 pmol Mix")
+calib <- subset(calib, Compound != "Histidine")
+count(calib$Compound)
+calib.list <- list()
+for(cc in unique(calib$Compound))
+{
+calib.list[[cc]] <- ggplotRegression(lm(std.amount ~ Amount, data = subset(calib, Compound == cc)))
+}
+p1 <- ggplot(calib, aes(x = std.amount, y = Amount)) +
+geom_point() +
+facet_wrap(~Compound) +
+theme_dominik + theme(panel.grid.major = element_line(colour = "grey"))
+pdf("02.1CalibrationCurves.pdf",width = 12, height = 12)
+do.call(grid.arrange, calib.list)
+dev.off()
+pdf("02.1CalibrationCurves.pdf",width = 20, height = 20)
+do.call(grid.arrange, calib.list)
+dev.off()
+calib.list <- list()
+for(cc in unique(calib$Compound))
+{
+calib.list[[cc]] <- ggplotRegression(lm(std.amount ~ Amount, data = subset(calib, Compound == cc)))  + ggtitle(cc)
+}
+pdf("02.1CalibrationCurves.pdf",width = 20, height = 20)
+do.call(grid.arrange, calib.list)
+dev.off()
+sample.list <- readWorksheetFromFile("AAs-HPLC-test-2018_02_21.xlsx", "Sample info")
+sample.data <- merge(final.summary$Sample, sample.list, by.x = "Sample.name", by.y = "Sample.label.on.tube")
+condi.colnames <- c("Condition.1", "Condition.2")
+### Create a group variable based on sample list (e.g. different species, conditions, treatments, etc.)
+if(length(condi.colnames) > 1)
+{sample.data$GroupVar <- apply(sample.data[,condi.colnames], 1, function(x){paste(x, collapse = "\n")})
+}else{
+sample.data$GroupVar <- sample.data[,condi.colnames]
+}
+sample.data$GroupVar <- factor(sample.data$GroupVar, levels = unique(sample.data[order(sample.data[,condi.colnames[1]]),  "GroupVar"]))
+sample.data$Amount <- as.numeric(sample.data$Amount)
+sample.data$µmol.mg.FW <- sample.data$Amount / sample.data$Sample.weight..mg. * 1000
+p2 <- ggplot(sample.data, aes(x = GroupVar, y = µmol.mg.FW)) +
+geom_point() +
+facet_wrap(~Compound, scales = "free") +
+theme_dominik
+pdf("02.2AminoAcids.pdf",width = 12, height = 12)
+p2
+dev.off()
diff --git a/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-03-15_DataAnalysis/01.UHPLC.RData b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-03-15_DataAnalysis/01.UHPLC.RData
new file mode 100755
index 0000000000000000000000000000000000000000..dd134214b114a97246796efdb29236adac9309cc
Binary files /dev/null and b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-03-15_DataAnalysis/01.UHPLC.RData differ
diff --git a/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-03-15_DataAnalysis/01UHPLC-DAD_Scram.R b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-03-15_DataAnalysis/01UHPLC-DAD_Scram.R
new file mode 100755
index 0000000000000000000000000000000000000000..3cfbdfcae9677a2750ed44d946e97be2c880add7
--- /dev/null
+++ b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-03-15_DataAnalysis/01UHPLC-DAD_Scram.R
@@ -0,0 +1,89 @@
+
+
+
+setwd("/Volumes/data/MSlab/21_projects/18-0008_Eva_Maleckova/UHPLC-DAD/")
+rm(list = ls())
+library(XLConnect)
+
+lc.report <- loadWorkbook("2018-03-14_EvaReport.xlsx")
+
+report.summmary <- list()
+for(i in getSheets(lc.report))
+{
+  
+  current.sheet <- readWorksheet(lc.report, i, header = F)
+  
+  info1 <- current.sheet[1:6, c(2, 5)]
+  info2 <- current.sheet[3:5, c(9, 11)]
+  info3 <- current.sheet[13, c(1, 3)]
+ 
+  colnames(info1) <- colnames(info2) <- colnames(info3) <- c("a", "b")
+  
+  info <- t(rbind(info1, info2, info3))   
+  
+  type <- info2$b[3]
+  
+    sample.data <- current.sheet[14:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]
+    
+    if(type == "Calibration"){sample.data <- current.sheet[13:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]}
+    
+    colnames(sample.data) <- sample.data[1,]
+    sample.data <- sample.data[-1,]
+    
+    colnames(sample.data)[c(1, 5:6)] <- c("Compound", "Amount", "Concentration")
+    
+    sample.data[,2:6] <- apply(sample.data[,2:6], 2, function(x){as.numeric(x)})
+    
+    duplicated.info <- data.frame(matrix(NA, ncol = ncol(info)))
+    colnames(duplicated.info) <- gsub(":", "", info[1,])
+    for(j in 1:nrow(sample.data))
+    {
+      duplicated.info <- rbind(duplicated.info, info[2,])
+    }
+    duplicated.info <- duplicated.info[-1,]
+    
+    
+    all.data <- cbind.data.frame(duplicated.info, sample.data)
+    colnames(all.data) <- gsub(" ", ".", colnames(all.data))
+    
+    report.summmary[[type]][[i]] <- all.data
+    
+}
+
+
+final.summary <- list()
+for(type in names(report.summmary))
+{
+  final.summary[[type]] <- do.call(rbind, report.summmary[[type]]) 
+}
+
+
+
+############################
+#### Export data
+xlcFreeMemory()
+
+
+Data.xlsx <- loadWorkbook(paste(Sys.Date(), "01.Data.xlsx", sep = "_"), create = TRUE)
+
+createSheet(Data.xlsx, "SampleData")
+writeWorksheet(Data.xlsx, final.summary$Sample, "SampleData")
+saveWorkbook(Data.xlsx)
+
+createSheet(Data.xlsx, "Calibration")
+writeWorksheet(Data.xlsx, final.summary$Calibration, "Calibration")
+saveWorkbook(Data.xlsx)
+
+createSheet(Data.xlsx, "Blank")
+writeWorksheet(Data.xlsx, final.summary$Blank, "Blank")
+saveWorkbook(Data.xlsx)
+
+
+
+
+save(final.summary, file = "01.UHPLC.RData")
+
+
+
+
+
diff --git a/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-03-15_DataAnalysis/02.1CalibrationCurves.pdf b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-03-15_DataAnalysis/02.1CalibrationCurves.pdf
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index 0000000000000000000000000000000000000000..02406110cedb5199696a8b99882266264da49c9f
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diff --git a/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-03-15_DataAnalysis/02.2AminoAcids.pdf b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-03-15_DataAnalysis/02.2AminoAcids.pdf
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diff --git a/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-03-15_DataAnalysis/02UHPLC.Analysis.R b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-03-15_DataAnalysis/02UHPLC.Analysis.R
new file mode 100755
index 0000000000000000000000000000000000000000..f2b3d0c120f9ad59af6dda543bdfba3bcf887782
--- /dev/null
+++ b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-03-15_DataAnalysis/02UHPLC.Analysis.R
@@ -0,0 +1,124 @@
+
+
+setwd("/Volumes/data/MSlab/21_projects/18-0008_Eva_Maleckova/UHPLC-DAD/")
+rm(list = ls())
+
+
+#################################################
+
+required.packages <- c("Rmisc", "plyr", "ggplot2", "XLConnect","reshape2", "gridExtra")
+
+for(package in required.packages)
+{
+  print(package)
+  ## Check if package is installed. If not, install
+  if(!package %in% row.names(installed.packages())){install.packages(package, repos ="https://cran.uni-muenster.de/")}
+  # ## Check if package is up to date. If not, update
+  # update.packages(package, repos = "https://cran.uni-muenster.de/")
+  ## Load package
+  library(package, character.only = T)
+}
+
+
+theme_dominik <- 
+  theme(panel.background = element_blank(), panel.border = element_rect(fill = NA)) + 
+  theme(axis.text = element_text(color = "black"), axis.ticks = element_line(color = "black"), axis.title = element_text(color = "black")) +
+  theme(plot.title = element_text(face= "bold")) +
+  theme(aspect.ratio = 1) +
+  theme(strip.background = element_blank(), strip.text = element_text(size = 10, face = "bold")) + 
+  theme(legend.position = "bottom", legend.direction = "horizontal", legend.title = element_blank())
+
+ggplotRegression <- function (fit) {
+  
+  ggplot(fit$model, aes_string(x = names(fit$model)[2], y = names(fit$model)[1])) +
+    stat_smooth(method = "lm", col = "firebrick") +
+    geom_point(size = 2) +
+    annotate("text", x = min(fit$model[,2]), y = max(fit$model[,1]), hjust = 0,  vjust = 1, label = paste("Adj R2 = ",signif(summary(fit)$adj.r.squared, 4),
+                                                                        "\nIntercept =",signif(fit$coef[[1]],2 ),
+                                                                        "\nSlope =",signif(fit$coef[[2]], 2),
+                                                                        "\nP =",signif(summary(fit)$coef[2,4], 2))
+            ) + 
+    theme_dominik
+}
+
+
+
+
+load("01.UHPLC.RData")
+
+
+### Calibration curves
+
+
+calib <- final.summary$Calibration
+calib$std.amount <- as.numeric(do.call(rbind, strsplit(calib$Sample.name, split = " "))[,1])
+
+calib <- subset(calib, !is.na(Amount))
+calib <- subset(calib, Sample.name != "200 pmol Mix")
+
+calib <- subset(calib, Compound != "Histidine")
+
+count(calib$Compound)
+
+calib.list <- list()
+for(cc in unique(calib$Compound))
+{
+  calib.list[[cc]] <- ggplotRegression(lm(std.amount ~ Amount, data = subset(calib, Compound == cc)))  + ggtitle(cc)
+}
+
+
+
+# p1 <- ggplot(calib, aes(x = std.amount, y = Amount)) + 
+  # geom_point() + 
+  # facet_wrap(~Compound) + 
+  # theme_dominik + theme(panel.grid.major = element_line(colour = "grey"))
+  
+
+pdf("02.1CalibrationCurves.pdf",width = 20, height = 20)
+do.call(grid.arrange, calib.list)
+dev.off()
+
+
+
+
+
+
+sample.list <- readWorksheetFromFile("AAs-HPLC-test-2018_02_21.xlsx", "Sample info")
+sample.data <- merge(final.summary$Sample, sample.list, by.x = "Sample.name", by.y = "Sample.label.on.tube")
+
+condi.colnames <- c("Condition.1", "Condition.2")
+
+
+### Create a group variable based on sample list (e.g. different species, conditions, treatments, etc.)
+if(length(condi.colnames) > 1)
+  
+{sample.data$GroupVar <- apply(sample.data[,condi.colnames], 1, function(x){paste(x, collapse = "\n")})
+}else{
+  sample.data$GroupVar <- sample.data[,condi.colnames]
+}
+
+sample.data$GroupVar <- factor(sample.data$GroupVar, levels = unique(sample.data[order(sample.data[,condi.colnames[1]]),  "GroupVar"]))
+sample.data$Amount <- as.numeric(sample.data$Amount)
+
+sample.data$µmol.mg.FW <- sample.data$Amount / sample.data$Sample.weight..mg. * 1000
+
+
+p2 <- ggplot(sample.data, aes(x = GroupVar, y = µmol.mg.FW)) + 
+  geom_point() + 
+  facet_wrap(~Compound, scales = "free") + 
+  theme_dominik
+
+
+pdf("02.2AminoAcids.pdf",width = 12, height = 12)
+p2
+dev.off()
+
+
+
+
+
+
+
+
+
+
diff --git a/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-03-15_DataAnalysis/2018-03-14_EvaReport.pdf b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-03-15_DataAnalysis/2018-03-14_EvaReport.pdf
new file mode 100755
index 0000000000000000000000000000000000000000..0df13cd00608af1f11581084d6755e0ff28aeb6f
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diff --git a/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-03-15_DataAnalysis/2018-03-14_EvaReport.xlsx b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-03-15_DataAnalysis/2018-03-14_EvaReport.xlsx
new file mode 100755
index 0000000000000000000000000000000000000000..6123fa55e07a9f64883c2f6991e6d35734c31625
Binary files /dev/null and b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-03-15_DataAnalysis/2018-03-14_EvaReport.xlsx differ
diff --git a/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-03-15_DataAnalysis/2018-03-15_01.Data.xlsx b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-03-15_DataAnalysis/2018-03-15_01.Data.xlsx
new file mode 100755
index 0000000000000000000000000000000000000000..75d1d82a136492c392e3b420952e585d38e0e700
Binary files /dev/null and b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-03-15_DataAnalysis/2018-03-15_01.Data.xlsx differ
diff --git a/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-05_DataAnalysis_UpdatedMethod/.DS_Store b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-05_DataAnalysis_UpdatedMethod/.DS_Store
new file mode 100755
index 0000000000000000000000000000000000000000..5008ddfcf53c02e82d7eee2e57c38e5672ef89f6
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diff --git a/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-05_DataAnalysis_UpdatedMethod/.Rhistory b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-05_DataAnalysis_UpdatedMethod/.Rhistory
new file mode 100755
index 0000000000000000000000000000000000000000..a587fee9b2d2ea0c43b1e6817c3ee11ce8a8deb2
--- /dev/null
+++ b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-05_DataAnalysis_UpdatedMethod/.Rhistory
@@ -0,0 +1,234 @@
+setwd("/Volumes/data/MSlab/05_projects/18-0008_Eva_Maleckova/UHPLC-DAD/2018-04-05_DataAnalysis_UpdatedMethod/")
+rm(list = ls())
+library(XLConnect)
+library(openxlsx)
+getSheets(lc.report)
+?read.xlsx
+lc.report <- read.xlsx("2018-03-14_EvaReport.xlsx")
+lc.report <- read.xlsx("2018-04-05_Report.xlsx")
+library(readxl)
+install.packages(readxl)
+install.packages('readxl')
+library(readxl)
+library(readxl)
+lc.report <- "2018-04-05_Report.xlsx"
+excel_sheets(lc.report)
+report.summmary <- list()
+for(i in excel_sheets(lc.report))
+{
+current.sheet <- as.data.frame(read_xlsx(lc.report, sheet = i, col_names = F))
+info1 <- current.sheet[1:6, c(2, 5)]
+info2 <- current.sheet[3:5, c(9, 11)]
+info3 <- current.sheet[13, c(1, 3)]
+colnames(info1) <- colnames(info2) <- colnames(info3) <- c("a", "b")
+info <- t(rbind(info1, info2, info3))
+type <- info2$b[3]
+sample.data <- current.sheet[14:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]
+if(type == "Calibration"){sample.data <- current.sheet[13:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]}
+colnames(sample.data) <- sample.data[1,]
+sample.data <- sample.data[-1,]
+colnames(sample.data)[c(1, 5:6)] <- c("Compound", "Amount", "Concentration")
+sample.data[,2:6] <- apply(sample.data[,2:6], 2, function(x){as.numeric(x)})
+duplicated.info <- data.frame(matrix(NA, ncol = ncol(info)))
+colnames(duplicated.info) <- gsub(":", "", info[1,])
+for(j in 1:nrow(sample.data))
+{
+duplicated.info <- rbind(duplicated.info, info[2,])
+}
+duplicated.info <- duplicated.info[-1,]
+all.data <- cbind.data.frame(duplicated.info, sample.data)
+colnames(all.data) <- gsub(" ", ".", colnames(all.data))
+report.summmary[[type]][[i]] <- all.data
+}
+i
+current.sheet <- as.data.frame(read_xlsx(lc.report, sheet = i, col_names = F))
+info1 <- current.sheet[1:6, c(2, 5)]
+info2 <- current.sheet[3:5, c(9, 11)]
+info3 <- current.sheet[13, c(1, 3)]
+colnames(info1) <- colnames(info2) <- colnames(info3) <- c("a", "b")
+info <- t(rbind(info1, info2, info3))
+type <- info2$b[3]
+type
+info
+current.sheet
+info1
+info2
+current.sheet
+info1
+info <- t(rbind(info1, info2, info3))
+info
+type
+if(type == "Calibration"){sample.data <- current.sheet[13:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]}
+if(type == "Calibration" & !is.na(type)){sample.data <- current.sheet[13:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]}
+colnames(sample.data) <- sample.data[1,]
+sample.data <- sample.data[-1,]
+sample.data
+sample.data <- sample.data[-1,]
+colnames(sample.data)[c(1, 5:6)] <- c("Compound", "Amount", "Concentration")
+sample.data[,2:6] <- apply(sample.data[,2:6], 2, function(x){as.numeric(x)})
+duplicated.info <- data.frame(matrix(NA, ncol = ncol(info)))
+colnames(duplicated.info) <- gsub(":", "", info[1,])
+for(j in 1:nrow(sample.data))
+{
+duplicated.info <- rbind(duplicated.info, info[2,])
+}
+duplicated.info <- duplicated.info[-1,]
+all.data <- cbind.data.frame(duplicated.info, sample.data)
+colnames(all.data) <- gsub(" ", ".", colnames(all.data))
+report.summmary[[type]][[i]] <- all.data
+report.summmary
+{
+current.sheet <- as.data.frame(read_xlsx(lc.report, sheet = i, col_names = F))
+info1 <- current.sheet[1:6, c(2, 5)]
+info2 <- current.sheet[3:5, c(9, 11)]
+info3 <- current.sheet[13, c(1, 3)]
+colnames(info1) <- colnames(info2) <- colnames(info3) <- c("a", "b")
+info <- t(rbind(info1, info2, info3))
+type <- info2$b[3]
+sample.data <- current.sheet[14:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]
+if(type == "Calibration" & !is.na(type)){sample.data <- current.sheet[13:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]}
+colnames(sample.data) <- sample.data[1,]
+sample.data <- sample.data[-1,]
+colnames(sample.data)[c(1, 5:6)] <- c("Compound", "Amount", "Concentration")
+sample.data[,2:6] <- apply(sample.data[,2:6], 2, function(x){as.numeric(x)})
+duplicated.info <- data.frame(matrix(NA, ncol = ncol(info)))
+colnames(duplicated.info) <- gsub(":", "", info[1,])
+for(j in 1:nrow(sample.data))
+{
+duplicated.info <- rbind(duplicated.info, info[2,])
+}
+duplicated.info <- duplicated.info[-1,]
+all.data <- cbind.data.frame(duplicated.info, sample.data)
+colnames(all.data) <- gsub(" ", ".", colnames(all.data))
+report.summmary[[type]][[i]] <- all.data
+}
+report.summmary <- list()
+for(i in excel_sheets(lc.report))
+{
+current.sheet <- as.data.frame(read_xlsx(lc.report, sheet = i, col_names = F))
+info1 <- current.sheet[1:6, c(2, 5)]
+info2 <- current.sheet[3:5, c(9, 11)]
+info3 <- current.sheet[13, c(1, 3)]
+colnames(info1) <- colnames(info2) <- colnames(info3) <- c("a", "b")
+info <- t(rbind(info1, info2, info3))
+type <- info2$b[3]
+sample.data <- current.sheet[14:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]
+if(type == "Calibration" & !is.na(type)){sample.data <- current.sheet[13:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]}
+colnames(sample.data) <- sample.data[1,]
+sample.data <- sample.data[-1,]
+colnames(sample.data)[c(1, 5:6)] <- c("Compound", "Amount", "Concentration")
+sample.data[,2:6] <- apply(sample.data[,2:6], 2, function(x){as.numeric(x)})
+duplicated.info <- data.frame(matrix(NA, ncol = ncol(info)))
+colnames(duplicated.info) <- gsub(":", "", info[1,])
+for(j in 1:nrow(sample.data))
+{
+duplicated.info <- rbind(duplicated.info, info[2,])
+}
+duplicated.info <- duplicated.info[-1,]
+all.data <- cbind.data.frame(duplicated.info, sample.data)
+colnames(all.data) <- gsub(" ", ".", colnames(all.data))
+report.summmary[[type]][[i]] <- all.data
+}
+report.summmary
+excel_sheets(lc.report)
+i <- "Page 2"
+current.sheet <- as.data.frame(read_xlsx(lc.report, sheet = i, col_names = F))
+info1 <- current.sheet[1:6, c(2, 5)]
+info2 <- current.sheet[3:5, c(9, 11)]
+info3 <- current.sheet[13, c(1, 3)]
+info3
+info2
+current.sheet
+View(current.sheet)
+info1 <- current.sheet[1:6, c(2, 5)]
+info2 <- current.sheet[3:5, c(10, 13)]
+View(current.sheet)
+info3 <- current.sheet[13, c(1, 3)]
+info3
+View(current.sheet)
+View(current.sheet)
+info3 <- current.sheet[12, c(1, 3)]
+colnames(info1) <- colnames(info2) <- colnames(info3) <- c("a", "b")
+info <- t(rbind(info1, info2, info3))
+info
+type <- info2$b[3]
+type
+if(type == "Calibration"){sample.data <- current.sheet[13:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]}
+sample.data
+report.summmary <- list()
+for(i in excel_sheets(lc.report))
+{
+current.sheet <- as.data.frame(read_xlsx(lc.report, sheet = i, col_names = F))
+info1 <- current.sheet[1:6, c(2, 5)]
+info2 <- current.sheet[3:5, c(10, 13)]
+info3 <- current.sheet[12, c(1, 3)]
+colnames(info1) <- colnames(info2) <- colnames(info3) <- c("a", "b")
+info <- t(rbind(info1, info2, info3))
+type <- info2$b[3]
+sample.data <- current.sheet[14:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]
+if(type == "Calibration"){sample.data <- current.sheet[13:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]}
+colnames(sample.data) <- sample.data[1,]
+sample.data <- sample.data[-1,]
+colnames(sample.data)[c(1, 5:6)] <- c("Compound", "Amount", "Concentration")
+sample.data[,2:6] <- apply(sample.data[,2:6], 2, function(x){as.numeric(x)})
+duplicated.info <- data.frame(matrix(NA, ncol = ncol(info)))
+colnames(duplicated.info) <- gsub(":", "", info[1,])
+for(j in 1:nrow(sample.data))
+{
+duplicated.info <- rbind(duplicated.info, info[2,])
+}
+duplicated.info <- duplicated.info[-1,]
+all.data <- cbind.data.frame(duplicated.info, sample.data)
+colnames(all.data) <- gsub(" ", ".", colnames(all.data))
+report.summmary[[type]][[i]] <- all.data
+}
+i
+report.summmary$Calibration
+report.summmary$Sample
+final.summary <- list()
+for(type in names(report.summmary))
+{
+final.summary[[type]] <- do.call(rbind, report.summmary[[type]])
+}
+final.summary
+save(final.summary, file = "01.UHPLC.RData")
+setwd("/Volumes/data/MSlab/05_projects/18-0008_Eva_Maleckova/UHPLC-DAD/2018-04-05_DataAnalysis_UpdatedMethod/")
+rm(list = ls())
+required.packages <- c("Rmisc", "plyr", "ggplot2", "readxl","reshape2", "gridExtra")
+for(package in required.packages)
+{
+print(package)
+## Check if package is installed. If not, install
+if(!package %in% row.names(installed.packages())){install.packages(package, repos ="https://cran.uni-muenster.de/")}
+# ## Check if package is up to date. If not, update
+# update.packages(package, repos = "https://cran.uni-muenster.de/")
+## Load package
+library(package, character.only = T)
+}
+theme_dominik <-
+theme(panel.background = element_blank(), panel.border = element_rect(fill = NA)) +
+theme(axis.text = element_text(color = "black"), axis.ticks = element_line(color = "black"), axis.title = element_text(color = "black")) +
+theme(plot.title = element_text(face= "bold")) +
+theme(aspect.ratio = 1) +
+theme(strip.background = element_blank(), strip.text = element_text(size = 10, face = "bold")) +
+theme(legend.position = "bottom", legend.direction = "horizontal", legend.title = element_blank())
+ggplotRegression <- function (fit) {
+ggplot(fit$model, aes_string(x = names(fit$model)[2], y = names(fit$model)[1])) +
+stat_smooth(method = "lm", col = "firebrick") +
+geom_point(size = 2) +
+annotate("text", x = min(fit$model[,2]), y = max(fit$model[,1]), hjust = 0,  vjust = 1, label = paste("Adj R2 = ",signif(summary(fit)$adj.r.squared, 4),
+"\nIntercept =",signif(fit$coef[[1]],2 ),
+"\nSlope =",signif(fit$coef[[2]], 2),
+"\nP =",signif(summary(fit)$coef[2,4], 2))
+) +
+theme_dominik
+}
+load("01.UHPLC.RData")
+calib <- final.summary$Calibration
+calib$std.amount <- as.numeric(do.call(rbind, strsplit(calib$Sample.name, split = " "))[,1])
+calib <- subset(calib, !is.na(Amount))
+calib <- subset(calib, Sample.name != "200 pmol Mix")
+calib <- subset(calib, Compound != "Histidine")
+count(calib$Compound)
+calib <- final.summary$Calibration
+calib
diff --git a/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-05_DataAnalysis_UpdatedMethod/01.UHPLC.RData b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-05_DataAnalysis_UpdatedMethod/01.UHPLC.RData
new file mode 100755
index 0000000000000000000000000000000000000000..525bfc0b3f456219de96bba2911331a635551414
Binary files /dev/null and b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-05_DataAnalysis_UpdatedMethod/01.UHPLC.RData differ
diff --git a/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-05_DataAnalysis_UpdatedMethod/01UHPLC-DAD_Scram.R b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-05_DataAnalysis_UpdatedMethod/01UHPLC-DAD_Scram.R
new file mode 100755
index 0000000000000000000000000000000000000000..cb7f7a52e288d9e2bae886fa05d1d5af82a48569
--- /dev/null
+++ b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-05_DataAnalysis_UpdatedMethod/01UHPLC-DAD_Scram.R
@@ -0,0 +1,91 @@
+
+
+
+setwd("/Volumes/data/MSlab/21_projects/18-0008_Eva_Maleckova/UHPLC-DAD/2018-04-05_DataAnalysis_UpdatedMethod/")
+rm(list = ls())
+
+library(readxl)    
+
+lc.report <- "2018-04-05_Report.xlsx"
+
+
+report.summmary <- list()
+for(i in excel_sheets(lc.report))
+{
+  
+  current.sheet <- as.data.frame(read_xlsx(lc.report, sheet = i, col_names = F))
+  
+  info1 <- current.sheet[1:6, c(2, 5)]
+  info2 <- current.sheet[3:5, c(10, 13)]
+  info3 <- current.sheet[12, c(1, 3)]
+ 
+  colnames(info1) <- colnames(info2) <- colnames(info3) <- c("a", "b")
+  
+  info <- t(rbind(info1, info2, info3))   
+  
+  type <- info2$b[3]
+  
+    sample.data <- current.sheet[14:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]
+    
+    if(type == "Calibration"){sample.data <- current.sheet[13:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]}
+    
+    colnames(sample.data) <- sample.data[1,]
+    sample.data <- sample.data[-1,]
+    
+    colnames(sample.data)[c(1, 5:6)] <- c("Compound", "Amount", "Concentration")
+    
+    sample.data[,2:6] <- apply(sample.data[,2:6], 2, function(x){as.numeric(x)})
+    
+    duplicated.info <- data.frame(matrix(NA, ncol = ncol(info)))
+    colnames(duplicated.info) <- gsub(":", "", info[1,])
+    for(j in 1:nrow(sample.data))
+    {
+      duplicated.info <- rbind(duplicated.info, info[2,])
+    }
+    duplicated.info <- duplicated.info[-1,]
+    
+    
+    all.data <- cbind.data.frame(duplicated.info, sample.data)
+    colnames(all.data) <- gsub(" ", ".", colnames(all.data))
+    
+    report.summmary[[type]][[i]] <- all.data
+    
+}
+
+
+final.summary <- list()
+for(type in names(report.summmary))
+{
+  final.summary[[type]] <- do.call(rbind, report.summmary[[type]]) 
+}
+
+# 
+# 
+# ############################
+# #### Export data
+# xlcFreeMemory()
+# 
+# 
+# Data.xlsx <- loadWorkbook(paste(Sys.Date(), "01.Data.xlsx", sep = "_"), create = TRUE)
+# 
+# createSheet(Data.xlsx, "SampleData")
+# writeWorksheet(Data.xlsx, final.summary$Sample, "SampleData")
+# saveWorkbook(Data.xlsx)
+# 
+# createSheet(Data.xlsx, "Calibration")
+# writeWorksheet(Data.xlsx, final.summary$Calibration, "Calibration")
+# saveWorkbook(Data.xlsx)
+# 
+# createSheet(Data.xlsx, "Blank")
+# writeWorksheet(Data.xlsx, final.summary$Blank, "Blank")
+# saveWorkbook(Data.xlsx)
+
+
+
+
+save(final.summary, file = "01.UHPLC.RData")
+
+
+
+
+
diff --git a/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-05_DataAnalysis_UpdatedMethod/02UHPLC.Analysis.R b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-05_DataAnalysis_UpdatedMethod/02UHPLC.Analysis.R
new file mode 100755
index 0000000000000000000000000000000000000000..dabc49fd4582fb7295a3d5a544634c7ef498dfd4
--- /dev/null
+++ b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-05_DataAnalysis_UpdatedMethod/02UHPLC.Analysis.R
@@ -0,0 +1,124 @@
+
+
+setwd("/Volumes/data/MSlab/21_projects/18-0008_Eva_Maleckova/UHPLC-DAD/2018-04-05_DataAnalysis_UpdatedMethod/")
+rm(list = ls())
+
+
+#################################################
+
+required.packages <- c("Rmisc", "plyr", "ggplot2", "readxl","reshape2", "gridExtra")
+
+for(package in required.packages)
+{
+  print(package)
+  ## Check if package is installed. If not, install
+  if(!package %in% row.names(installed.packages())){install.packages(package, repos ="https://cran.uni-muenster.de/")}
+  # ## Check if package is up to date. If not, update
+  # update.packages(package, repos = "https://cran.uni-muenster.de/")
+  ## Load package
+  library(package, character.only = T)
+}
+
+
+theme_dominik <- 
+  theme(panel.background = element_blank(), panel.border = element_rect(fill = NA)) + 
+  theme(axis.text = element_text(color = "black"), axis.ticks = element_line(color = "black"), axis.title = element_text(color = "black")) +
+  theme(plot.title = element_text(face= "bold")) +
+  theme(aspect.ratio = 1) +
+  theme(strip.background = element_blank(), strip.text = element_text(size = 10, face = "bold")) + 
+  theme(legend.position = "bottom", legend.direction = "horizontal", legend.title = element_blank())
+
+ggplotRegression <- function (fit) {
+  
+  ggplot(fit$model, aes_string(x = names(fit$model)[2], y = names(fit$model)[1])) +
+    stat_smooth(method = "lm", col = "firebrick") +
+    geom_point(size = 2) +
+    annotate("text", x = min(fit$model[,2]), y = max(fit$model[,1]), hjust = 0,  vjust = 1, label = paste("Adj R2 = ",signif(summary(fit)$adj.r.squared, 4),
+                                                                        "\nIntercept =",signif(fit$coef[[1]],2 ),
+                                                                        "\nSlope =",signif(fit$coef[[2]], 2),
+                                                                        "\nP =",signif(summary(fit)$coef[2,4], 2))
+            ) + 
+    theme_dominik
+}
+
+
+
+
+load("01.UHPLC.RData")
+
+
+### Calibration curves
+
+
+calib <- final.summary$Calibration
+calib$std.amount <- as.numeric(do.call(rbind, strsplit(calib$Sample.name, split = " "))[,1])
+
+calib <- subset(calib, !is.na(Amount))
+calib <- subset(calib, Sample.name != "200 pmol Mix")
+
+calib <- subset(calib, Compound != "Histidine")
+
+count(calib$Compound)
+
+calib.list <- list()
+for(cc in unique(calib$Compound))
+{
+  calib.list[[cc]] <- ggplotRegression(lm(std.amount ~ Amount, data = subset(calib, Compound == cc)))  + ggtitle(cc)
+}
+
+
+
+# p1 <- ggplot(calib, aes(x = std.amount, y = Amount)) + 
+  # geom_point() + 
+  # facet_wrap(~Compound) + 
+  # theme_dominik + theme(panel.grid.major = element_line(colour = "grey"))
+  
+
+pdf("02.1CalibrationCurves.pdf",width = 20, height = 20)
+do.call(grid.arrange, calib.list)
+dev.off()
+
+
+
+
+
+
+sample.list <- readWorksheetFromFile("AAs-HPLC-test-2018_02_21.xlsx", "Sample info")
+sample.data <- merge(final.summary$Sample, sample.list, by.x = "Sample.name", by.y = "Sample.label.on.tube")
+
+condi.colnames <- c("Condition.1", "Condition.2")
+
+
+### Create a group variable based on sample list (e.g. different species, conditions, treatments, etc.)
+if(length(condi.colnames) > 1)
+  
+{sample.data$GroupVar <- apply(sample.data[,condi.colnames], 1, function(x){paste(x, collapse = "\n")})
+}else{
+  sample.data$GroupVar <- sample.data[,condi.colnames]
+}
+
+sample.data$GroupVar <- factor(sample.data$GroupVar, levels = unique(sample.data[order(sample.data[,condi.colnames[1]]),  "GroupVar"]))
+sample.data$Amount <- as.numeric(sample.data$Amount)
+
+sample.data$µmol.mg.FW <- sample.data$Amount / sample.data$Sample.weight..mg. * 1000
+
+
+p2 <- ggplot(sample.data, aes(x = GroupVar, y = µmol.mg.FW)) + 
+  geom_point() + 
+  facet_wrap(~Compound, scales = "free") + 
+  theme_dominik
+
+
+pdf("02.2AminoAcids.pdf",width = 12, height = 12)
+p2
+dev.off()
+
+
+
+
+
+
+
+
+
+
diff --git a/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-11_DataAnalysis_UpUpdated/.Rhistory b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-11_DataAnalysis_UpUpdated/.Rhistory
new file mode 100755
index 0000000000000000000000000000000000000000..a587fee9b2d2ea0c43b1e6817c3ee11ce8a8deb2
--- /dev/null
+++ b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-11_DataAnalysis_UpUpdated/.Rhistory
@@ -0,0 +1,234 @@
+setwd("/Volumes/data/MSlab/05_projects/18-0008_Eva_Maleckova/UHPLC-DAD/2018-04-05_DataAnalysis_UpdatedMethod/")
+rm(list = ls())
+library(XLConnect)
+library(openxlsx)
+getSheets(lc.report)
+?read.xlsx
+lc.report <- read.xlsx("2018-03-14_EvaReport.xlsx")
+lc.report <- read.xlsx("2018-04-05_Report.xlsx")
+library(readxl)
+install.packages(readxl)
+install.packages('readxl')
+library(readxl)
+library(readxl)
+lc.report <- "2018-04-05_Report.xlsx"
+excel_sheets(lc.report)
+report.summmary <- list()
+for(i in excel_sheets(lc.report))
+{
+current.sheet <- as.data.frame(read_xlsx(lc.report, sheet = i, col_names = F))
+info1 <- current.sheet[1:6, c(2, 5)]
+info2 <- current.sheet[3:5, c(9, 11)]
+info3 <- current.sheet[13, c(1, 3)]
+colnames(info1) <- colnames(info2) <- colnames(info3) <- c("a", "b")
+info <- t(rbind(info1, info2, info3))
+type <- info2$b[3]
+sample.data <- current.sheet[14:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]
+if(type == "Calibration"){sample.data <- current.sheet[13:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]}
+colnames(sample.data) <- sample.data[1,]
+sample.data <- sample.data[-1,]
+colnames(sample.data)[c(1, 5:6)] <- c("Compound", "Amount", "Concentration")
+sample.data[,2:6] <- apply(sample.data[,2:6], 2, function(x){as.numeric(x)})
+duplicated.info <- data.frame(matrix(NA, ncol = ncol(info)))
+colnames(duplicated.info) <- gsub(":", "", info[1,])
+for(j in 1:nrow(sample.data))
+{
+duplicated.info <- rbind(duplicated.info, info[2,])
+}
+duplicated.info <- duplicated.info[-1,]
+all.data <- cbind.data.frame(duplicated.info, sample.data)
+colnames(all.data) <- gsub(" ", ".", colnames(all.data))
+report.summmary[[type]][[i]] <- all.data
+}
+i
+current.sheet <- as.data.frame(read_xlsx(lc.report, sheet = i, col_names = F))
+info1 <- current.sheet[1:6, c(2, 5)]
+info2 <- current.sheet[3:5, c(9, 11)]
+info3 <- current.sheet[13, c(1, 3)]
+colnames(info1) <- colnames(info2) <- colnames(info3) <- c("a", "b")
+info <- t(rbind(info1, info2, info3))
+type <- info2$b[3]
+type
+info
+current.sheet
+info1
+info2
+current.sheet
+info1
+info <- t(rbind(info1, info2, info3))
+info
+type
+if(type == "Calibration"){sample.data <- current.sheet[13:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]}
+if(type == "Calibration" & !is.na(type)){sample.data <- current.sheet[13:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]}
+colnames(sample.data) <- sample.data[1,]
+sample.data <- sample.data[-1,]
+sample.data
+sample.data <- sample.data[-1,]
+colnames(sample.data)[c(1, 5:6)] <- c("Compound", "Amount", "Concentration")
+sample.data[,2:6] <- apply(sample.data[,2:6], 2, function(x){as.numeric(x)})
+duplicated.info <- data.frame(matrix(NA, ncol = ncol(info)))
+colnames(duplicated.info) <- gsub(":", "", info[1,])
+for(j in 1:nrow(sample.data))
+{
+duplicated.info <- rbind(duplicated.info, info[2,])
+}
+duplicated.info <- duplicated.info[-1,]
+all.data <- cbind.data.frame(duplicated.info, sample.data)
+colnames(all.data) <- gsub(" ", ".", colnames(all.data))
+report.summmary[[type]][[i]] <- all.data
+report.summmary
+{
+current.sheet <- as.data.frame(read_xlsx(lc.report, sheet = i, col_names = F))
+info1 <- current.sheet[1:6, c(2, 5)]
+info2 <- current.sheet[3:5, c(9, 11)]
+info3 <- current.sheet[13, c(1, 3)]
+colnames(info1) <- colnames(info2) <- colnames(info3) <- c("a", "b")
+info <- t(rbind(info1, info2, info3))
+type <- info2$b[3]
+sample.data <- current.sheet[14:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]
+if(type == "Calibration" & !is.na(type)){sample.data <- current.sheet[13:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]}
+colnames(sample.data) <- sample.data[1,]
+sample.data <- sample.data[-1,]
+colnames(sample.data)[c(1, 5:6)] <- c("Compound", "Amount", "Concentration")
+sample.data[,2:6] <- apply(sample.data[,2:6], 2, function(x){as.numeric(x)})
+duplicated.info <- data.frame(matrix(NA, ncol = ncol(info)))
+colnames(duplicated.info) <- gsub(":", "", info[1,])
+for(j in 1:nrow(sample.data))
+{
+duplicated.info <- rbind(duplicated.info, info[2,])
+}
+duplicated.info <- duplicated.info[-1,]
+all.data <- cbind.data.frame(duplicated.info, sample.data)
+colnames(all.data) <- gsub(" ", ".", colnames(all.data))
+report.summmary[[type]][[i]] <- all.data
+}
+report.summmary <- list()
+for(i in excel_sheets(lc.report))
+{
+current.sheet <- as.data.frame(read_xlsx(lc.report, sheet = i, col_names = F))
+info1 <- current.sheet[1:6, c(2, 5)]
+info2 <- current.sheet[3:5, c(9, 11)]
+info3 <- current.sheet[13, c(1, 3)]
+colnames(info1) <- colnames(info2) <- colnames(info3) <- c("a", "b")
+info <- t(rbind(info1, info2, info3))
+type <- info2$b[3]
+sample.data <- current.sheet[14:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]
+if(type == "Calibration" & !is.na(type)){sample.data <- current.sheet[13:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]}
+colnames(sample.data) <- sample.data[1,]
+sample.data <- sample.data[-1,]
+colnames(sample.data)[c(1, 5:6)] <- c("Compound", "Amount", "Concentration")
+sample.data[,2:6] <- apply(sample.data[,2:6], 2, function(x){as.numeric(x)})
+duplicated.info <- data.frame(matrix(NA, ncol = ncol(info)))
+colnames(duplicated.info) <- gsub(":", "", info[1,])
+for(j in 1:nrow(sample.data))
+{
+duplicated.info <- rbind(duplicated.info, info[2,])
+}
+duplicated.info <- duplicated.info[-1,]
+all.data <- cbind.data.frame(duplicated.info, sample.data)
+colnames(all.data) <- gsub(" ", ".", colnames(all.data))
+report.summmary[[type]][[i]] <- all.data
+}
+report.summmary
+excel_sheets(lc.report)
+i <- "Page 2"
+current.sheet <- as.data.frame(read_xlsx(lc.report, sheet = i, col_names = F))
+info1 <- current.sheet[1:6, c(2, 5)]
+info2 <- current.sheet[3:5, c(9, 11)]
+info3 <- current.sheet[13, c(1, 3)]
+info3
+info2
+current.sheet
+View(current.sheet)
+info1 <- current.sheet[1:6, c(2, 5)]
+info2 <- current.sheet[3:5, c(10, 13)]
+View(current.sheet)
+info3 <- current.sheet[13, c(1, 3)]
+info3
+View(current.sheet)
+View(current.sheet)
+info3 <- current.sheet[12, c(1, 3)]
+colnames(info1) <- colnames(info2) <- colnames(info3) <- c("a", "b")
+info <- t(rbind(info1, info2, info3))
+info
+type <- info2$b[3]
+type
+if(type == "Calibration"){sample.data <- current.sheet[13:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]}
+sample.data
+report.summmary <- list()
+for(i in excel_sheets(lc.report))
+{
+current.sheet <- as.data.frame(read_xlsx(lc.report, sheet = i, col_names = F))
+info1 <- current.sheet[1:6, c(2, 5)]
+info2 <- current.sheet[3:5, c(10, 13)]
+info3 <- current.sheet[12, c(1, 3)]
+colnames(info1) <- colnames(info2) <- colnames(info3) <- c("a", "b")
+info <- t(rbind(info1, info2, info3))
+type <- info2$b[3]
+sample.data <- current.sheet[14:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]
+if(type == "Calibration"){sample.data <- current.sheet[13:(nrow(current.sheet)-1), c(1, 4, 6, 7, 8, 10)]}
+colnames(sample.data) <- sample.data[1,]
+sample.data <- sample.data[-1,]
+colnames(sample.data)[c(1, 5:6)] <- c("Compound", "Amount", "Concentration")
+sample.data[,2:6] <- apply(sample.data[,2:6], 2, function(x){as.numeric(x)})
+duplicated.info <- data.frame(matrix(NA, ncol = ncol(info)))
+colnames(duplicated.info) <- gsub(":", "", info[1,])
+for(j in 1:nrow(sample.data))
+{
+duplicated.info <- rbind(duplicated.info, info[2,])
+}
+duplicated.info <- duplicated.info[-1,]
+all.data <- cbind.data.frame(duplicated.info, sample.data)
+colnames(all.data) <- gsub(" ", ".", colnames(all.data))
+report.summmary[[type]][[i]] <- all.data
+}
+i
+report.summmary$Calibration
+report.summmary$Sample
+final.summary <- list()
+for(type in names(report.summmary))
+{
+final.summary[[type]] <- do.call(rbind, report.summmary[[type]])
+}
+final.summary
+save(final.summary, file = "01.UHPLC.RData")
+setwd("/Volumes/data/MSlab/05_projects/18-0008_Eva_Maleckova/UHPLC-DAD/2018-04-05_DataAnalysis_UpdatedMethod/")
+rm(list = ls())
+required.packages <- c("Rmisc", "plyr", "ggplot2", "readxl","reshape2", "gridExtra")
+for(package in required.packages)
+{
+print(package)
+## Check if package is installed. If not, install
+if(!package %in% row.names(installed.packages())){install.packages(package, repos ="https://cran.uni-muenster.de/")}
+# ## Check if package is up to date. If not, update
+# update.packages(package, repos = "https://cran.uni-muenster.de/")
+## Load package
+library(package, character.only = T)
+}
+theme_dominik <-
+theme(panel.background = element_blank(), panel.border = element_rect(fill = NA)) +
+theme(axis.text = element_text(color = "black"), axis.ticks = element_line(color = "black"), axis.title = element_text(color = "black")) +
+theme(plot.title = element_text(face= "bold")) +
+theme(aspect.ratio = 1) +
+theme(strip.background = element_blank(), strip.text = element_text(size = 10, face = "bold")) +
+theme(legend.position = "bottom", legend.direction = "horizontal", legend.title = element_blank())
+ggplotRegression <- function (fit) {
+ggplot(fit$model, aes_string(x = names(fit$model)[2], y = names(fit$model)[1])) +
+stat_smooth(method = "lm", col = "firebrick") +
+geom_point(size = 2) +
+annotate("text", x = min(fit$model[,2]), y = max(fit$model[,1]), hjust = 0,  vjust = 1, label = paste("Adj R2 = ",signif(summary(fit)$adj.r.squared, 4),
+"\nIntercept =",signif(fit$coef[[1]],2 ),
+"\nSlope =",signif(fit$coef[[2]], 2),
+"\nP =",signif(summary(fit)$coef[2,4], 2))
+) +
+theme_dominik
+}
+load("01.UHPLC.RData")
+calib <- final.summary$Calibration
+calib$std.amount <- as.numeric(do.call(rbind, strsplit(calib$Sample.name, split = " "))[,1])
+calib <- subset(calib, !is.na(Amount))
+calib <- subset(calib, Sample.name != "200 pmol Mix")
+calib <- subset(calib, Compound != "Histidine")
+count(calib$Compound)
+calib <- final.summary$Calibration
+calib
diff --git a/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-11_DataAnalysis_UpUpdated/01.UHPLC.RData b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-11_DataAnalysis_UpUpdated/01.UHPLC.RData
new file mode 100755
index 0000000000000000000000000000000000000000..a58aacbcca6a51755739db890777c5fd070e4010
Binary files /dev/null and b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-11_DataAnalysis_UpUpdated/01.UHPLC.RData differ
diff --git a/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-11_DataAnalysis_UpUpdated/01UHPLC-DAD_Scram.R b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-11_DataAnalysis_UpUpdated/01UHPLC-DAD_Scram.R
new file mode 100755
index 0000000000000000000000000000000000000000..e1d1ba2d692ea1112aabc0830991b14f286fecf1
--- /dev/null
+++ b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-11_DataAnalysis_UpUpdated/01UHPLC-DAD_Scram.R
@@ -0,0 +1,84 @@
+
+
+
+setwd("/Volumes/data/MSlab/21_projects/18-0008_Eva_Maleckova/UHPLC-DAD/2018-04-11_DataAnalysis_UpUpdated/")
+rm(list = ls())
+
+library(readxl)    
+
+lc.report <- "2018-04-10_Report.xlsx"
+
+
+report.summmary <- list()
+for(i in excel_sheets(lc.report))
+{
+  
+  current.sheet <- as.data.frame(read_xlsx(lc.report, sheet = i, col_names = F))
+  
+  if(!current.sheet[1, 2] %in% c("Blank", "blank"))
+  {
+    
+    
+    info.table <- c()
+    for(row in 1:(which(current.sheet[, 1] == 'Name')-1) )
+    {
+    
+      x <- current.sheet[row, 1:5]
+      y <- x[!is.na(x)]
+      if(length(y) == 2){info.table <- c(info.table, y)}
+      if(length(y) == 1){info.table <- c(info.table, c(y, 'NA'))}
+      
+      x <- current.sheet[row, 6:ncol(current.sheet)]
+      y <- x[!is.na(x)]
+      if(length(y) == 2){info.table <- c(info.table, y)}
+      if(length(y) == 1){info.table <- c(info.table, c(y, 'NA'))}
+      
+    }
+    
+    info <- t(data.frame('a' = info.table[seq(1, length(info.table), 2)], 'b' = info.table[seq(2, length(info.table), 2)]))
+    
+    type <- info['b', 8]
+    
+    sample.data <- current.sheet[which(current.sheet[, 1] == 'Name'):(nrow(current.sheet)-1), ]
+    colnames(sample.data) <- sample.data[1,]
+    sample.data <- sample.data[-1, !is.na(colnames(sample.data))]
+    
+    sample.data <- sample.data[, apply(sample.data, 2, function(x){sum(is.na(x)) != nrow(sample.data)})]
+    
+    colnames(sample.data)[c(1, 5, 6)] <- c("Compound", "Amount_pmol", "Concentration_pmol.µl")
+    
+    sample.data[,2:6] <- apply(sample.data[,2:6], 2, function(x){as.numeric(x)})
+    
+    duplicated.info <- data.frame(matrix(NA, ncol = ncol(info)))
+    colnames(duplicated.info) <- gsub(":", "", info[1,])
+    for(j in 1:nrow(sample.data))
+    {
+      duplicated.info <- rbind(duplicated.info, info[2,])
+    }
+    duplicated.info <- duplicated.info[-1,]
+    
+    all.data <- cbind.data.frame(duplicated.info, sample.data)
+    colnames(all.data) <- gsub(" ", ".", colnames(all.data))
+    
+    report.summmary[[type]][[i]] <- all.data
+    
+  }
+    
+}
+
+
+final.summary <- list()
+for(type in names(report.summmary))
+{
+  final.summary[[type]] <- do.call(rbind, report.summmary[[type]])
+
+  
+}
+
+
+save(final.summary, file = "01.UHPLC.RData")
+
+
+
+
+
diff --git a/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-11_DataAnalysis_UpUpdated/02UHPLC.Analysis.R b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-11_DataAnalysis_UpUpdated/02UHPLC.Analysis.R
new file mode 100755
index 0000000000000000000000000000000000000000..143f9f688c0859ee20f0c428366d4eaf7f470555
--- /dev/null
+++ b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-11_DataAnalysis_UpUpdated/02UHPLC.Analysis.R
@@ -0,0 +1,166 @@
+
+
+setwd("/Volumes/data/MSlab/21_projects/18-0008_Eva_Maleckova/UHPLC-DAD/2018-04-11_DataAnalysis_UpUpdated/")
+rm(list = ls())
+
+
+sample.list <- data.frame(read_xlsx("../AAs-HPLC-test-2018_02_21_DB.xlsx", "Sample list"))
+condi.colnames <- c("Condition.1", "Condition.2")
+matching.name.col <- 'Sample.ID'
+
+#################################################
+
+required.packages <- c("Rmisc", "plyr", "ggplot2", "readxl","reshape2", "gridExtra")
+
+for(package in required.packages)
+{
+  print(package)
+  ## Check if package is installed. If not, install
+  if(!package %in% row.names(installed.packages())){install.packages(package, repos ="https://cran.uni-muenster.de/")}
+  # ## Check if package is up to date. If not, update
+  # update.packages(package, repos = "https://cran.uni-muenster.de/")
+  ## Load package
+  library(package, character.only = T)
+}
+
+
+theme_dominik <- 
+  theme(panel.background = element_blank(), panel.border = element_rect(fill = NA)) + 
+  theme(axis.text = element_text(color = "black"), axis.ticks = element_line(color = "black"), axis.title.y = element_text(color = "black"), axis.title.x = element_blank()) +
+  theme(plot.title = element_text(face= "bold")) +
+  theme(aspect.ratio = 1) +
+  theme(strip.background = element_blank(), strip.text = element_text(size = 10, face = "bold")) + 
+  theme(legend.position = "right", legend.direction = "vertical", legend.title = element_blank())
+
+ggplotRegression <- function (fit) {
+  
+  ggplot(fit$model, aes_string(x = names(fit$model)[2], y = names(fit$model)[1])) +
+    stat_smooth(method = "lm", col = "firebrick") +
+    geom_point(size = 2) +
+    annotate("text", x = min(fit$model[,2]), y = max(fit$model[,1]), hjust = 0,  vjust = 1, label = paste("Adj R2 = ",signif(summary(fit)$adj.r.squared, 4),
+                                                                        "\nIntercept =",signif(fit$coef[[1]],2 ),
+                                                                        "\nSlope =",signif(fit$coef[[2]], 2),
+                                                                        "\nP =",signif(summary(fit)$coef[2,4], 2))
+            ) + 
+    theme_dominik
+}
+
+
+
+
+load("01.UHPLC.RData")
+
+
+### Calibration curves
+
+
+calib <- final.summary$Calibration
+calib$std.amount <- as.numeric(gsub('NA', '', do.call(rbind, lapply(strsplit(calib$Sample.name, split = ""), function(x){paste(as.numeric(x), collapse = '')}))))
+
+# calib <- subset(calib, !is.na(Amount[pmol]))
+# calib <- subset(calib, Sample.name != "200 pmol Mix")
+
+calib <- subset(calib, !Compound %in%  c('Histidine', 'Tryptophane', 'Norvaline'))
+
+count(calib$Compound)
+
+calib.list <- list()
+for(cc in unique(calib$Compound))
+{
+  calib.list[[cc]] <- ggplotRegression(lm(Concentration_pmol.µl ~ std.amount, data = subset(calib, Compound == cc)))  + ggtitle(cc)
+}
+
+
+
+# p1 <- ggplot(calib, aes(x = std.amount, y = Amount)) + 
+  # geom_point() + 
+  # facet_wrap(~Compound) + 
+  # theme_dominik + theme(panel.grid.major = element_line(colour = "grey"))
+  
+
+pdf(paste(Sys.Date(), "CalibrationCurves.pdf", sep = ''),width = 20, height = 20)
+do.call(grid.arrange, calib.list)
+dev.off()
+
+
+
+
+sample.data <- merge(final.summary$Sample, sample.list, by.x = "Sample.name", by.y = matching.name.col)
+
+sample.data <- subset(sample.data, Compound != 'Norvaline')
+
+
+### Create a group variable based on sample list (e.g. different species, conditions, treatments, etc.)
+if(length(condi.colnames) > 1)
+  
+{sample.data$GroupVar <- apply(sample.data[,condi.colnames], 1, function(x){paste(x, collapse = "\n")})
+}else{
+  sample.data$GroupVar <- sample.data[,condi.colnames]
+}
+
+sample.data$GroupVar <- factor(sample.data$GroupVar, levels = unique(sample.data[order(sample.data[,condi.colnames[1]], sample.data[,condi.colnames[2]]),  "GroupVar"]))
+
+sample.data$Inj..volume <- as.numeric(sample.data$Inj..volume)
+
+
+
+if(length(unique(as.numeric(c(sample.data$Inj..volume, calib$Inj..volume)))) != 1){warning("Injection volume was not the same across all measurements")}
+
+
+# sample.data$AmountInDeriv <- sample.data$Amount / sample.data$Total.derivatisation..volume..µl. * sample.data$Inj..volume
+# sample.data$AmountInResusp <- sample.data$AmountInDeriv * sample.data$Resuspension...volume....µl. / sample.data$Sample.volume...used.for.derivatisation..µl.
+# # sample.data$AmountInExtract <- sample.data$AmountInResusp * sample.data$Extraction...volume...µl. / sample.data$Volume.in...speed.vac....µl.
+# # sample.data$pmol.mg.FW <- sample.data$AmountInExtract / sample.data$Fresh.weight..mg..or...culture.volume..ml....used.for.extraction
+# sample.data$pmol.mg.FW <- sample.data$AmountInExtract / sample.data$OD
+# 
+
+
+## Calculate the amount (in pmol) in the derivatization 
+## 1µl is injected out of e.g. 50 µl derivatization mix
+## e.g. 15 pmol/µl * 1 µl injected * 50 µl (total) / 1 µl (inj)
+
+sample.data$AmountInDeriv <- sample.data$Concentration_pmol.µl * sample.data$Total.derivatisation..volume..µl.
+
+## Only a fraction (typically 1/5) of the speed vac reuspension is used 
+sample.data$AmountInResusp <- sample.data$AmountInDeriv * sample.data$Resuspension...volume....µl. / sample.data$Sample.volume...used.for.derivatisation..µl.
+
+## During speed vac, the sample is concentrated (e.g. 4x)
+sample.data$AmountInSpeedVac <- sample.data$AmountInResusp * sample.data$Resuspension...volume....µl. / sample.data$Volume.in...speed.vac....µl.
+
+## Only a fraction (typically 1/4) of the extract is used 
+sample.data$AmountInExtract <- sample.data$AmountInSpeedVac * sample.data$Extraction...volume...µl. / sample.data$Volume.in...speed.vac....µl.
+
+## Normalize for mg FW
+sample.data$pmol.mg <- sample.data$AmountInExtract / sample.data$Fresh.weight..mg..or...culture.volume..ml....used.for.extraction
+sample.data$nmol.mg <- sample.data$pmol.mg / 1000
+
+## Normalize for culture volume and OD
+# sample.data$pmol.ml.OD <- sample.data$AmountInExtract / sample.data$Fresh.weight..mg..or...culture.volume..ml....used.for.extraction / sample.data$Cultured..density...OD.
+# sample.data$nmol.ml.OD <- sample.data$pmol.ml.OD / 1000
+
+  
+
+# p2 <- ggplot(sample.data, aes(x = GroupVar, y = nmol.ml.OD)) + 
+p2 <- ggplot(sample.data, aes(x = GroupVar, y = nmol.mg)) + 
+  # geom_point(aes(col = Condition.2, shape = Condition.3)) + 
+  geom_text(aes(label  = Sample.name, col = GroupVar), size = 2) + 
+  facet_wrap(~Compound, scales = "free") + 
+  # scale_color_brewer() +
+  theme_dominik + 
+  theme(axis.text.x = element_blank())
+
+
+pdf(paste(Sys.Date(), "AminoAcids.pdf", sep = ''),width = 16, height = 16)
+p2
+dev.off()
+
+
+
+write.table(sample.data, file = paste(Sys.Date(), 'Data.txt', sep = ''), sep = '\t', row.names = F)
+
+
+
+
+sample.data$GroupVar
+
+
diff --git a/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-11_DataAnalysis_UpUpdated/2018-04-10_Report.pdf b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-11_DataAnalysis_UpUpdated/2018-04-10_Report.pdf
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diff --git a/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-11_DataAnalysis_UpUpdated/2018-04-10_Report.xlsx b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-11_DataAnalysis_UpUpdated/2018-04-10_Report.xlsx
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diff --git a/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-11_DataAnalysis_UpUpdated/2018-04-12AminoAcids.pdf b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-11_DataAnalysis_UpUpdated/2018-04-12AminoAcids.pdf
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diff --git a/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-11_DataAnalysis_UpUpdated/2018-04-12Data.txt b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-11_DataAnalysis_UpUpdated/2018-04-12Data.txt
new file mode 100755
index 0000000000000000000000000000000000000000..32b82a64cbea32ba9c2428c741528f1849a552f8
--- /dev/null
+++ b/cmml/18-0008_Eva_Maleckova/UHPLC-DAD_testRun/2018-04-11_DataAnalysis_UpUpdated/2018-04-12Data.txt
@@ -0,0 +1,273 @@
+"Sample.name"	"Data.file"	"Instrument"	"Injection.date"	"Inj..volume"	"Location"	"Acq..method"	"Type"	"Processing.method"	"Manually.modified"	"Signal"	"Compound"	"RT.[min]"	"RF"	"Area"	"Amount_pmol"	"Concentration_pmol.µl"	"ISTD.Name"	"Sample.number"	"Species"	"Tissue.type"	"Condition.1"	"Condition.2"	"Condition.3"	"Technical.replicate"	"Biological.replicate"	"Cultured..density...OD."	"Fresh.weight..mg..or...culture.volume..ml....used.for.extraction"	"Extraction..buffer"	"Extraction...volume...µl."	"Volume.in...speed.vac....µl."	"Resuspension...volume....µl."	"Sample.volume...used.for.derivatisation..µl."	"Total.derivatisation..volume..µl."	"GroupVar"	"AmountInDeriv"	"AmountInResusp"	"AmountInSpeedVac"	"AmountInExtract"	"pmol.mg"	"nmol.mg"
+"102.1"	"180301_10.dx"	"OpenLab 1"	"2018-03-01 18:08:21+01:00"	1	"P1-B-4"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Serine"	2.022	0.369	18.806	3.14	3.14	"Norvaline"	4	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	1	1	"NA"	42.8	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	157	785	392.5	4710	110.046728971963	0.110046728971963
+"102.1"	"180301_10.dx"	"OpenLab 1"	"2018-03-01 18:08:21+01:00"	1	"P1-B-4"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Arginine + Glutamine"	2.079	0.314	16.264	3.186	3.186	"Norvaline"	4	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	1	1	"NA"	42.8	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	159.3	796.5	398.25	4779	111.658878504673	0.111658878504673
+"102.1"	"180301_10.dx"	"OpenLab 1"	"2018-03-01 18:08:21+01:00"	1	"P1-B-4"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Glycine"	2.25	0.4	6.463	0.995	0.995	"Norvaline"	4	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	1	1	"NA"	42.8	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	49.75	248.75	124.375	1492.5	34.8714953271028	0.0348714953271028
+"102.1"	"180301_10.dx"	"OpenLab 1"	"2018-03-01 18:08:21+01:00"	1	"P1-B-4"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Aspartate"	2.4	0.388	13.701	2.174	2.174	"Norvaline"	4	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	1	1	"NA"	42.8	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	108.7	543.5	271.75	3261	76.1915887850467	0.0761915887850467
+"102.1"	"180301_10.dx"	"OpenLab 1"	"2018-03-01 18:08:21+01:00"	1	"P1-B-4"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Glutamate"	2.782	0.217	78.192	22.189	22.189	"Norvaline"	4	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	1	1	"NA"	42.8	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	1109.45	5547.25	2773.625	33283.5	777.651869158879	0.777651869158879
+"102.1"	"180301_10.dx"	"OpenLab 1"	"2018-03-01 18:08:21+01:00"	1	"P1-B-4"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Threonine"	3.176	-0.006	0.128	-1.426	-1.426	"Norvaline"	4	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	1	1	"NA"	42.8	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	-71.3	-356.5	-178.25	-2139	-49.9766355140187	-0.0499766355140187
+"102.1"	"180301_10.dx"	"OpenLab 1"	"2018-03-01 18:08:21+01:00"	1	"P1-B-4"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Alanine"	3.602	-1.074	3.687	-0.212	-0.212	"Norvaline"	4	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	1	1	"NA"	42.8	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	-10.6	-53	-26.5	-318	-7.42990654205608	-0.00742990654205608
+"102.1"	"180301_10.dx"	"OpenLab 1"	"2018-03-01 18:08:21+01:00"	1	"P1-B-4"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Proline"	4.325	0.827	4.124	0.307	0.307	"Norvaline"	4	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	1	1	"NA"	42.8	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	15.35	76.75	38.375	460.5	10.7593457943925	0.0107593457943925
+"102.1"	"180301_10.dx"	"OpenLab 1"	"2018-03-01 18:08:21+01:00"	1	"P1-B-4"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Lysine"	6.077	-0.791	1.152	-0.09	-0.09	"Norvaline"	4	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	1	1	"NA"	42.8	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	-4.5	-22.5	-11.25	-135	-3.15420560747664	-0.00315420560747664
+"102.1"	"180301_10.dx"	"OpenLab 1"	"2018-03-01 18:08:21+01:00"	1	"P1-B-4"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Tyrosine"	6.266	-0.197	1.572	-0.491	-0.491	"Norvaline"	4	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	1	1	"NA"	42.8	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	-24.55	-122.75	-61.375	-736.5	-17.2079439252336	-0.0172079439252336
+"102.1"	"180301_10.dx"	"OpenLab 1"	"2018-03-01 18:08:21+01:00"	1	"P1-B-4"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Valine"	6.702	-0.182	3.726	-1.263	-1.263	"Norvaline"	4	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	1	1	"NA"	42.8	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	-63.15	-315.75	-157.875	-1894.5	-44.2640186915888	-0.0442640186915888
+"102.1"	"180301_10.dx"	"OpenLab 1"	"2018-03-01 18:08:21+01:00"	1	"P1-B-4"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Isoleucine"	7.728	-0.334	3.294	-0.607	-0.607	"Norvaline"	4	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	1	1	"NA"	42.8	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	-30.35	-151.75	-75.875	-910.5	-21.2733644859813	-0.0212733644859813
+"102.1"	"180301_10.dx"	"OpenLab 1"	"2018-03-01 18:08:21+01:00"	1	"P1-B-4"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Leucine"	7.824	-0.145	2.425	-1.032	-1.032	"Norvaline"	4	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	1	1	"NA"	42.8	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	-51.6	-258	-129	-1548	-36.1682242990654	-0.0361682242990654
+"102.1"	"180301_10.dx"	"OpenLab 1"	"2018-03-01 18:08:21+01:00"	1	"P1-B-4"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Phenylalanine"	7.911	-0.072	1.924	-1.65	-1.65	"Norvaline"	4	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	1	1	"NA"	42.8	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	-82.5	-412.5	-206.25	-2475	-57.8271028037383	-0.0578271028037383
+"102.2"	"180301_11.dx"	"OpenLab 1"	"2018-03-01 18:18:16+01:00"	1	"P1-B-5"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Serine"	2.016	0.313	20.527	4.74	4.74	"Norvaline"	5	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	2	1	"NA"	47.1	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	237	1185	592.5	7110	150.955414012739	0.150955414012739
+"102.2"	"180301_11.dx"	"OpenLab 1"	"2018-03-01 18:18:16+01:00"	1	"P1-B-5"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Arginine + Glutamine"	2.072	0.303	15.007	3.583	3.583	"Norvaline"	5	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	2	1	"NA"	47.1	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	179.15	895.75	447.875	5374.5	114.108280254777	0.114108280254777
+"102.2"	"180301_11.dx"	"OpenLab 1"	"2018-03-01 18:18:16+01:00"	1	"P1-B-5"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Glycine"	2.249	0.303	8.275	1.972	1.972	"Norvaline"	5	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	2	1	"NA"	47.1	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	98.6	493	246.5	2958	62.8025477707006	0.0628025477707006
+"102.2"	"180301_11.dx"	"OpenLab 1"	"2018-03-01 18:18:16+01:00"	1	"P1-B-5"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Aspartate"	2.397	0.261	22.958	6.366	6.366	"Norvaline"	5	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	2	1	"NA"	47.1	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	318.3	1591.5	795.75	9549	202.738853503185	0.202738853503185
+"102.2"	"180301_11.dx"	"OpenLab 1"	"2018-03-01 18:18:16+01:00"	1	"P1-B-5"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Glutamate"	2.781	0.212	92.931	31.633	31.633	"Norvaline"	5	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	2	1	"NA"	47.1	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	1581.65	7908.25	3954.125	47449.5	1007.42038216561	1.0074203821656
+"102.2"	"180301_11.dx"	"OpenLab 1"	"2018-03-01 18:18:16+01:00"	1	"P1-B-5"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Alanine"	3.604	-2.575	3.482	-0.098	-0.098	"Norvaline"	5	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	2	1	"NA"	47.1	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	-4.9	-24.5	-12.25	-147	-3.12101910828026	-0.00312101910828026
+"102.2"	"180301_11.dx"	"OpenLab 1"	"2018-03-01 18:18:16+01:00"	1	"P1-B-5"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Proline"	4.325	0.35	6.137	1.266	1.266	"Norvaline"	5	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	2	1	"NA"	47.1	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	63.3	316.5	158.25	1899	40.3184713375796	0.0403184713375796
+"102.2"	"180301_11.dx"	"OpenLab 1"	"2018-03-01 18:18:16+01:00"	1	"P1-B-5"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Cysteine"	5.983	-0.003	0.027	-0.648	-0.648	"Norvaline"	5	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	2	1	"NA"	47.1	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	-32.4	-162	-81	-972	-20.6369426751592	-0.0206369426751592
+"102.2"	"180301_11.dx"	"OpenLab 1"	"2018-03-01 18:18:16+01:00"	1	"P1-B-5"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Lysine"	6.077	6.165	1.301	0.015	0.015	"Norvaline"	5	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	2	1	"NA"	47.1	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	0.75	3.75	1.875	22.5	0.477707006369427	0.000477707006369427
+"102.2"	"180301_11.dx"	"OpenLab 1"	"2018-03-01 18:18:16+01:00"	1	"P1-B-5"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Tyrosine"	6.265	-0.289	1.678	-0.419	-0.419	"Norvaline"	5	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	2	1	"NA"	47.1	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	-20.95	-104.75	-52.375	-628.5	-13.343949044586	-0.013343949044586
+"102.2"	"180301_11.dx"	"OpenLab 1"	"2018-03-01 18:18:16+01:00"	1	"P1-B-5"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Methionine"	6.394	-0.001	0.022	-2.792	-2.792	"Norvaline"	5	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	2	1	"NA"	47.1	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	-139.6	-698	-349	-4188	-88.9171974522293	-0.0889171974522293
+"102.2"	"180301_11.dx"	"OpenLab 1"	"2018-03-01 18:18:16+01:00"	1	"P1-B-5"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Valine"	6.702	-0.283	3.958	-1.01	-1.01	"Norvaline"	5	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	2	1	"NA"	47.1	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	-50.5	-252.5	-126.25	-1515	-32.1656050955414	-0.0321656050955414
+"102.2"	"180301_11.dx"	"OpenLab 1"	"2018-03-01 18:18:16+01:00"	1	"P1-B-5"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Isoleucine"	7.727	-0.71	3.535	-0.36	-0.36	"Norvaline"	5	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	2	1	"NA"	47.1	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	-18	-90	-45	-540	-11.4649681528662	-0.0114649681528662
+"102.2"	"180301_11.dx"	"OpenLab 1"	"2018-03-01 18:18:16+01:00"	1	"P1-B-5"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Leucine"	7.822	-0.223	2.605	-0.843	-0.843	"Norvaline"	5	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	2	1	"NA"	47.1	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	-42.15	-210.75	-105.375	-1264.5	-26.8471337579618	-0.0268471337579618
+"102.2"	"180301_11.dx"	"OpenLab 1"	"2018-03-01 18:18:16+01:00"	1	"P1-B-5"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Phenylalanine"	7.91	-0.103	2.121	-1.488	-1.488	"Norvaline"	5	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	2	1	"NA"	47.1	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	-74.4	-372	-186	-2232	-47.3885350318471	-0.0473885350318471
+"102.3"	"180301_12.dx"	"OpenLab 1"	"2018-03-01 18:28:10+01:00"	1	"P1-B-6"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Serine"	2.011	0.312	25.508	4.791	4.791	"Norvaline"	6	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	3	1	"NA"	55.3	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	239.55	1197.75	598.875	7186.5	129.9547920434	0.1299547920434
+"102.3"	"180301_12.dx"	"OpenLab 1"	"2018-03-01 18:28:10+01:00"	1	"P1-B-6"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Arginine + Glutamine"	2.068	0.273	24.259	5.2	5.2	"Norvaline"	6	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	3	1	"NA"	55.3	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	260	1300	650	7800	141.048824593128	0.141048824593128
+"102.3"	"180301_12.dx"	"OpenLab 1"	"2018-03-01 18:28:10+01:00"	1	"P1-B-6"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Glycine"	2.243	0.316	9.418	1.744	1.744	"Norvaline"	6	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	3	1	"NA"	55.3	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	87.2	436	218	2616	47.3056057866185	0.0473056057866185
+"102.3"	"180301_12.dx"	"OpenLab 1"	"2018-03-01 18:28:10+01:00"	1	"P1-B-6"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Aspartate"	2.392	0.305	19.854	3.812	3.812	"Norvaline"	6	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	3	1	"NA"	55.3	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	190.6	953	476.5	5718	103.399638336347	0.103399638336347
+"102.3"	"180301_12.dx"	"OpenLab 1"	"2018-03-01 18:28:10+01:00"	1	"P1-B-6"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Glutamate"	2.775	0.212	114.868	31.688	31.688	"Norvaline"	6	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	3	1	"NA"	55.3	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	1584.4	7922	3961	47532	859.529837251356	0.859529837251356
+"102.3"	"180301_12.dx"	"OpenLab 1"	"2018-03-01 18:28:10+01:00"	1	"P1-B-6"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Threonine"	3.173	-0.013	0.305	-1.38	-1.38	"Norvaline"	6	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	3	1	"NA"	55.3	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	-69	-345	-172.5	-2070	-37.4321880650995	-0.0374321880650995
+"102.3"	"180301_12.dx"	"OpenLab 1"	"2018-03-01 18:28:10+01:00"	1	"P1-B-6"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Alanine"	3.599	0.974	5.966	0.358	0.358	"Norvaline"	6	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	3	1	"NA"	55.3	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	17.9	89.5	44.75	537	9.71066907775768	0.00971066907775768
+"102.3"	"180301_12.dx"	"OpenLab 1"	"2018-03-01 18:28:10+01:00"	1	"P1-B-6"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Proline"	4.323	0.33	8.21	1.455	1.455	"Norvaline"	6	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	3	1	"NA"	55.3	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	72.75	363.75	181.875	2182.5	39.4665461121157	0.0394665461121157
+"102.3"	"180301_12.dx"	"OpenLab 1"	"2018-03-01 18:28:10+01:00"	1	"P1-B-6"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Cysteine"	5.976	-0.004	0.047	-0.643	-0.643	"Norvaline"	6	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	3	1	"NA"	55.3	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	-32.15	-160.75	-80.375	-964.5	-17.4412296564195	-0.0174412296564195
+"102.3"	"180301_12.dx"	"OpenLab 1"	"2018-03-01 18:28:10+01:00"	1	"P1-B-6"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Lysine"	6.074	5.875	1.609	0.016	0.016	"Norvaline"	6	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	3	1	"NA"	55.3	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	0.8	4	2	24	0.433996383363472	0.000433996383363472
+"102.3"	"180301_12.dx"	"OpenLab 1"	"2018-03-01 18:28:10+01:00"	1	"P1-B-6"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Tyrosine"	6.262	-0.525	2.73	-0.305	-0.305	"Norvaline"	6	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	3	1	"NA"	55.3	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	-15.25	-76.25	-38.125	-457.5	-8.27305605786619	-0.00827305605786618
+"102.3"	"180301_12.dx"	"OpenLab 1"	"2018-03-01 18:28:10+01:00"	1	"P1-B-6"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Valine"	6.699	-0.352	5.344	-0.889	-0.889	"Norvaline"	6	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	3	1	"NA"	55.3	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	-44.45	-222.25	-111.125	-1333.5	-24.1139240506329	-0.0241139240506329
+"102.3"	"180301_12.dx"	"OpenLab 1"	"2018-03-01 18:28:10+01:00"	1	"P1-B-6"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Isoleucine"	7.726	-1.17	4.798	-0.24	-0.24	"Norvaline"	6	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	3	1	"NA"	55.3	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	-12	-60	-30	-360	-6.50994575045208	-0.00650994575045208
+"102.3"	"180301_12.dx"	"OpenLab 1"	"2018-03-01 18:28:10+01:00"	1	"P1-B-6"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Leucine"	7.822	-0.26	3.449	-0.777	-0.777	"Norvaline"	6	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	3	1	"NA"	55.3	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	-38.85	-194.25	-97.125	-1165.5	-21.0759493670886	-0.0210759493670886
+"102.3"	"180301_12.dx"	"OpenLab 1"	"2018-03-01 18:28:10+01:00"	1	"P1-B-6"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Phenylalanine"	7.91	-0.104	2.631	-1.484	-1.484	"Norvaline"	6	"Talinum triangulare"	"Leaf"	"CAM"	"ED"	"NA"	3	1	"NA"	55.3	"80% ethanol"	1200	100	50	10	50	"CAM
+ED"	-74.2	-371	-185.5	-2226	-40.253164556962	-0.040253164556962
+"122.1"	"180301_13.dx"	"OpenLab 1"	"2018-03-01 18:38:03+01:00"	1	"P1-B-7"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Serine"	2.054	0.245	46.237	12.474	12.474	"Norvaline"	7	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	1	1	"NA"	66.3	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	623.7	3118.5	1559.25	18711	282.217194570136	0.282217194570136
+"122.1"	"180301_13.dx"	"OpenLab 1"	"2018-03-01 18:38:03+01:00"	1	"P1-B-7"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Glycine"	2.232	-1.67	2.629	-0.104	-0.104	"Norvaline"	7	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	1	1	"NA"	66.3	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	-5.2	-26	-13	-156	-2.35294117647059	-0.00235294117647059
+"122.1"	"180301_13.dx"	"OpenLab 1"	"2018-03-01 18:38:03+01:00"	1	"P1-B-7"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Aspartate"	2.382	0.217	61.876	18.848	18.848	"Norvaline"	7	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	1	1	"NA"	66.3	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	942.4	4712	2356	28272	426.425339366516	0.426425339366516
+"122.1"	"180301_13.dx"	"OpenLab 1"	"2018-03-01 18:38:03+01:00"	1	"P1-B-7"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Glutamate"	2.769	0.214	87.353	26.915	26.915	"Norvaline"	7	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	1	1	"NA"	66.3	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	1345.75	6728.75	3364.375	40372.5	608.93665158371	0.60893665158371
+"122.1"	"180301_13.dx"	"OpenLab 1"	"2018-03-01 18:38:03+01:00"	1	"P1-B-7"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Threonine"	3.169	-0.026	0.521	-1.303	-1.303	"Norvaline"	7	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	1	1	"NA"	66.3	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	-65.15	-325.75	-162.875	-1954.5	-29.4796380090498	-0.0294796380090498
+"122.1"	"180301_13.dx"	"OpenLab 1"	"2018-03-01 18:38:03+01:00"	1	"P1-B-7"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Alanine"	3.607	-0.029	0.499	-1.118	-1.118	"Norvaline"	7	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	1	1	"NA"	66.3	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	-55.9	-279.5	-139.75	-1677	-25.2941176470588	-0.0252941176470588
+"122.1"	"180301_13.dx"	"OpenLab 1"	"2018-03-01 18:38:03+01:00"	1	"P1-B-7"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Proline"	4.32	0.267	11.292	2.795	2.795	"Norvaline"	7	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	1	1	"NA"	66.3	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	139.75	698.75	349.375	4192.5	63.2352941176471	0.0632352941176471
+"122.1"	"180301_13.dx"	"OpenLab 1"	"2018-03-01 18:38:03+01:00"	1	"P1-B-7"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Cysteine"	5.979	-0.016	0.148	-0.604	-0.604	"Norvaline"	7	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	1	1	"NA"	66.3	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	-30.2	-151	-75.5	-906	-13.6651583710407	-0.0136651583710407
+"122.1"	"180301_13.dx"	"OpenLab 1"	"2018-03-01 18:38:03+01:00"	1	"P1-B-7"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Lysine"	6.074	0.303	5.013	1.092	1.092	"Norvaline"	7	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	1	1	"NA"	66.3	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	54.6	273	136.5	1638	24.7058823529412	0.0247058823529412
+"122.1"	"180301_13.dx"	"OpenLab 1"	"2018-03-01 18:38:03+01:00"	1	"P1-B-7"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Tyrosine"	6.264	0.716	7.511	0.692	0.692	"Norvaline"	7	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	1	1	"NA"	66.3	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	34.6	173	86.5	1038	15.6561085972851	0.0156561085972851
+"122.1"	"180301_13.dx"	"OpenLab 1"	"2018-03-01 18:38:03+01:00"	1	"P1-B-7"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Valine"	6.7	1.156	9.593	0.548	0.548	"Norvaline"	7	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	1	1	"NA"	66.3	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	27.4	137	68.5	822	12.3981900452489	0.0123981900452489
+"122.1"	"180301_13.dx"	"OpenLab 1"	"2018-03-01 18:38:03+01:00"	1	"P1-B-7"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Isoleucine"	7.726	-0.882	4.052	-0.303	-0.303	"Norvaline"	7	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	1	1	"NA"	66.3	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	-15.15	-75.75	-37.875	-454.5	-6.8552036199095	-0.0068552036199095
+"122.1"	"180301_13.dx"	"OpenLab 1"	"2018-03-01 18:38:03+01:00"	1	"P1-B-7"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Leucine"	7.823	-0.537	3.963	-0.487	-0.487	"Norvaline"	7	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	1	1	"NA"	66.3	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	-24.35	-121.75	-60.875	-730.5	-11.0180995475113	-0.0110180995475113
+"122.1"	"180301_13.dx"	"OpenLab 1"	"2018-03-01 18:38:03+01:00"	1	"P1-B-7"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Phenylalanine"	7.911	-0.466	4.906	-0.695	-0.695	"Norvaline"	7	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	1	1	"NA"	66.3	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	-34.75	-173.75	-86.875	-1042.5	-15.7239819004525	-0.0157239819004525
+"122.2"	"180301_14.dx"	"OpenLab 1"	"2018-03-01 18:47:57+01:00"	1	"P1-B-8"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Histidine"	1.419	0.103	0.993	0.669	0.669	"Norvaline"	8	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	2	1	"NA"	56.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	33.45	167.25	83.625	1003.5	17.855871886121	0.017855871886121
+"122.2"	"180301_14.dx"	"OpenLab 1"	"2018-03-01 18:47:57+01:00"	1	"P1-B-8"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Serine"	2.011	0.512	12.407	1.688	1.688	"Norvaline"	8	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	2	1	"NA"	56.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	84.4	422	211	2532	45.0533807829181	0.0450533807829181
+"122.2"	"180301_14.dx"	"OpenLab 1"	"2018-03-01 18:47:57+01:00"	1	"P1-B-8"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Arginine + Glutamine"	2.068	0.248	30.235	8.497	8.497	"Norvaline"	8	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	2	1	"NA"	56.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	424.85	2124.25	1062.125	12745.5	226.788256227758	0.226788256227758
+"122.2"	"180301_14.dx"	"OpenLab 1"	"2018-03-01 18:47:57+01:00"	1	"P1-B-8"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Glycine"	2.239	-0.534	2.024	-0.264	-0.264	"Norvaline"	8	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	2	1	"NA"	56.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	-13.2	-66	-33	-396	-7.04626334519573	-0.00704626334519573
+"122.2"	"180301_14.dx"	"OpenLab 1"	"2018-03-01 18:47:57+01:00"	1	"P1-B-8"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Aspartate"	2.391	0.223	47.476	14.839	14.839	"Norvaline"	8	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	2	1	"NA"	56.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	741.95	3709.75	1854.875	22258.5	396.05871886121	0.39605871886121
+"122.2"	"180301_14.dx"	"OpenLab 1"	"2018-03-01 18:47:57+01:00"	1	"P1-B-8"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Glutamate"	2.775	0.219	61.275	19.446	19.446	"Norvaline"	8	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	2	1	"NA"	56.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	972.3	4861.5	2430.75	29169	519.021352313167	0.519021352313167
+"122.2"	"180301_14.dx"	"OpenLab 1"	"2018-03-01 18:47:57+01:00"	1	"P1-B-8"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Threonine"	3.171	-0.019	0.361	-1.346	-1.346	"Norvaline"	8	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	2	1	"NA"	56.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	-67.3	-336.5	-168.25	-2019	-35.9252669039146	-0.0359252669039146
+"122.2"	"180301_14.dx"	"OpenLab 1"	"2018-03-01 18:47:57+01:00"	1	"P1-B-8"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Alanine"	3.62	-0.02	0.338	-1.162	-1.162	"Norvaline"	8	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	2	1	"NA"	56.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	-58.1	-290.5	-145.25	-1743	-31.0142348754448	-0.0310142348754448
+"122.2"	"180301_14.dx"	"OpenLab 1"	"2018-03-01 18:47:57+01:00"	1	"P1-B-8"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Proline"	4.322	0.28	9.384	2.329	2.329	"Norvaline"	8	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	2	1	"NA"	56.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	116.45	582.25	291.125	3493.5	62.161921708185	0.062161921708185
+"122.2"	"180301_14.dx"	"OpenLab 1"	"2018-03-01 18:47:57+01:00"	1	"P1-B-8"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Cysteine"	5.981	-0.031	0.248	-0.563	-0.563	"Norvaline"	8	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	2	1	"NA"	56.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	-28.15	-140.75	-70.375	-844.5	-15.0266903914591	-0.0150266903914591
+"122.2"	"180301_14.dx"	"OpenLab 1"	"2018-03-01 18:47:57+01:00"	1	"P1-B-8"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Lysine"	6.075	0.338	3.73	0.769	0.769	"Norvaline"	8	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	2	1	"NA"	56.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	38.45	192.25	96.125	1153.5	20.5249110320285	0.0205249110320285
+"122.2"	"180301_14.dx"	"OpenLab 1"	"2018-03-01 18:47:57+01:00"	1	"P1-B-8"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Tyrosine"	6.262	1.658	4.732	0.199	0.199	"Norvaline"	8	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	2	1	"NA"	56.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	9.95	49.75	24.875	298.5	5.31138790035587	0.00531138790035587
+"122.2"	"180301_14.dx"	"OpenLab 1"	"2018-03-01 18:47:57+01:00"	1	"P1-B-8"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Valine"	6.7	-0.566	5.268	-0.648	-0.648	"Norvaline"	8	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	2	1	"NA"	56.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	-32.4	-162	-81	-972	-17.2953736654804	-0.0172953736654804
+"122.2"	"180301_14.dx"	"OpenLab 1"	"2018-03-01 18:47:57+01:00"	1	"P1-B-8"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Isoleucine"	7.728	-0.261	2.63	-0.7	-0.7	"Norvaline"	8	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	2	1	"NA"	56.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	-35	-175	-87.5	-1050	-18.6832740213523	-0.0186832740213523
+"122.2"	"180301_14.dx"	"OpenLab 1"	"2018-03-01 18:47:57+01:00"	1	"P1-B-8"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Leucine"	7.824	-0.205	2.592	-0.881	-0.881	"Norvaline"	8	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	2	1	"NA"	56.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	-44.05	-220.25	-110.125	-1321.5	-23.5142348754448	-0.0235142348754448
+"122.2"	"180301_14.dx"	"OpenLab 1"	"2018-03-01 18:47:57+01:00"	1	"P1-B-8"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Phenylalanine"	7.912	-0.21	3.361	-1.113	-1.113	"Norvaline"	8	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	2	1	"NA"	56.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	-55.65	-278.25	-139.125	-1669.5	-29.7064056939502	-0.0297064056939502
+"122.3"	"180301_15.dx"	"OpenLab 1"	"2018-03-01 18:57:51+01:00"	1	"P1-B-9"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Histidine"	1.451	0.103	1.36	0.804	0.804	"Norvaline"	9	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	3	1	"NA"	59.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	40.2	201	100.5	1206	20.3716216216216	0.0203716216216216
+"122.3"	"180301_15.dx"	"OpenLab 1"	"2018-03-01 18:57:51+01:00"	1	"P1-B-9"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Serine"	2.031	0.504	14.279	1.73	1.73	"Norvaline"	9	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	3	1	"NA"	59.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	86.5	432.5	216.25	2595	43.8344594594595	0.0438344594594595
+"122.3"	"180301_15.dx"	"OpenLab 1"	"2018-03-01 18:57:51+01:00"	1	"P1-B-9"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Arginine + Glutamine"	2.097	0.248	34.189	8.419	8.419	"Norvaline"	9	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	3	1	"NA"	59.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	420.95	2104.75	1052.375	12628.5	213.319256756757	0.213319256756757
+"122.3"	"180301_15.dx"	"OpenLab 1"	"2018-03-01 18:57:51+01:00"	1	"P1-B-9"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Glycine"	2.256	-4.388	3.047	-0.042	-0.042	"Norvaline"	9	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	3	1	"NA"	59.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	-2.1	-10.5	-5.25	-63	-1.06418918918919	-0.00106418918918919
+"122.3"	"180301_15.dx"	"OpenLab 1"	"2018-03-01 18:57:51+01:00"	1	"P1-B-9"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Glutamate"	2.787	0.219	70.664	19.7	19.7	"Norvaline"	9	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	3	1	"NA"	59.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	985	4925	2462.5	29550	499.155405405405	0.499155405405405
+"122.3"	"180301_15.dx"	"OpenLab 1"	"2018-03-01 18:57:51+01:00"	1	"P1-B-9"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Threonine"	3.179	-0.013	0.295	-1.379	-1.379	"Norvaline"	9	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	3	1	"NA"	59.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	-68.95	-344.75	-172.375	-2068.5	-34.9408783783784	-0.0349408783783784
+"122.3"	"180301_15.dx"	"OpenLab 1"	"2018-03-01 18:57:51+01:00"	1	"P1-B-9"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Alanine"	3.627	-0.035	0.629	-1.092	-1.092	"Norvaline"	9	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	3	1	"NA"	59.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	-54.6	-273	-136.5	-1638	-27.6689189189189	-0.0276689189189189
+"122.3"	"180301_15.dx"	"OpenLab 1"	"2018-03-01 18:57:51+01:00"	1	"P1-B-9"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Proline"	4.327	0.28	10.764	2.351	2.351	"Norvaline"	9	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	3	1	"NA"	59.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	117.55	587.75	293.875	3526.5	59.5692567567568	0.0595692567567567
+"122.3"	"180301_15.dx"	"OpenLab 1"	"2018-03-01 18:57:51+01:00"	1	"P1-B-9"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Cysteine"	5.982	-0.031	0.284	-0.562	-0.562	"Norvaline"	9	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	3	1	"NA"	59.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	-28.1	-140.5	-70.25	-843	-14.2398648648649	-0.0142398648648649
+"122.3"	"180301_15.dx"	"OpenLab 1"	"2018-03-01 18:57:51+01:00"	1	"P1-B-9"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Lysine"	6.076	0.345	4.09	0.724	0.724	"Norvaline"	9	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	3	1	"NA"	59.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	36.2	181	90.5	1086	18.3445945945946	0.0183445945945946
+"122.3"	"180301_15.dx"	"OpenLab 1"	"2018-03-01 18:57:51+01:00"	1	"P1-B-9"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Tyrosine"	6.264	1.016	6.427	0.386	0.386	"Norvaline"	9	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	3	1	"NA"	59.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	19.3	96.5	48.25	579	9.78040540540541	0.00978040540540541
+"122.3"	"180301_15.dx"	"OpenLab 1"	"2018-03-01 18:57:51+01:00"	1	"P1-B-9"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Valine"	6.701	-0.568	6.009	-0.646	-0.646	"Norvaline"	9	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	3	1	"NA"	59.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	-32.3	-161.5	-80.75	-969	-16.3682432432432	-0.0163682432432432
+"122.3"	"180301_15.dx"	"OpenLab 1"	"2018-03-01 18:57:51+01:00"	1	"P1-B-9"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Isoleucine"	7.726	-0.303	3.191	-0.644	-0.644	"Norvaline"	9	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	3	1	"NA"	59.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	-32.2	-161	-80.5	-966	-16.3175675675676	-0.0163175675675676
+"122.3"	"180301_15.dx"	"OpenLab 1"	"2018-03-01 18:57:51+01:00"	1	"P1-B-9"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Leucine"	7.822	-0.174	2.715	-0.952	-0.952	"Norvaline"	9	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	3	1	"NA"	59.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	-47.6	-238	-119	-1428	-24.1216216216216	-0.0241216216216216
+"122.3"	"180301_15.dx"	"OpenLab 1"	"2018-03-01 18:57:51+01:00"	1	"P1-B-9"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Phenylalanine"	7.909	-0.173	3.452	-1.22	-1.22	"Norvaline"	9	"Talinum triangulare"	"Leaf"	"CAM"	"EN"	"NA"	3	1	"NA"	59.2	"80% ethanol"	1200	100	50	10	50	"CAM
+EN"	-61	-305	-152.5	-1830	-30.9121621621622	-0.0309121621621622
+"19.1"	"180301_07.dx"	"OpenLab 1"	"2018-03-01 17:38:38+01:00"	1	"P1-B-1"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Serine"	2.011	0.255	44.969	10.022	10.022	"Norvaline"	1	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	1	1	"NA"	60.7	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	501.1	2505.5	1252.75	15033	247.660626029654	0.247660626029654
+"19.1"	"180301_07.dx"	"OpenLab 1"	"2018-03-01 17:38:38+01:00"	1	"P1-B-1"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Arginine + Glutamine"	2.074	0.217	143.799	37.692	37.692	"Norvaline"	1	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	1	1	"NA"	60.7	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	1884.6	9423	4711.5	56538	931.433278418451	0.931433278418451
+"19.1"	"180301_07.dx"	"OpenLab 1"	"2018-03-01 17:38:38+01:00"	1	"P1-B-1"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Glycine"	2.241	0.254	17.543	3.923	3.923	"Norvaline"	1	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	1	1	"NA"	60.7	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	196.15	980.75	490.375	5884.5	96.9439868204283	0.0969439868204283
+"19.1"	"180301_07.dx"	"OpenLab 1"	"2018-03-01 17:38:38+01:00"	1	"P1-B-1"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Aspartate"	2.391	0.2	246.121	69.775	69.775	"Norvaline"	1	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	1	1	"NA"	60.7	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	3488.75	17443.75	8721.875	104662.5	1724.2586490939	1.7242586490939
+"19.1"	"180301_07.dx"	"OpenLab 1"	"2018-03-01 17:38:38+01:00"	1	"P1-B-1"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Glutamate"	2.775	0.205	280.645	77.577	77.577	"Norvaline"	1	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	1	1	"NA"	60.7	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	3878.85	19394.25	9697.125	116365.5	1917.05930807249	1.91705930807249
+"19.1"	"180301_07.dx"	"OpenLab 1"	"2018-03-01 17:38:38+01:00"	1	"P1-B-1"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Threonine"	3.181	0.705	7.972	0.642	0.642	"Norvaline"	1	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	1	1	"NA"	60.7	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	32.1	160.5	80.25	963	15.8649093904448	0.0158649093904448
+"19.1"	"180301_07.dx"	"OpenLab 1"	"2018-03-01 17:38:38+01:00"	1	"P1-B-1"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Alanine"	3.596	0.23	71.743	17.753	17.753	"Norvaline"	1	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	1	1	"NA"	60.7	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	887.65	4438.25	2219.125	26629.5	438.706754530478	0.438706754530478
+"19.1"	"180301_07.dx"	"OpenLab 1"	"2018-03-01 17:38:38+01:00"	1	"P1-B-1"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Proline"	4.323	0.238	19.826	4.724	4.724	"Norvaline"	1	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	1	1	"NA"	60.7	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	236.2	1181	590.5	7086	116.73805601318	0.11673805601318
+"19.1"	"180301_07.dx"	"OpenLab 1"	"2018-03-01 17:38:38+01:00"	1	"P1-B-1"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Lysine"	6.078	0.309	5.516	1.013	1.013	"Norvaline"	1	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	1	1	"NA"	60.7	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	50.65	253.25	126.625	1519.5	25.0329489291598	0.0250329489291598
+"19.1"	"180301_07.dx"	"OpenLab 1"	"2018-03-01 17:38:38+01:00"	1	"P1-B-1"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Tyrosine"	6.267	-0.388	2.474	-0.362	-0.362	"Norvaline"	1	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	1	1	"NA"	60.7	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	-18.1	-90.5	-45.25	-543	-8.94563426688632	-0.00894563426688632
+"19.1"	"180301_07.dx"	"OpenLab 1"	"2018-03-01 17:38:38+01:00"	1	"P1-B-1"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Methionine"	6.393	-0.019	0.856	-2.576	-2.576	"Norvaline"	1	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	1	1	"NA"	60.7	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	-128.8	-644	-322	-3864	-63.6573311367381	-0.0636573311367381
+"19.1"	"180301_07.dx"	"OpenLab 1"	"2018-03-01 17:38:38+01:00"	1	"P1-B-1"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Valine"	6.703	0.33	27.794	4.789	4.789	"Norvaline"	1	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	1	1	"NA"	60.7	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	239.45	1197.25	598.625	7183.5	118.34431630972	0.11834431630972
+"19.1"	"180301_07.dx"	"OpenLab 1"	"2018-03-01 17:38:38+01:00"	1	"P1-B-1"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Isoleucine"	7.729	0.371	13.678	2.094	2.094	"Norvaline"	1	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	1	1	"NA"	60.7	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	104.7	523.5	261.75	3141	51.7462932454695	0.0517462932454695
+"19.1"	"180301_07.dx"	"OpenLab 1"	"2018-03-01 17:38:38+01:00"	1	"P1-B-1"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Leucine"	7.825	-0.097	2.045	-1.193	-1.193	"Norvaline"	1	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	1	1	"NA"	60.7	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	-59.65	-298.25	-149.125	-1789.5	-29.4810543657331	-0.0294810543657331
+"19.1"	"180301_07.dx"	"OpenLab 1"	"2018-03-01 17:38:38+01:00"	1	"P1-B-1"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Phenylalanine"	7.912	-0.119	2.966	-1.417	-1.417	"Norvaline"	1	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	1	1	"NA"	60.7	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	-70.85	-354.25	-177.125	-2125.5	-35.0164744645799	-0.0350164744645799
+"19.2"	"180301_08.dx"	"OpenLab 1"	"2018-03-01 17:48:33+01:00"	1	"P1-B-2"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Histidine"	1.421	0.103	0.161	0.093	0.093	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	4.65	23.25	11.625	139.5	3.66141732283465	0.00366141732283465
+"19.2"	"180301_08.dx"	"OpenLab 1"	"2018-03-01 17:48:33+01:00"	1	"P1-B-2"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Serine"	2.021	0.299	27.148	5.421	5.421	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	271.05	1355.25	677.625	8131.5	213.425196850394	0.213425196850394
+"19.2"	"180301_08.dx"	"OpenLab 1"	"2018-03-01 17:48:33+01:00"	1	"P1-B-2"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Arginine + Glutamine"	2.086	0.221	95.22	25.738	25.738	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	1286.9	6434.5	3217.25	38607	1013.30708661417	1.01330708661417
+"19.2"	"180301_08.dx"	"OpenLab 1"	"2018-03-01 17:48:33+01:00"	1	"P1-B-2"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Glycine"	2.25	0.326	8.725	1.596	1.596	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	79.8	399	199.5	2394	62.8346456692913	0.0628346456692914
+"19.2"	"180301_08.dx"	"OpenLab 1"	"2018-03-01 17:48:33+01:00"	1	"P1-B-2"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Aspartate"	2.4	0.204	150.103	43.952	43.952	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	2197.6	10988	5494	65928	1730.3937007874	1.7303937007874
+"19.2"	"180301_08.dx"	"OpenLab 1"	"2018-03-01 17:48:33+01:00"	1	"P1-B-2"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Glutamate"	2.783	0.208	174.053	49.95	49.95	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	2497.5	12487.5	6243.75	74925	1966.53543307087	1.96653543307087
+"19.2"	"180301_08.dx"	"OpenLab 1"	"2018-03-01 17:48:33+01:00"	1	"P1-B-2"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Threonine"	3.187	-2.525	4.857	-0.115	-0.115	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	-5.75	-28.75	-14.375	-172.5	-4.52755905511811	-0.00452755905511811
+"19.2"	"180301_08.dx"	"OpenLab 1"	"2018-03-01 17:48:33+01:00"	1	"P1-B-2"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Alanine"	3.601	0.246	35.237	8.55	8.55	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	427.5	2137.5	1068.75	12825	336.614173228346	0.336614173228346
+"19.2"	"180301_08.dx"	"OpenLab 1"	"2018-03-01 17:48:33+01:00"	1	"P1-B-2"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Proline"	4.327	0.283	10.725	2.264	2.264	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	113.2	566	283	3396	89.1338582677165	0.0891338582677165
+"19.2"	"180301_08.dx"	"OpenLab 1"	"2018-03-01 17:48:33+01:00"	1	"P1-B-2"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Lysine"	6.078	0.534	2.58	0.288	0.288	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	14.4	72	36	432	11.3385826771654	0.0113385826771654
+"19.2"	"180301_08.dx"	"OpenLab 1"	"2018-03-01 17:48:33+01:00"	1	"P1-B-2"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Tyrosine"	6.264	-0.115	1.117	-0.581	-0.581	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	-29.05	-145.25	-72.625	-871.5	-22.8740157480315	-0.0228740157480315
+"19.2"	"180301_08.dx"	"OpenLab 1"	"2018-03-01 17:48:33+01:00"	1	"P1-B-2"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Methionine"	6.392	-0.006	0.295	-2.719	-2.719	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	-135.95	-679.75	-339.875	-4078.5	-107.047244094488	-0.107047244094488
+"19.2"	"180301_08.dx"	"OpenLab 1"	"2018-03-01 17:48:33+01:00"	1	"P1-B-2"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Valine"	6.702	0.695	12.599	1.082	1.082	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	54.1	270.5	135.25	1623	42.5984251968504	0.0425984251968504
+"19.2"	"180301_08.dx"	"OpenLab 1"	"2018-03-01 17:48:33+01:00"	1	"P1-B-2"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Isoleucine"	7.728	0.715	7.909	0.66	0.66	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	33	165	82.5	990	25.9842519685039	0.0259842519685039
+"19.2"	"180301_08.dx"	"OpenLab 1"	"2018-03-01 17:48:33+01:00"	1	"P1-B-2"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Leucine"	7.824	-0.056	1.304	-1.379	-1.379	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	-68.95	-344.75	-172.375	-2068.5	-54.2913385826772	-0.0542913385826772
+"19.2"	"180301_08.dx"	"OpenLab 1"	"2018-03-01 17:48:33+01:00"	1	"P1-B-2"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Phenylalanine"	7.913	-0.054	1.593	-1.758	-1.758	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	-87.9	-439.5	-219.75	-2637	-69.2125984251968	-0.0692125984251969
+"19.2"	"180301_09.dx"	"OpenLab 1"	"2018-03-01 17:58:28+01:00"	1	"P1-B-3"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Histidine"	1.43	0.103	0.658	0.381	0.381	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	19.05	95.25	47.625	571.5	15	0.015
+"19.2"	"180301_09.dx"	"OpenLab 1"	"2018-03-01 17:58:28+01:00"	1	"P1-B-3"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Serine"	2.03	0.416	16.979	2.443	2.443	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	122.15	610.75	305.375	3664.5	96.1811023622047	0.0961811023622047
+"19.2"	"180301_09.dx"	"OpenLab 1"	"2018-03-01 17:58:28+01:00"	1	"P1-B-3"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Arginine + Glutamine"	2.097	0.224	78.25	20.927	20.927	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	1046.35	5231.75	2615.875	31390.5	823.897637795276	0.823897637795275
+"19.2"	"180301_09.dx"	"OpenLab 1"	"2018-03-01 17:58:28+01:00"	1	"P1-B-3"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Glycine"	2.259	0.303	9.958	1.965	1.965	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	98.25	491.25	245.625	2947.5	77.3622047244095	0.0773622047244095
+"19.2"	"180301_09.dx"	"OpenLab 1"	"2018-03-01 17:58:28+01:00"	1	"P1-B-3"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Aspartate"	2.406	0.202	195.325	58.029	58.029	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	2901.45	14507.25	7253.625	87043.5	2284.6062992126	2.2846062992126
+"19.2"	"180301_09.dx"	"OpenLab 1"	"2018-03-01 17:58:28+01:00"	1	"P1-B-3"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Glutamate"	2.786	0.207	209.058	60.544	60.544	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	3027.2	15136	7568	90816	2383.62204724409	2.38362204724409
+"19.2"	"180301_09.dx"	"OpenLab 1"	"2018-03-01 17:58:28+01:00"	1	"P1-B-3"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Threonine"	3.191	0.958	6.776	0.424	0.424	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	21.2	106	53	636	16.6929133858268	0.0166929133858268
+"19.2"	"180301_09.dx"	"OpenLab 1"	"2018-03-01 17:58:28+01:00"	1	"P1-B-3"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Alanine"	3.603	0.236	49.093	12.454	12.454	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	622.7	3113.5	1556.75	18681	490.314960629921	0.490314960629921
+"19.2"	"180301_09.dx"	"OpenLab 1"	"2018-03-01 17:58:28+01:00"	1	"P1-B-3"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Proline"	4.326	0.246	16.473	4.017	4.017	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	200.85	1004.25	502.125	6025.5	158.149606299213	0.158149606299213
+"19.2"	"180301_09.dx"	"OpenLab 1"	"2018-03-01 17:58:28+01:00"	1	"P1-B-3"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Lysine"	6.078	0.343	4.216	0.736	0.736	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	36.8	184	92	1104	28.9763779527559	0.0289763779527559
+"19.2"	"180301_09.dx"	"OpenLab 1"	"2018-03-01 17:58:28+01:00"	1	"P1-B-3"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Tyrosine"	6.265	-0.409	2.402	-0.352	-0.352	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	-17.6	-88	-44	-528	-13.8582677165354	-0.0138582677165354
+"19.2"	"180301_09.dx"	"OpenLab 1"	"2018-03-01 17:58:28+01:00"	1	"P1-B-3"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Methionine"	6.391	-0.009	0.394	-2.691	-2.691	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	-134.55	-672.75	-336.375	-4036.5	-105.944881889764	-0.105944881889764
+"19.2"	"180301_09.dx"	"OpenLab 1"	"2018-03-01 17:58:28+01:00"	1	"P1-B-3"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Valine"	6.701	0.355	22.934	3.868	3.868	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	193.4	967	483.5	5802	152.283464566929	0.152283464566929
+"19.2"	"180301_09.dx"	"OpenLab 1"	"2018-03-01 17:58:28+01:00"	1	"P1-B-3"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Isoleucine"	7.726	0.416	11.339	1.633	1.633	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	81.65	408.25	204.125	2449.5	64.2913385826772	0.0642913385826772
+"19.2"	"180301_09.dx"	"OpenLab 1"	"2018-03-01 17:58:28+01:00"	1	"P1-B-3"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Leucine"	7.822	-0.117	2.186	-1.121	-1.121	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	-56.05	-280.25	-140.125	-1681.5	-44.1338582677165	-0.0441338582677165
+"19.2"	"180301_09.dx"	"OpenLab 1"	"2018-03-01 17:58:28+01:00"	1	"P1-B-3"	"171214_ACCQ.amx"	"Sample"	"*2018-04-10_Amino_Acids_ISTD_NorVal.pmx"	"Manual Integration"	"DAD1F,Sig=260.0,16.0  Ref=324.0,8.0"	"Phenylalanine"	7.91	-0.109	2.662	-1.459	-1.459	"Norvaline"	2	"Talinum triangulare"	"Leaf"	"C3"	"ED"	"NA"	2	1	"NA"	38.1	"80% ethanol"	1200	100	50	10	50	"C3
+ED"	-72.95	-364.75	-182.375	-2188.5	-57.4409448818898	-0.0574409448818898
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