Step 1: Read files into dataframes
standardSpectra <- read.table('D3_0001_D3_25-07-18_15-57_0001.txt',header=FALSE,skip=8)
sampleSpectra <- read.table('D4_0001_D4_25-07-18_15-58_0001.txt',header=FALSE,skip=8)
#Remove outlier in next Row
#standardSpectra <-standardSpectra {-1,}
#sampleSpectra <-sampleSpectra {-1,}
#names(standardSpectra) <- c('m_2','intesnsity')
#names(sampleSpectra) <- c (('m_2','intesnsity')
library (tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.4 ✔ readr 2.1.5
## ✔ forcats 1.0.0 ✔ stringr 1.5.1
## ✔ ggplot2 3.5.2 ✔ tibble 3.3.0
## ✔ lubridate 1.9.4 ✔ tidyr 1.3.1
## ✔ purrr 1.1.0
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
sampleSpectra$type <-'sample'
standardSpectra$type <- 'standard'
ms_data <- rbind(sampleSpectra,standardSpectra)
names(ms_data)<-c('mz','intensity','type')
ggplot(ms_data, aes(x = mz,y=intensity))+
geom_col(aes(colour = type,fill=type))+
scale_color_manual(values=c("#ffc868","#e5216b"))+
scale_fill_manual(values=c("#ffc868","#e5216b"))+
xlab("m/z Ratio") + ylab("Millivolts")+
theme(legend.position="right")
matchSpectra <- merge(standardSpectra,sampleSpectra, by="V1")
write.csv(matchSpectra,"matchSpectra.csv")
#facet wrap
ggplot(ms_data, aes(x = mz,y=intensity))+
geom_col(aes(colour = type ,fill=type))+
scale_color_manual(values=c("#ffc868","#e5216b"))+
scale_fill_manual(values=c("#ffc868","#e5216b"))+
xlab("m/z ratio") + ylab("Millivolts")+
facet_wrap(~type,nrow=2)