Plot MS Spectra

Script to read in and plot MS Spectra from Shiadzu MALDI-TOF

#Step 1: Read files into dataframes

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   3.5.1     ✔ tibble    3.2.1
## ✔ lubridate 1.9.3     ✔ tidyr     1.3.1
## ✔ purrr     1.0.2     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
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## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

standardSpectra = read.table('A3_0001_A3_25-07-18_16-03_0001.txt', header=FALSE, skip=8)
sampleSpectra = read.table('A4_0001_A4_25-07-18_16-04_0001.txt', header=FALSE, skip=8)

#Step 2: Remove outlier in first row and add column names

standardSpectra = standardSpectra[-1,]
standardSpectra = standardSpectra[standardSpectra$V1<900,]
sampleSpectra = sampleSpectra[-1,]
sampleSpectra = sampleSpectra[sampleSpectra$V1<900,]
names(standardSpectra) = c('m_z','intensity')
names(sampleSpectra) = c('m_z','intensity')

#Step 3: Tidy data

sampleSpectra$type = 'Sample'
standardSpectra$type = 'Standard'
ms_data = rbind(sampleSpectra,standardSpectra)
names(ms_data) = c('m_z','intensity','type')

#Step 4: Visualize data using ggplot

ggplot(
  ms_data, aes(x = m_z,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("Intensity (mV)")+
  theme(legend.position="right")

#Step 5: Isolate sample type visuals using facet wrap

ggplot(
  ms_data, aes(x = m_z,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("Intensity (mV)")+
  facet_wrap(~type,nrow=2)