In ethanbass/chromConverter: Chromatographic File Converter

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

library(chromConverter)
library(ggplot2)
library(data.table)

MS chromatograms are returned by default in long format with three columns: retention time, m/z, and intensity.

As an example, we can load the 'Varian' SMS chromatogram included in the chromConverterExtraTests package.

# download example file from the web
path_sms <- tempfile(fileext = ".sms")
download.file("https://raw.github.com/ethanbass/chromConverterExtraTests/master/inst/STRD15.SMS", destfile = path_sms)

dat <- read_chroms(path_sms, format_in = "varian_sms", format_out = "data.frame")

Plot TIC and mass spectra use base R syntax

x <- dat[[1]]$MS1

# derive TIC using aggregate
tic <- aggregate(intensity ~ rt, data = x, FUN = sum)

# plot TIC
matplot(tic$rt, tic$intensity, type = 'l',
        ylab = "Total intensity", xlab = "Time (min)")

Here is a simple plot function you could use to plot mass spectra in base R:

plot_spec <- function(spec, lab_int=0.2, digits=1){
  plot(spec, type = "h", xlab = "m/z", ylab = "Intensity")
  lab.idx <- which(spec$intensity > lab_int * max(spec$intensity))
  text(spec$mz[lab.idx], spec$intensity[lab.idx], round(spec$mz[lab.idx], 
                    digits), offset = 0.25, pos = 3, cex = 0.5)
}

You can extract mass spectra by filtering on time, e.g., to get the mass spectrum of the first scan, you could do:

times <- unique(x$rt)
spec <- x[x$rt == times[100], -1]
plot_spec(spec)

Plot TIC and mass spectra using dplyr syntax

Plot TIC with dplyr:

tic <- x |> dplyr::group_by(rt) |> dplyr::summarize_at("intensity", sum)

plot(intensity ~ rt, data=tic, type = 'l',
        ylab = "Total intensity", xlab = "Time (min)")

Plot spectrum with dplyr:

dplyr::filter(x, rt == 7.26355) |> 
  dplyr::select(mz, intensity) |> 
  plot_spec()

Plot TIC and mass spectra using data.table syntax

Convert to data.table:

x <- data.table::as.data.table(x)

chromConverter can also return chromatograms in data.table format directly:

dat <- read_chroms(path_sms, format_in = "varian_sms", format_out = "data.table")

Extract the total ion chromatogram:

tic <- x[, .(intensity = sum(intensity)), by = rt]
matplot(tic$rt, tic$intensity, type = 'l',
        ylab = "Total intensity", xlab = "Time (min)")

Extract the base ion chromatogram:

bpc <- x[, .(intensity = max(intensity)), by = rt]
matplot(bpc$rt, bpc$intensity, type = 'l',
        ylab = "Base ion chromatogram", xlab = "Time (min)")

To obtain a mass spectrum we just filter by retention time as before:

plot_spec(x[rt == 7.26355, c('mz','intensity')])

Plot TIC and mass spectra using ggplot

library(ggplot2)
ggplot(data = tic, aes(x=rt, y=intensity)) + 
  geom_line() + 
  xlab("Retention time (min)") +
  ylab("Intensity")

Plot mass spectrum with ggplot:

lab_int <- 0.2
digits <- 1
dplyr::filter(x, rt == 7.26355) |> 
  dplyr::select(mz, intensity) |> 
  ggplot(aes(x = mz, y = intensity)) +
  geom_segment(aes(xend = mz, yend = 0), linewidth = 0.5) +
  geom_text(data = subset(spec, intensity > lab_int * max(intensity)),
            aes(label = round(mz, digits)),
            vjust = -0.5, size = 2) +
  labs(x = "m/z", y = "Intensity") +
  theme_minimal()