combineSpectra: Combine Spectra

In MSnbase: Base Functions and Classes for Mass Spectrometry and Proteomics

Description

combineSpectra combines spectra in a MSnExp, OnDiskMSnExp or MSpectra object applying the summarization function fun to sets of spectra defined by a factor (fcol parameter). The resulting combined spectrum for each set contains metadata information (present in mcols and all spectrum information other than mz and intensity) from the first spectrum in each set.

Combining of spectra for MSnExp or OnDiskMSnExp objects is performed by default for each file separately, combining of spectra across files is thus not possible. See examples for details.

Usage

## S4 method for signature 'MSnExp'
combineSpectra(
  object,
  fcol = "fileIdx",
  method = meanMzInts,
  ...,
  BPPARAM = bpparam()
)

## S4 method for signature 'MSpectra'
combineSpectra(object, fcol, method = meanMzInts, fun, ...)

Arguments

object	A MSnExp or MSpectra
fcol	For MSpectra objects: mcols column name to be used to define the sets of spectra to be combined. If missing, all spectra are considered to be one set. For MSnExp/OnDiskMSnExp objects: column in fData(object) defining which spectra to combine. See examples below for more details.
method	function to be used to combine the spectra by fcol. Has to be a function that takes a list of spectra as input and returns a single Spectrum. See meanMzInts() for details.
...	additional arguments for fun.
BPPARAM	For MSnExp/OnDiskMSnExp objects: parallel processing setup to perform per-file parallel spectra combining. See bpparam() for more details.
fun	Deprecated use method instead.

Value

A MSpectra or MSnExp object with combined spectra. Metadata (mcols) and all spectrum attributes other than mz and intensity are taken from the first Spectrum in each set.

Author(s)

Johannes Rainer, Laurent Gatto

See Also

meanMzInts() for a function to combine spectra.

Examples

set.seed(123)
mzs <- seq(1, 20, 0.1)
ints1 <- abs(rnorm(length(mzs), 10))
ints1[11:20] <- c(15, 30, 90, 200, 500, 300, 100, 70, 40, 20) # add peak
ints2 <- abs(rnorm(length(mzs), 10))
ints2[11:20] <- c(15, 30, 60, 120, 300, 200, 90, 60, 30, 23)
ints3 <- abs(rnorm(length(mzs), 10))
ints3[11:20] <- c(13, 20, 50, 100, 200, 100, 80, 40, 30, 20)

## Create the spectra.
sp1 <- new("Spectrum1", mz = mzs + rnorm(length(mzs), sd = 0.01),
    intensity = ints1, rt = 1)
sp2 <- new("Spectrum1", mz = mzs + rnorm(length(mzs), sd = 0.01),
    intensity = ints2, rt = 2)
sp3 <- new("Spectrum1", mz = mzs + rnorm(length(mzs), sd = 0.009),
    intensity = ints3, rt = 3)

spctra <- MSpectra(sp1, sp2, sp3,
    elementMetadata = DataFrame(idx = 1:3, group = c("b", "a", "a")))

## Combine the spectra reporting the maximym signal
res <- combineSpectra(spctra, mzd = 0.05, intensityFun = max)
res

## All values other than m/z and intensity are kept from the first spectrum
rtime(res)

## Plot the individual and the merged spectrum
par(mfrow = c(2, 1), mar = c(4.3, 4, 1, 1))
plot(mz(sp1), intensity(sp1), xlim = range(mzs[5:25]), type = "h", col = "red")
points(mz(sp2), intensity(sp2), type = "h", col = "green")
points(mz(sp3), intensity(sp3), type = "h", col = "blue")
plot(mz(res[[1]]), intensity(res[[1]]), type = "h",
    col = "black", xlim = range(mzs[5:25]))

## Combine spectra in two sets.
res <- combineSpectra(spctra, fcol = "group", mzd = 0.05)
res

rtime(res)

## Plot the individual and the merged spectra
par(mfrow = c(3, 1), mar = c(4.3, 4, 1, 1))
plot(mz(sp1), intensity(sp1), xlim = range(mzs[5:25]), type = "h", col = "red")
points(mz(sp2), intensity(sp2), type = "h", col = "green")
points(mz(sp3), intensity(sp3), type = "h", col = "blue")
plot(mz(res[[1]]), intensity(res[[1]]), xlim = range(mzs[5:25]), type = "h",
    col = "black")
plot(mz(res[[2]]), intensity(res[[2]]), xlim = range(mzs[5:25]), type = "h",
    col = "black")

## Combining spectra of an MSnExp/OnDiskMSnExp objects
## Reading data from 2 mzML files
sciex <- readMSData(dir(system.file("sciex", package = "msdata"),
    full.names = TRUE), mode = "onDisk")

## Filter the file to a retention time range from 2 to 20 seconds (to reduce
## execution time of the example)
sciex <- filterRt(sciex, rt = c(2, 20))
table(fromFile(sciex))

## We have thus 64 spectra per file.

## In the example below we combine spectra measured in one second to a
## single spectrum. We thus first define the grouping variable and add that
## to the `fData` of the object. For combining, we use the
## `consensusSpectrum` function that combines the spectra keeping only peaks
## that were found in 50% of the spectra; by defining `mzd = 0.01` all peaks
## within an m/z of 0.01 are evaluated for combining.
seconds <- round(rtime(sciex))
head(seconds)
fData(sciex)$second <- seconds

res <- combineSpectra(sciex, fcol = "second", mzd = 0.01, minProp = 0.1,
    method = consensusSpectrum)
table(fromFile(res))

## The data was reduced to 19 spectra for each file.

MSnbase documentation built on Jan. 23, 2021, 2 a.m.