consensusSpectrum: Combine spectra to a consensus spectrum
In MSnbase: Base Functions and Classes for Mass Spectrometry and Proteomics

Description Usage Arguments Details Author(s) See Also Examples

consensusSpectrum takes a list of spectra and combines them to a consensus spectrum containing mass peaks that are present in a user definable proportion of spectra.

consensusSpectrum(
  x,
  mzd = 0,
  minProp = 0.5,
  intensityFun = stats::median,
  mzFun = stats::median,
  ppm = 0,
  weighted = FALSE,
  ...
)

`x`	`list` of Spectrum objects (either Spectrum1 or Spectrum2).
`mzd`	`numeric(1)` defining the maximal m/z difference below which mass peaks are grouped in to the same final mass peak (see details for more information). Defaults to `0`; see `meanMzInts()` for estimating this value from the distribution of differences of m/z values from the spectra. See also parameter `ppm` below for the definition of an m/z dependent peak grouping.
`minProp`	`numeric(1)` defining the minimal proportion of spectra in which a mass peak has to be present in order to include it in the final consensus spectrum. Should be a number between 0 and 1 (present in all spectra).
`intensityFun`	`function` (or name of a function) to be used to define the intensity of the aggregated peak. By default the median signal for a mass peak is reported.
`mzFun`	`function` (or name of a function) to be used to define the intensity of the aggregated peak. By default the median m/z is reported. Note that setting `weighted = TRUE` overrides this parameter.
`ppm`	`numeric(1)` allowing to perform a m/z dependent grouping of mass peaks. See details for more information.
`weighted`	`logical(1)` whether the m/z of the aggregated peak represents the intensity-weighted average of the m/z values of all peaks of the peak group. If `FALSE` (the default), the m/z of the peak is calculated with `mzFun`.
`...`	additional arguments to be passed to `intensityFun`.

Peaks from spectra with a difference of their m/z being smaller than mzd are grouped into the same final mass peak with their intensities being aggregated with intensityFun. Alternatively (or in addition) it is possible to perform an m/z dependent grouping of mass peaks with parameter ppm: mass peaks from different spectra with a difference in their m/z smaller than ppm of their m/z are grouped into the same final peak.

The m/z of the final mass peaks is calculated with mzFun. By setting weighted = TRUE the parameter mzFun is ignored and an intensity-weighted mean of the m/z values from the individual mass peaks is returned as the peak's m/z.

Johannes Rainer

Other spectra combination functions: meanMzInts()

library(MSnbase)
## Create 3 example spectra.
sp1 <- new("Spectrum2", rt = 1, precursorMz = 1.41,
    mz = c(1.2, 1.5, 1.8, 3.6, 4.9, 5.0, 7.8, 8.4),
    intensity = c(10, 3, 140, 14, 299, 12, 49, 20))
sp2 <- new("Spectrum2", rt = 1.1, precursorMz = 1.4102,
    mz = c(1.4, 1.81, 2.4, 4.91, 6.0, 7.2, 9),
    intensity = c(3, 184, 8, 156, 12, 23, 10))
sp3 <- new("Spectrum2", rt = 1.2, precursorMz = 1.409,
    mz = c(1, 1.82, 2.2, 3, 7.0, 8),
    intensity = c(8, 210, 7, 101, 17, 8))
spl <- MSpectra(sp1, sp2, sp3)

## Plot the spectra, each in a different color
par(mfrow = c(2, 1), mar = c(4.3, 4, 1, 1))
plot(mz(sp1), intensity(sp1), type = "h", col = "#ff000080", lwd = 2,
    xlab = "m/z", ylab = "intensity", xlim = range(mz(spl)),
    ylim = range(intensity(spl)))
points(mz(sp2), intensity(sp2), type = "h", col = "#00ff0080", lwd = 2)
points(mz(sp3), intensity(sp3), type = "h", col = "#0000ff80", lwd = 2)

cons <- consensusSpectrum(spl, mzd = 0.02, minProp = 2/3)

## Peaks of the consensus spectrum
mz(cons)
intensity(cons)

## Other Spectrum data is taken from the first Spectrum in the list
rtime(cons)
precursorMz(cons)

plot(mz(cons), intensity(cons), type = "h", xlab = "m/z", ylab = "intensity",
    xlim = range(mz(spl)), ylim = range(intensity(spl)), lwd = 2)