combinePeaks {Spectra} | R Documentation

## Combine peaks with similar m/z across spectra

### Description

`combinePeaks` aggregates provided peak matrices into a single peak matrix. Peaks are grouped by their m/z values with the `group()` function from the `MsCoreUtils` package. In brief, all peaks in all provided spectra are first ordered by their m/z and consecutively grouped into one group if the (pairwise) difference between them is smaller than specified with parameter `tolerance` and `ppm` (see `group()` for grouping details and examples).

The m/z and intensity values for the resulting peak matrix are calculated using the `mzFun` and `intensityFun` on the grouped m/z and intensity values.

The function supports also different strategies for peak combinations which can be specified with the `peaks` parameter:

- `peaks = "union"` (default): report all peaks from all input spectra.

- `peaks = "intersect"`: keep only peaks in the resulting peak matrix that are present in `>= minProp` proportion of input spectra. This would generate a consensus or representative spectra from a set of e.g. fragment spectra measured from the same precursor ion.

As a special case it is possible to report only peaks in the resulting matrix from peak groups that contain a peak from one of the input spectra, which can be specified with parameter `main`. Thus, if e.g. `main = 2` is specified, only (grouped) peaks that have a peak in the second input matrix are returned.

Setting `timeDomain` to `TRUE` causes grouping to be performed on the square root of the m/z values (assuming a TOF instrument was used to create the data).

### Usage

    combinePeaks(
      x,
      intensityFun = base::mean,
      mzFun = base::mean,
      weighted = FALSE,
      tolerance = 0,
      ppm = 0,
      timeDomain = FALSE,
      peaks = c("union", "intersect"),
      main = integer(),
      minProp = 0.5,
      ...
    )

### Arguments

`x` | `list` of peak matrices.
`intensityFun` | `function` to be used to combine intensity values for matching peaks. By default the mean intensity value is returned.
`mzFun` | `function` to be used to combine m/z values for matching peaks. By default the mean m/z value is returned.
`weighted` | `logical(1)` defining whether m/z values for matching peaks should be calculated by an intensity-weighted average of the individuak m/z values. This overrides parameter `mzFun`.
`tolerance` | `numeric(1)` defining the (absolute) maximal accepted difference between mass peaks to group them into the same final peak.
`ppm` | `numeric(1)` defining the m/z-relative maximal accepted difference between mass peaks (expressed in parts-per-million) to group them into the same final peak.
`timeDomain` | `logical(1)` whether grouping of mass peaks is performed on the m/z values (`timeDomain = FALSE`) or on `sqrt(mz)` (`timeDomain = TRUE`).
`peaks` | `character(1)` specifying how peaks should be combined. Can be either `"peaks = "union"` (default) or `peaks = "intersect"`. See function description for details.
`main` | optional `integer(1)` to force the resulting peak list to contain only peaks that are present in the specified input spectrum. See description for details.
`minProp` | `numeric(1)` for 'peaks = "intersect": the minimal required proportion of input spectra (peak matrices) a mass peak has to be present to be included in the consensus peak matrix.
`...` | additional parameters to the `mzFun` and `intensityFun` functions.

### Details

For general merging of spectra, the `tolerance` and/or `ppm` should be manually specified based on the precision of the MS instrument. Peaks from spectra with a difference in their m/z being smaller than `tolerance` or smaller than `ppm` of their m/z are grouped into the same final peak.

Some details for the combination of consecutive spectra of an LC-MS run:

The m/z values of the same ion in consecutive scans (spectra) of a LC-MS run will not be identical. Assuming that this random variation is much smaller than the resolution of the MS instrument (i.e. the difference between m/z values within each single spectrum), m/z value groups are defined across the spectra and those containing m/z values of the `main` spectrum are retained. Intensities and m/z values falling within each of these m/z groups are aggregated using the `intensityFun` and `mzFun`, respectively. It is highly likely that all QTOF profile data is collected with a timing circuit that collects data points with regular intervals of time that are then later converted into m/z values based on the relationship `t = k * sqrt(m/z)`. The m/z scale is thus non-linear and the m/z scattering (which is in fact caused by small variations in the time circuit) will thus be different in the lower and upper m/z scale. m/z-intensity pairs from consecutive scans to be combined are therefore defined by default on the square root of the m/z values. With `timeDomain = FALSE`, the actual m/z values will be used.

### Value

Peaks `matrix` with m/z and intensity values representing the aggregated values across the provided peak matrices.

### Author(s)

Johannes Rainer

### 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 peaks matrices
    p1 <- cbind(mz = mzs + rnorm(length(mzs), sd = 0.01),
        intensity = ints1)
    p2 <- cbind(mz = mzs + rnorm(length(mzs), sd = 0.01),
        intensity = ints2)
    p3 <- cbind(mz = mzs + rnorm(length(mzs), sd = 0.009),
        intensity = ints3)

    ## Combine the spectra. With `tolerance = 0` and `ppm = 0` only peaks with
    ## **identical** m/z are combined. The result will be a single spectrum
    ## containing the *union* of mass peaks from the individual input spectra.
    p <- combinePeaks(list(p1, p2, p3))

    ## Plot the spectra before and after combining
    par(mfrow = c(2, 1), mar = c(4.3, 4, 1, 1))
    plot(p1[, 1], p1[, 2], xlim = range(mzs[5:25]), type = "h", col = "red")
    points(p2[, 1], p2[, 2], type = "h", col = "green")
    points(p3[, 1], p3[, 2], type = "h", col = "blue")

    plot(p[, 1], p[, 2], xlim = range(mzs[5:25]), type = "h",
        col = "black")
    ## The peaks were not merged, because their m/z differs too much.

    ## Combine spectra with `tolerance = 0.05`. This will merge all triplets.
    p <- combinePeaks(list(p1, p2, p3), tolerance = 0.05)

    ## Plot the spectra before and after combining
    par(mfrow = c(2, 1), mar = c(4.3, 4, 1, 1))
    plot(p1[, 1], p1[, 2], xlim = range(mzs[5:25]), type = "h", col = "red")
    points(p2[, 1], p2[, 2], type = "h", col = "green")
    points(p3[, 1], p3[, 2], type = "h", col = "blue")

    plot(p[, 1], p[, 2], xlim = range(mzs[5:25]), type = "h",
        col = "black")

    ## With `intensityFun = max` the maximal intensity per peak is reported.
    p <- combinePeaks(list(p1, p2, p3), tolerance = 0.05,
        intensityFun = max)

    ## Create *consensus*/representative spectrum from a set of spectra

    p1 <- cbind(mz = c(12, 45, 64, 70), intensity = c(10, 20, 30, 40))
    p2 <- cbind(mz = c(17, 45.1, 63.9, 70.2), intensity = c(11, 21, 31, 41))
    p3 <- cbind(mz = c(12.1, 44.9, 63), intensity = c(12, 22, 32))

    ## No mass peaks identical thus consensus peaks are empty
    combinePeaks(list(p1, p2, p3), peaks = "intersect")

    ## Reducing the minProp to 0.2. The consensus spectrum will contain all
    ## peaks
    combinePeaks(list(p1, p2, p3), peaks = "intersect", minProp = 0.2)

    ## With a tolerance of 0.1 mass peaks can be matched across spectra
    combinePeaks(list(p1, p2, p3), peaks = "intersect", tolerance = 0.1)

    ## Report the minimal m/z and intensity
    combinePeaks(list(p1, p2, p3), peaks = "intersect", tolerance = 0.1,
        intensityFun = min, mzFun = min)

[Package Spectra version 1.2.2 Index]