compareSpectra() compares each spectrum in x with each spectrum in y
using the function provided with FUN (defaults to
MsCoreUtils::ndotproduct()). If y is missing, each spectrum in x is
compared with each other spectrum in x.
The matching/mapping of peaks between the compared spectra is done with the
MAPFUN function. The default joinPeaks() matches peaks of both spectra
and allows to keep all peaks from the first spectrum (type = "left"),
from the second (type = "right"), from both (type = "outer") and to
keep only matching peaks (type = "inner"); see joinPeaks() for more
information and examples). The MAPFUN function should have parameters
x, y, xPrecursorMz and yPrecursorMz as these values are passed to
the function.
In addition to joinPeaks() also joinPeaksGnps() is supported for
GNPS-like similarity score calculations. Note that joinPeaksGnps() should
only be used in combination with FUN = MsCoreUtils::gnps
(see joinPeaksGnps() for more information and details). Use
MAPFUN = joinPeaksNone to disable internal peak matching/mapping if a
similarity scoring function is used that performs the matching internally.
FUN is supposed to be a function to compare intensities of (matched)
peaks of the two spectra that are compared. The function needs to take two
matrices with columns "mz" and "intensity" as input and is supposed
to return a single numeric as result. In addition to the two peak matrices
the spectra's precursor m/z values are passed to the function as parameters
xPrecursorMz (precursor m/z of the x peak matrix) and yPrecursorMz
(precursor m/z of the y peak matrix). Additional parameters to functions
FUN and MAPFUN can be passed with .... Parameters ppm and
tolerance are passed to both MAPFUN and FUN.
The function returns a matrix with the results of FUN for each
comparison, number of rows equal to length(x) and number of columns
equal length(y) (i.e. element in row 2 and column 3 is the result from
the comparison of x[2] with y[3]). If SIMPLIFY = TRUE the matrix
is simplified to a numeric if length of x or y is one. See also
the vignette for additional examples, such as using spectral entropy
similarity in the scoring.
Usage
# S4 method for class 'Spectra,Spectra'
compareSpectra(
x,
y,
MAPFUN = joinPeaks,
tolerance = 0,
ppm = 20,
FUN = ndotproduct,
...,
SIMPLIFY = TRUE
)
# S4 method for class 'Spectra,missing'
compareSpectra(
x,
y = NULL,
MAPFUN = joinPeaks,
tolerance = 0,
ppm = 20,
FUN = ndotproduct,
...,
SIMPLIFY = TRUE
)Arguments
- x
A
Spectraobject.- y
A
Spectraobject.- MAPFUN
For
compareSpectra(): function to map/match peaks between the two compared spectra. SeejoinPeaks()for more information and possible functions. Defaults tojoinPeaks().- tolerance
numeric(1)allowing to define a constant maximal accepted difference between m/z values for peaks to be matched. This parameter is directly passed toMAPFUN.- ppm
numeric(1)defining a relative, m/z-dependent, maximal accepted difference between m/z values for peaks to be matched. This parameter is directly passed toMAPFUN.- FUN
function to compare intensities of peaks between two spectra. Defaults to
MsCoreUtils::ndotproduct().- ...
Additional arguments passed to the internal functions.
- SIMPLIFY
logical(1)defining whether the result matrix should be simplified to anumericif possible (i.e. if eitherxoryis of length 1).
Examples
## Load a `Spectra` object with LC-MS/MS data.
fl <- system.file("TripleTOF-SWATH", "PestMix1_DDA.mzML",
package = "msdata")
sps_dda <- Spectra(fl)
sps_dda
#> MSn data (Spectra) with 7602 spectra in a MsBackendMzR backend:
#> msLevel rtime scanIndex
#> <integer> <numeric> <integer>
#> 1 1 0.231 1
#> 2 1 0.351 2
#> 3 1 0.471 3
#> 4 1 0.591 4
#> 5 1 0.711 5
#> ... ... ... ...
#> 7598 1 899.491 7598
#> 7599 1 899.613 7599
#> 7600 1 899.747 7600
#> 7601 1 899.872 7601
#> 7602 1 899.993 7602
#> ... 33 more variables/columns.
#>
#> file(s):
#> PestMix1_DDA.mzML
## Restrict to MS2 (fragment) spectra:
sps_ms2 <- filterMsLevel(sps_dda, msLevel = 2L)
## Compare spectra: comparing spectra 2 and 3 against spectra 10:20 using
## the normalized dotproduct method.
res <- compareSpectra(sps_ms2[2:3], sps_ms2[10:20])
## first row contains comparisons of spectrum 2 with spectra 10 to 20 and
## the second row comparisons of spectrum 3 with spectra 10 to 20
res
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11]
#> [1,] 0 0 0.05181365 0 0 0 0 0 0 0 0
#> [2,] 0 0 0.20331585 0 0 0 0 0 0 0 0
## We next calculate the pairwise similarity for the first 10 spectra
compareSpectra(sps_ms2[1:10])
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
#> [1,] 1.00000000 0.03261724 0.12798950 0 0 0 0 NaN 0 0
#> [2,] 0.03261724 1.00000000 0.07398183 0 0 0 0 NaN 0 0
#> [3,] 0.12798950 0.07398183 1.00000000 0 0 0 0 NaN 0 0
#> [4,] 0.00000000 0.00000000 0.00000000 1 0 0 0 NaN 0 0
#> [5,] 0.00000000 0.00000000 0.00000000 0 1 0 0 NaN 0 0
#> [6,] 0.00000000 0.00000000 0.00000000 0 0 1 0 NaN 0 0
#> [7,] 0.00000000 0.00000000 0.00000000 0 0 0 1 NaN 0 0
#> [8,] NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
#> [9,] 0.00000000 0.00000000 0.00000000 0 0 0 0 NaN 1 0
#> [10,] 0.00000000 0.00000000 0.00000000 0 0 0 0 NaN 0 1
## Use compareSpectra to determine the number of common (matching) peaks
## with a ppm of 10:
## type = "inner" uses a *inner join* to match peaks, i.e. keeps only
## peaks that can be mapped betwen both spectra. The provided FUN returns
## simply the number of matching peaks.
compareSpectra(sps_ms2[2:3], sps_ms2[10:20], ppm = 10, type = "inner",
FUN = function(x, y, ...) nrow(x))
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11]
#> [1,] 0 0 0 0 0 0 0 0 0 0 0
#> [2,] 0 0 0 0 0 0 0 0 0 0 0
## We repeat this calculation between all pairwise combinations
## of the first 20 spectra
compareSpectra(sps_ms2[1:20], ppm = 10, type = "inner",
FUN = function(x, y, ...) nrow(x))
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
#> [1,] 3 0 0 0 0 0 0 0 0 0 0 1 0
#> [2,] 0 3 1 0 0 0 0 0 0 0 0 0 0
#> [3,] 0 1 3 0 0 0 0 0 0 0 0 0 0
#> [4,] 0 0 0 3 0 0 0 0 0 0 0 0 0
#> [5,] 0 0 0 0 1 0 0 0 0 0 0 0 0
#> [6,] 0 0 0 0 0 11 0 0 0 0 0 0 0
#> [7,] 0 0 0 0 0 0 8 0 0 0 0 0 0
#> [8,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [9,] 0 0 0 0 0 0 0 0 7 0 0 0 0
#> [10,] 0 0 0 0 0 0 0 0 0 4 0 0 0
#> [11,] 0 0 0 0 0 0 0 0 0 0 3 0 0
#> [12,] 1 0 0 0 0 0 0 0 0 0 0 4 0
#> [13,] 0 0 0 0 0 0 0 0 0 0 0 0 2
#> [14,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [15,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [16,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [17,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [18,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [19,] 0 0 0 0 0 0 0 0 1 0 0 0 0
#> [20,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [,14] [,15] [,16] [,17] [,18] [,19] [,20]
#> [1,] 0 0 0 0 0 0 0
#> [2,] 0 0 0 0 0 0 0
#> [3,] 0 0 0 0 0 0 0
#> [4,] 0 0 0 0 0 0 0
#> [5,] 0 0 0 0 0 0 0
#> [6,] 0 0 0 0 0 0 0
#> [7,] 0 0 0 0 0 0 0
#> [8,] 0 0 0 0 0 0 0
#> [9,] 0 0 0 0 0 1 0
#> [10,] 0 0 0 0 0 0 0
#> [11,] 0 0 0 0 0 0 0
#> [12,] 0 0 0 0 0 0 0
#> [13,] 0 0 0 0 0 0 0
#> [14,] 16 0 2 0 0 2 0
#> [15,] 0 1 0 0 0 0 0
#> [16,] 2 0 5 0 0 2 0
#> [17,] 0 0 0 3 1 0 0
#> [18,] 0 0 0 1 1 0 0
#> [19,] 2 0 2 0 0 11 0
#> [20,] 0 0 0 0 0 0 4