Matching MS Spectra against a reference — matchSpectra,Spectra,CompDbSource,Param-method • MetaboAnnotation

matchSpectra compares experimental (query) MS2 spectra against reference (target) MS2 spectra and reports matches with a similarity that passing a specified threshold. The function performs the similarity calculation between each query spectrum against each target spectrum. Parameters query and target can be used to define the query and target spectra, respectively, while parameter param allows to define and configure the similarity calculation and matching condition. Parameter query takes a Spectra object while target can be either a Spectra object, a CompDb (reference library) object defined in the CompoundDb package or a CompAnnotationSource (e.g. a CompDbSource()) with the reference or connection information to a supported annotation resource).

Some notes on performance and information on parallel processing are provided in the vignette.

Currently supported parameter objects defining the matching are:

CompareSpectraParam: the generic parameter object allowing to set all settings for the compareSpectra() call that is used to perform the similarity calculation. This includes MAPFUN and FUN defining the peak-mapping and similarity calculation functions and ppm and tolerance to define an acceptable difference between m/z values of the compared peaks. Additional parameters to the compareSpectra call can be passed along with .... See the help of Spectra() for more information on these parameters. Parameters requirePrecursor (default TRUE) and requirePrecursorPeak (default FALSE) allow to pre-filter the target spectra prior to the actual similarity calculation for each individual query spectrum. Target spectra can also be pre-filtered based on retention time if parameter toleranceRt is set to a value different than the default toleranceRt = Inf. Only target spectra with a retention time within the query's retention time +/- (toleranceRt + percentRt% of the query's retention time) are considered. Note that while for ppm and tolerance only a single value is accepted, toleranceRt and percentRt can be also of length equal to the number of query spectra hence allowing to define different rt boundaries for each query spectrum. While these pre-filters can considerably improve performance, it should be noted that no matches will be found between query and target spectra with missing values in the considered variable (precursor m/z or retention time). For target spectra without retention times (such as for Spectra from a public reference database such as MassBank) the default toleranceRt = Inf should thus be used. Finally, parameter THRESHFUN allows to define a function to be applied to the similarity scores to define which matches to report. See below for more details.
MatchForwardReverseParam: performs spectra matching as with CompareSpectraParam but reports, similar to MS-DIAL, also the reverse similarity score and the presence ratio. In detail, the matching of query spectra to target spectra is performed by considering all peaks from the query and all peaks from the target (reference) spectrum (i.e. forward matching using an outer join-based peak matching strategy). For matching spectra also the reverse similarity is calculated considering only peaks present in the target (reference) spectrum (i.e. using a right join-based peak matching). This is reported as spectra variable "reverse_score". In addition, the ratio between the number of matched peaks and the total number of peaks in the target (reference) spectra is reported as the presence ratio (spectra variable "presence_ratio") and the total number of matched peaks as "matched_peaks_count". See examples below for details. Parameter THRESHFUN_REVERSE allows to define an additional threshold function to filter matches. If THRESHFUN_REVERSE is defined only matches with a spectra similarity fulfilling both THRESHFUN and THRESHFUN_REVERSE are returned. With the default THRESHFUN_REVERSE = NULL all matches passing THRESHFUN are reported.

Usage

# S4 method for class 'Spectra,CompDbSource,Param'
matchSpectra(
  query,
  target,
  param,
  BPPARAM = BiocParallel::SerialParam(),
  addOriginalQueryIndex = TRUE
)

CompareSpectraParam(
  MAPFUN = joinPeaks,
  tolerance = 0,
  ppm = 5,
  FUN = MsCoreUtils::ndotproduct,
  requirePrecursor = TRUE,
  requirePrecursorPeak = FALSE,
  THRESHFUN = function(x) which(x >= 0.7),
  toleranceRt = Inf,
  percentRt = 0,
  ...
)

MatchForwardReverseParam(
  MAPFUN = joinPeaks,
  tolerance = 0,
  ppm = 5,
  FUN = MsCoreUtils::ndotproduct,
  requirePrecursor = TRUE,
  requirePrecursorPeak = FALSE,
  THRESHFUN = function(x) which(x >= 0.7),
  THRESHFUN_REVERSE = NULL,
  toleranceRt = Inf,
  percentRt = 0,
  ...
)

# S4 method for class 'Spectra,Spectra,CompareSpectraParam'
matchSpectra(
  query,
  target,
  param,
  rtColname = c("rtime", "rtime"),
  BPPARAM = BiocParallel::SerialParam(),
  addOriginalQueryIndex = TRUE
)

# S4 method for class 'Spectra,CompDb,Param'
matchSpectra(
  query,
  target,
  param,
  rtColname = c("rtime", "rtime"),
  BPPARAM = BiocParallel::SerialParam(),
  addOriginalQueryIndex = TRUE
)

# S4 method for class 'Spectra,Spectra,MatchForwardReverseParam'
matchSpectra(
  query,
  target,
  param,
  rtColname = c("rtime", "rtime"),
  BPPARAM = BiocParallel::SerialParam(),
  addOriginalQueryIndex = TRUE
)

Arguments

query: for matchSpectra: Spectra object with the query spectra.
target: for matchSpectra: Spectra, CompDb or object extending CompAnnotationSource (such as CompDbSource) with the target (reference) spectra to compare query against.
param: for matchSpectra: parameter object (such as CompareSpectraParam) defining the settings for the matching.
BPPARAM: for matchSpectra: parallel processing setup (see the BiocParallel package for more information). Parallel processing is disabled by default (with the default setting BPPARAM = SerialParam()).
addOriginalQueryIndex: for matchSpectra(): logical(1) whether an additional spectra variable ".original_query_index" should be added to the query Spectra object providing the index of the spectrum in this originally provided object. This spectra variable can be useful to link back to the original Spectra object if the MatchedSpectra object gets subsetted/processed.
MAPFUN: function used to map peaks between the compared spectra. Defaults for CompareSpectraParam to joinPeaks(). See compareSpectra() for details.
tolerance: numeric(1) for an absolute maximal accepted difference between m/z values. This will be used in compareSpectra as well as for eventual precursor m/z matching.
ppm: numeric(1) for a relative, m/z-dependent, maximal accepted difference between m/z values. This will be used in compareSpectra as well as for eventual precursor m/z matching.
FUN: function used to calculate similarity between spectra. Defaults for CompareSpectraParam to MsCoreUtils::ndotproduct(). See MsCoreUtils::ndotproduct() for details.
requirePrecursor: logical(1) whether only target spectra are considered in the similarity calculation with a precursor m/z that matches the precursor m/z of the query spectrum (considering also ppm and tolerance). With requirePrecursor = TRUE (the default) the function will complete much faster, but will not find any hits for target (or query spectra) with missing precursor m/z. It is suggested to check first the availability of the precursor m/z in target and query.
requirePrecursorPeak: logical(1) whether only target spectra will be considered in the spectra similarity calculation that have a peak with an m/z matching the precursor m/z of the query spectrum. Defaults to requirePrecursorPeak = FALSE. It is suggested to check first the availability of the precursor m/z in query, as no match will be reported for query spectra with missing precursor m/z.
THRESHFUN: function applied to the similarity score to define which target spectra are considered matching. Defaults to THRESHFUN = function(x) which(x >= 0.7) hence selects all target spectra matching a query spectrum with a similarity higher or equal than 0.7. Any function that takes a numeric vector with similarity scores from the comparison of a query spectrum with all target spectra (as returned by compareSpectra()) as input and returns a logical vector (same dimensions as the similarity scores) or an integer with the matches is supported.
toleranceRt: numeric of length 1 or equal to the number of query spectra defining the maximal accepted (absolute) difference in retention time between query and target spectra. By default (with toleranceRt = Inf) the retention time-based filter is not considered. See help of CompareSpectraParam above for more information.
percentRt: numeric of length 1 or equal to the number of query spectra defining the maximal accepted relative difference in retention time between query and target spectra expressed in percentage of the query rt. For percentRt = 10, similarities are defined between the query spectrum and all target spectra with a retention time within query rt +/- 10% of the query. By default (with toleranceRt = Inf) the retention time-based filter is not considered. Thus, to consider the percentRt parameter, toleranceRt should be set to a value different than that. See help of CompareSpectraParam above for more information.
...: for CompareSpectraParam: additional parameters passed along to the compareSpectra() call.
THRESHFUN_REVERSE: for MatchForwardReverseParam: optional additional thresholding function to filter the results on the reverse score. If specified the same format than THRESHFUN is expected.
rtColname: character(2) with the name of the spectra variable containing the retention time information for compounds to be used in retention time matching (only used if toleranceRt is not Inf). It can also be character(1) if the two names are the same. Defaults to rtColname = c("rtime", "rtime").

Value

matchSpectra returns a MatchedSpectra() object with the matching results. If target is a CompAnnotationSource only matching target spectra will be reported.

Constructor functions return an instance of the class.

Author

Johannes Rainer, Michael Witting

Examples


library(Spectra)
#> Loading required package: S4Vectors
#> Loading required package: stats4
#> Loading required package: BiocGenerics
#> Loading required package: generics
#> 
#> Attaching package: ‘generics’
#> The following objects are masked from ‘package:base’:
#> 
#>     as.difftime, as.factor, as.ordered, intersect, is.element, setdiff,
#>     setequal, union
#> 
#> Attaching package: ‘BiocGenerics’
#> The following objects are masked from ‘package:stats’:
#> 
#>     IQR, mad, sd, var, xtabs
#> The following objects are masked from ‘package:base’:
#> 
#>     Filter, Find, Map, Position, Reduce, anyDuplicated, aperm, append,
#>     as.data.frame, basename, cbind, colnames, dirname, do.call,
#>     duplicated, eval, evalq, get, grep, grepl, is.unsorted, lapply,
#>     mapply, match, mget, order, paste, pmax, pmax.int, pmin, pmin.int,
#>     rank, rbind, rownames, sapply, saveRDS, table, tapply, unique,
#>     unsplit, which.max, which.min
#> 
#> Attaching package: ‘S4Vectors’
#> The following object is masked from ‘package:MetaboAnnotation’:
#> 
#>     endoapply
#> The following object is masked from ‘package:utils’:
#> 
#>     findMatches
#> The following objects are masked from ‘package:base’:
#> 
#>     I, expand.grid, unname
#> Loading required package: BiocParallel
library(msdata)
fl <- system.file("TripleTOF-SWATH", "PestMix1_DDA.mzML", package = "msdata")
pest_ms2 <- filterMsLevel(Spectra(fl), 2L)

## subset to selected spectra.
pest_ms2 <- pest_ms2[c(808, 809, 945:955)]

## Load a small example MassBank data set
load(system.file("extdata", "minimb.RData", package = "MetaboAnnotation"))

## Match spectra with the default similarity score (normalized dot product)
csp <- CompareSpectraParam(requirePrecursor = TRUE, ppm = 10)
mtches <- matchSpectra(pest_ms2, minimb, csp)

mtches
#> Object of class MatchedSpectra 
#> Total number of matches: 16 
#> Number of query objects: 13 (5 matched)
#> Number of target objects: 100 (11 matched)

## Are there any matching spectra for the first query spectrum?
mtches[1]
#> Object of class MatchedSpectra 
#> Total number of matches: 0 
#> Number of query objects: 1 (0 matched)
#> Number of target objects: 100 (0 matched)
## No

## And for the second query spectrum?
mtches[2]
#> Object of class MatchedSpectra 
#> Total number of matches: 4 
#> Number of query objects: 1 (1 matched)
#> Number of target objects: 100 (4 matched)
## The second query spectrum matches 4 target spectra. The scores for these
## matches are:
mtches[2]$score
#> [1] 0.7869556 0.8855473 0.7234894 0.7219942

## To access the score for the full data set
mtches$score
#>  [1]        NA 0.7869556 0.8855473 0.7234894 0.7219942        NA 0.7769746
#>  [8] 0.7577286        NA 0.7433718 0.7019807 0.7081274        NA 0.7320465
#> [15] 0.8106258 0.7290458 0.8168876 0.7247800 0.7412586 0.7198787        NA
#> [22]        NA        NA        NA

## Below we use a THRESHFUN that returns for each query spectrum the (first)
## best matching target spectrum.
csp <- CompareSpectraParam(requirePrecursor = FALSE, ppm = 10,
    THRESHFUN = function(x) which.max(x))
mtches <- matchSpectra(pest_ms2, minimb, csp)
mtches
#> Object of class MatchedSpectra 
#> Total number of matches: 13 
#> Number of query objects: 13 (13 matched)
#> Number of target objects: 100 (10 matched)

## Each of the query spectra is matched to one target spectrum
length(mtches)
#> [1] 13
matches(mtches)
#>    query_idx target_idx        score
#> 1          1          1 0.000000e+00
#> 2          2         73 8.855473e-01
#> 3          3          2 6.313687e-01
#> 4          4         44 7.769746e-01
#> 5          5         74 1.772117e-05
#> 6          6          2 7.433718e-01
#> 7          7          5 1.906998e-03
#> 8          8         53 8.168876e-01
#> 9          9         44 7.412586e-01
#> 10        10         86 4.085289e-04
#> 11        11         53 4.323403e-01
#> 12        12         47 3.469648e-03
#> 13        13         71 7.612480e-06

## Match spectra considering also measured retention times. This requires
## that both query and target spectra have non-missing retention times.
rtime(pest_ms2)
#>  [1] 361.651 361.741 377.609 377.699 378.120 378.539 378.779 378.869 378.959
#> [10] 379.379 380.059 380.609 381.029
rtime(minimb)
#>   [1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
#>  [26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
#>  [51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
#>  [76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

## Target spectra don't have retention times. Below we artificially set
## retention times to show how an additional retention time filter would
## work.
rtime(minimb) <- rep(361, length(minimb))

## Matching spectra requiring a matching precursor m/z and the difference
## of retention times between query and target spectra to be <= 2 seconds.
csp <- CompareSpectraParam(requirePrecursor = TRUE, ppm = 10,
    toleranceRt = 2)
mtches <- matchSpectra(pest_ms2, minimb, csp)
mtches
#> Object of class MatchedSpectra 
#> Total number of matches: 4 
#> Number of query objects: 13 (1 matched)
#> Number of target objects: 100 (4 matched)
matches(mtches)
#>   query_idx target_idx     score
#> 1         2         70 0.7869556
#> 2         2         73 0.8855473
#> 3         2         75 0.7234894
#> 4         2         76 0.7219942

## Note that parameter `rtColname` can be used to define different spectra
## variables with retention time information (such as retention indices etc).

## A `CompDb` compound annotation database could also be used with
## parameter `target`. Below we load the test `CompDb` database from the
## `CompoundDb` Bioconductor package.
library(CompoundDb)
#> Loading required package: AnnotationFilter
fl <- system.file("sql", "CompDb.MassBank.sql", package = "CompoundDb")
cdb <- CompDb(fl)
res <- matchSpectra(pest_ms2, cdb, CompareSpectraParam())

## We do however not find any matches since the used compound annotation
## database contains only a very small subset of the MassBank.
res
#> Object of class MatchedSpectra 
#> Total number of matches: 0 
#> Number of query objects: 13 (0 matched)
#> Number of target objects: 70 (0 matched)

## As `target` we have now however the MS2 spectra data from the compound
## annotation database
target(res)
#> MSn data (Spectra) with 70 spectra in a MsBackendCompDb backend:
#>       msLevel precursorMz  polarity
#>     <integer>   <numeric> <integer>
#> 1           2      179.07         1
#> 2           2      179.07         1
#> 3           2      179.07         1
#> 4           2      179.07         1
#> 5           2      179.07         1
#> ...       ...         ...       ...
#> 66          2     337.091         1
#> 67          2     337.091         1
#> 68          2     337.091         1
#> 69          2     337.091         1
#> 70          2     337.091         1
#>  ... 46 more variables/columns.
#>  Use  'spectraVariables' to list all of them.
#>  data source: MassBank 
#>  version: 2020.09 
#>  organism: NA 

## See the package vignette for details, descriptions and more examples,
## also on how to retrieve e.g. MassBank reference databases from
## Bioconductor's AnnotationHub.