The delta m/z plot

Description

The m/z delta plot illustrates the suitability of MS2 spectra for identification by plotting the m/z differences of the most intense peaks. The resulting histogram should optimally shown outstanding bars at amino acid residu masses. The plots have been described in Foster et al 2011.

Only a certain percentage of most intense MS2 peaks are taken into account to use the most significant signal. Default value is 10% (see percentage argument). The difference between peaks is then computed for all individual spectra and their distribution is plotted as a histogram where single bars represent 1 m/z differences. Delta m/z between 40 and 200 are plotted by default, to encompass the residue masses of all amino acids and several common contaminants, although this can be changes with the xlim argument.

In addition to the processing described above, isobaric reporter tag peaks (see the reporters argument) and the precursor peak (see the precMz argument) can also be removed from the MS2 spectrum, to avoid interence with the fragment peaks.

Note that figures in Foster et al 2011 have been produced and optimised for centroided data. Application of the plot as is for data in profile mode has not been tested thoroughly, although the example below suggest that it might work.

The methods make use the ggplot2 system. An object of class ggplot is returned invisibly.

Most of the code for plotMzDelta has kindly been contributed by Guangchuang Yu.

Arguments

Methods

signature(object = "MSnExp", ...)

Plots and (invisibly) returns the m/z delta histogram.

Author(s)

Laurent Gatto <lg390@cam.ac.uk>

References

Foster JM, Degroeve S, Gatto L, Visser M, Wang R, Griss J, Apweiler R, Martens L. "A posteriori quality control for the curation and reuse of public proteomics data." Proteomics, 2011 Jun;11(11):2182-94. doi:10.1002/pmic.201000602. Epub 2011 May 2. PMID: 21538885

See Also

The plotDensity and plot2d methods for other QC plots.

Examples

mzdplot <- plotMzDelta(itraqdata,
                       subset = 0.5,
                       reporters = iTRAQ4,
                       verbose = FALSE, plot = FALSE)
## let's retrieve peptide sequence information
## and get a table of amino acids
peps <- as.character(fData(itraqdata)$PeptideSequence)
aas <- unlist(strsplit(peps,""))
## table of aas
table(aas)
## mzDelta plot
print(mzdplot)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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> library(MSnbase)
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Loading required package: Biobase
Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: mzR
Loading required package: Rcpp
Loading required package: BiocParallel
Loading required package: ProtGenerics

This is MSnbase version 1.20.7 
  Read '?MSnbase' and references therein for information
  about the package and how to get started.


Attaching package: 'MSnbase'

The following object is masked from 'package:stats':

    smooth

The following object is masked from 'package:base':

    trimws

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/MSnbase/plotMzDelta-methods.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plotMzDelta-methods
> ### Title: The delta m/z plot
> ### Aliases: plotMzDelta-methods plotMzDelta,MSnExp-method
> ###   plotMzDelta,mzRramp-method plotMzDelta
> ### Keywords: methods
> 
> ### ** Examples
> 
> mzdplot <- plotMzDelta(itraqdata,
+                        subset = 0.5,
+                        reporters = iTRAQ4,
+                        verbose = FALSE, plot = FALSE)
> ## let's retrieve peptide sequence information
> ## and get a table of amino acids
> peps <- as.character(fData(itraqdata)$PeptideSequence)
> aas <- unlist(strsplit(peps,""))
> ## table of aas
> table(aas)
aas
 A  C  D  E  F  G  H  I  K  L  M  N  P  Q  R  S  T  V  W  Y 
70  1 53 49 12 53  6 32 41 63 16 26 20 29 14 36 47 58  3 13 
> ## mzDelta plot
> print(mzdplot)
Warning messages:
1: Removed 2 rows containing missing values (geom_vline). 
2: Removed 2 rows containing missing values (geom_text). 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>