Performs reporter ions purity correction
purityCorrect-methods.RdManufacturers sometimes provide purity correction values indicating the percentages of each reporter ion that have masses differing by +/- n Da from the nominal reporter ion mass due to isotopic variants. This correction is generally applied after reporter peaks quantitation.
Purity correction here is applied using solve from the
base package using the purity correction values as coefficient of
the linear system and the reporter quantities as the right-hand side
of the linear system. 'NA' values are ignored and negative
intensities after correction are also set to 'NA'.
A more elaborated purity correction method is described in Shadforth et al., i-Tracker: for quantitative proteomics using iTRAQ. BMC Genomics. 2005 Oct 20;6:145. (PMID 16242023).
Function makeImpuritiesMatrix(x, filename, edit = TRUE) helps
the user to create such a matrix. The function can be used in two ways.
If given an integer x, it is used as the dimension of the
square matrix (i.e the number of reporter ions). For TMT6-plex and
iTRAQ4-plex, default values taken from manufacturer's certification
sheets are used as templates, but batch specific values should be used
whenever possible. Alternatively, the filename of a csv
spreadsheet can be provided. The sheet should define the correction
factors as illustrated below (including reporter names in the first
column and header row) and the corresponding correction matrix is
calculated. Examples of such csv files are available in the
package's extdata directory. Use
dir(system.file("extdata", package = "MSnbase"), pattern =
"PurityCorrection", full.names = TRUE) to locate them.
If edit = TRUE, the the matrix can be edited before
it is returned.
Arguments
- object
An object of class
"MSnSet".- impurities
A square 'matrix' of dim equal to ncol(object) defining the correction coefficients to be applied. The reporter ions should be ordered along the columns and the relative percentages along the rows.
As an example, below is the correction factors as provided in an ABI iTRAQ 4-plex certificate of analysis:
reporter % of -2 % of -1 % of +1 % of +2 114 0.0 1.0 5.9 0.2 115 0.0 2.0 5.6 0.1 116 0.0 3.0 4.5 0.1 117 0.1 4.0 3.5 0.1 The impurity table will be
0.929 0.059 0.002 0.000 0.020 0.923 0.056 0.001 0.000 0.030 0.924 0.045 0.000 0.001 0.040 0.923 where, the diagonal is computed as 100 - sum of rows of the original table and subsequent cells are directly filled in.
Similarly, for TMT 6-plex tags, we observe
reporter % of -3 % of -2 % of -1 % of +1 % % of +2 % of +3 126 0 0 0 6.1 0 0 127 0 0 0.5 6.7 0 0 128 0 0 1.1 4.2 0 0 129 0 0 1.7 4.1 0 0 130 0 0 1.6 2.1 0 0 131 0 0.2 3.2 2.8 0 0 and obtain the following impurity correction matrix
0.939 0.061 0.000 0.000 0.000 0.000 0.005 0.928 0.067 0.000 0.000 0.000 0.000 0.011 0.947 0.042 0.000 0.000 0.000 0.000 0.017 0.942 0.041 0.000 0.000 0.000 0.000 0.016 0.963 0.021 0.000 0.000 0.000 0.002 0.032 0.938 For iTRAQ 8-plex, given the following correction factors (to make such a matrix square, if suffices to add -4, -3, +3 and +4 columns filled with zeros):
TAG -2 -1 +1 +2 113 0 2.5 3 0.1 114 0 1 5.9 0.2 115 0 2 5.6 0.1 116 0 3 4.5 0.1 117 0.1 4 3.5 0.1 118 0.1 2 3 0.1 119 0.1 2 4 0.1 121 0.1 2 3 0.1 we calculate the impurity correction matrix shown below
113 114 115 116 117 118 119 121 % reporter 113 0.944 0.030 0.001 0.000 0.000 0.000 0.000 0.000 % reporter 114 0.010 0.929 0.059 0.002 0.000 0.000 0.000 0.000 % reporter 115 0.000 0.020 0.923 0.056 0.001 0.000 0.000 0.000 % reporter 116 0.000 0.000 0.030 0.924 0.045 0.001 0.000 0.000 % reporter 117 0.000 0.000 0.001 0.040 0.923 0.035 0.001 0.000 % reporter 118 0.000 0.000 0.000 0.001 0.020 0.948 0.030 0.001 % reporter 119 0.000 0.000 0.000 0.000 0.001 0.020 0.938 0.040 % reporter 121 0.000 0.000 0.000 0.000 0.000 0.001 0.020 0.948 Finally, for a TMT 10-plex impurity matrix (for example lot RH239932)
. -2 -1 1 2 126 0.0 0.0 5.0 (127C) 0.0 (128C) 127N 0.0 0.2 5.8 (128N) 0.0 (129N) 127C 0.0 0.3 (126) 4.8 (128C) 0.0 (129C) 128N 0.0 0.4 (127N) 4.1 (129N) 0.0 (130N) 128C 0.0 (126) 0.6 (127C) 3.0 (129C) 0.0 (130C) 129N 0.0 (127N) 0.8 (128N) 3.5 (130N) 0.0 (131) 129C 0.0 (127C) 1.4 (128C) 2.4 (130C) 0.0 130N 0.1 (128N) 1.5 (129N) 2.4 (131) 3.2 130C 0.0 (128C) 1.7 (129C) 1.8 0.0 (Note that a previous example, taken from lot PB199188A, contained a typo.)
the impurity correction matrix is
. 126 127N 127C 128N 128C 129N 129C 130N 130C 131 % reporter 126 0.950 0.000 0.050 0.000 0.000 0.000 0.000 0.000 0.000 0.000 % reporter 127N 0.000 0.940 0.000 0.058 0.000 0.000 0.000 0.000 0.000 0.000 % reporter 127C 0.003 0.000 0.949 0.000 0.048 0.000 0.000 0.000 0.000 0.000 % reporter 128N 0.000 0.004 0.000 0.955 0.000 0.041 0.000 0.000 0.000 0.000 % reporter 128C 0.000 0.000 0.006 0.000 0.964 0.000 0.030 0.000 0.000 0.000 % reporter 129N 0.000 0.000 0.000 0.008 0.000 0.957 0.000 0.035 0.000 0.000 % reporter 129C 0.000 0.000 0.000 0.000 0.014 0.000 0.962 0.000 0.024 0.000 % reporter 130N 0.000 0.000 0.000 0.001 0.000 0.015 0.000 0.928 0.000 0.024 % reporter 130C 0.000 0.000 0.000 0.000 0.000 0.000 0.017 0.000 0.965 0.000 % reporter 131 0.000 0.000 0.000 0.000 0.000 0.002 0.000 0.020 0.000 0.956 These examples are provided as defaults impurity correction matrices in
makeImpuritiesMatrix.
Examples
## quantifying full experiment
data(msnset)
impurities <- matrix(c(0.929,0.059,0.002,0.000,
0.020,0.923,0.056,0.001,
0.000,0.030,0.924,0.045,
0.000,0.001,0.040,0.923),
nrow=4, byrow = TRUE)
## or, using makeImpuritiesMatrix()
if (FALSE) impurities <- makeImpuritiesMatrix(4) # \dontrun{}
msnset.crct <- purityCorrect(msnset, impurities)
head(exprs(msnset))
#> iTRAQ4.114 iTRAQ4.115 iTRAQ4.116 iTRAQ4.117
#> X1 1347.6158 2247.3097 3927.6931 7661.1463
#> X10 739.9861 799.3501 712.5983 940.6793
#> X11 27638.3582 33394.0252 32104.2879 26628.7278
#> X12 31892.8928 33634.6980 37674.7272 37227.7119
#> X13 26143.7542 29677.4781 29089.0593 27902.5608
#> X14 6448.0829 6234.1957 6902.8903 6437.2303
head(exprs(msnset.crct))
#> iTRAQ4.114 iTRAQ4.115 iTRAQ4.116 iTRAQ4.117
#> X1 1402.9442 2214.0346 3762.2549 8114.4429
#> X10 779.4666 793.0792 678.8083 985.2003
#> X11 29034.3781 33271.0470 31484.7131 27279.1383
#> X12 33618.9092 33046.3075 37031.6133 38492.1376
#> X13 27508.0038 29440.9296 28390.4561 28814.2463
#> X14 6809.7600 6090.7894 6799.5030 6636.1450
processingData(msnset.crct)
#> - - - Processing information - - -
#> Data loaded: Wed May 11 18:54:39 2011
#> iTRAQ4 quantification by trapezoidation: Wed Apr 1 21:41:53 2015
#> Purity corrected: Tue Oct 15 15:27:10 2024
#> MSnbase version: 1.1.22
## default impurity matrix for iTRAQ 8-plex
makeImpuritiesMatrix(8, edit = FALSE)
#> 113 114 115 116 117 118 119 121
#> % reporter 113 0.944 0.030 0.001 0.000 0.000 0.000 0.000 0.000
#> % reporter 114 0.010 0.929 0.059 0.002 0.000 0.000 0.000 0.000
#> % reporter 115 0.000 0.020 0.923 0.056 0.001 0.000 0.000 0.000
#> % reporter 116 0.000 0.000 0.030 0.924 0.045 0.001 0.000 0.000
#> % reporter 117 0.000 0.000 0.001 0.040 0.923 0.035 0.001 0.000
#> % reporter 118 0.000 0.000 0.000 0.001 0.020 0.948 0.030 0.001
#> % reporter 119 0.000 0.000 0.000 0.000 0.001 0.020 0.938 0.040
#> % reporter 121 0.000 0.000 0.000 0.000 0.000 0.001 0.020 0.948
## default impurity matrix for TMT 10-plex
makeImpuritiesMatrix(10, edit = FALSE)
#> 126 127N 127C 128N 128C 129N 129C 130N 130C 131
#> % reporter 126 0.950 0.000 0.050 0.000 0.000 0.000 0.000 0.000 0.000 0.000
#> % reporter 127N 0.000 0.940 0.000 0.058 0.000 0.000 0.000 0.000 0.000 0.000
#> % reporter 127C 0.003 0.000 0.949 0.000 0.048 0.000 0.000 0.000 0.000 0.000
#> % reporter 128N 0.000 0.004 0.000 0.955 0.000 0.041 0.000 0.000 0.000 0.000
#> % reporter 128C 0.000 0.000 0.006 0.000 0.964 0.000 0.030 0.000 0.000 0.000
#> % reporter 129N 0.000 0.000 0.000 0.008 0.000 0.957 0.000 0.035 0.000 0.000
#> % reporter 129C 0.000 0.000 0.000 0.000 0.014 0.000 0.962 0.000 0.024 0.000
#> % reporter 130N 0.000 0.000 0.000 0.001 0.000 0.015 0.000 0.928 0.000 0.024
#> % reporter 130C 0.000 0.000 0.000 0.000 0.000 0.000 0.017 0.000 0.965 0.000
#> % reporter 131 0.000 0.000 0.000 0.000 0.000 0.002 0.000 0.020 0.000 0.956