Read SRM/MRM chromatographic data — readSRMData • MSnbase

The readSRMData function reads MRM/SRM data from provided mzML files and returns the results as a MChromatograms() object.

readSRMData(files, pdata = NULL)

Arguments

files: character with the files containing the SRM/MRM data.
pdata: data.frame or AnnotatedDataFrame with file/sample descriptions.

Value

A MChromatograms() object. See details above for more information.

Details

readSRMData supports reading chromatogram entries from mzML files. If multiple files are provided the same precursor and product m/z for SRM/MRM chromatograms are expected across files. The number of columns of the resulting MChromatograms() object corresponds to the number of files. Each row in the MChromatograms object is supposed to contain chromatograms with same polarity, precursor and product m/z. If chromatograms with redundant polarity, precursor and product m/z values and precursor collision energies are found, they are placed into multiple consecutive rows in the MChromatograms object.

Note

readSRMData reads only SRM/MRM chromatogram data, i.e. chromatogram data from mzML files with precursorIsolationWindowTargetMZ and productIsolationWindowTargetMZ attributes. Total ion chromatogram data is hence not extracted.

The number of features and hence rows of the resulting MChromatograms object depends on the total list of unique precursor and product m/z isolation windows (and precursor collision energies) found across all input files. In cases in which not each file has chromatgraphic data for the same polarity, precursor m/z, product m/z and collision energy, an empty Chromatogram() object is reported for the specific precursor and product m/z combination of the respective file (and a warning is thrown).

Author

Johannes Rainer

Examples


## Read an example MRM/SRM data
library(msdata)
fl <- proteomics(full.names = TRUE, pattern = "MRM")

## Read the data
mrm <- readSRMData(fl)
#> Warning: file MRM-standmix-5.mzML.gz contains multiple chromatograms with identical polarity, precursor and product m/z values

## The data is represented as a MChromatograms object, each column
## containing the data from one input file
mrm
#> MChromatograms with 137 rows and 1 column
#>                     1
#>        <Chromatogram>
#> [1,]      length: 523
#> [2,]      length: 523
#> ...              ... 
#> [136,]    length: 962
#> [137,]    length: 962
#> phenoData with 1 variables
#> featureData with 10 variables

## Access the polarity for each chromatogram (row)
polarity(mrm)
#>   [1] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#>  [38] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#>  [75] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [112] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

## Access the precursor m/z. The result is returned as a matrix with
## columns representing the minimum and maximum m/z (will be identical in
## most cases).
precursorMz(mrm)
#>        mzmin mzmax
#>   [1,] 115.0 115.0
#>   [2,] 115.0 115.0
#>   [3,] 117.0 117.0
#>   [4,] 117.0 117.0
#>   [5,] 133.0 133.0
#>   [6,] 133.0 133.0
#>   [7,] 134.0 134.0
#>   [8,] 134.0 134.0
#>   [9,] 135.0 135.0
#>  [10,] 135.0 135.0
#>  [11,] 138.9 138.9
#>  [12,] 138.9 138.9
#>  [13,] 145.0 145.0
#>  [14,] 145.0 145.0
#>  [15,] 145.1 145.1
#>  [16,] 145.1 145.1
#>  [17,] 146.0 146.0
#>  [18,] 146.0 146.0
#>  [19,] 148.0 148.0
#>  [20,] 148.0 148.0
#>  [21,] 151.0 151.0
#>  [22,] 151.0 151.0
#>  [23,] 160.1 160.1
#>  [24,] 160.1 160.1
#>  [25,] 166.9 166.9
#>  [26,] 166.9 166.9
#>  [27,] 167.0 167.0
#>  [28,] 167.0 167.0
#>  [29,] 167.0 167.0
#>  [30,] 168.9 168.9
#>  [31,] 168.9 168.9
#>  [32,] 168.9 168.9
#>  [33,] 173.1 173.1
#>  [34,] 173.1 173.1
#>  [35,] 180.1 180.1
#>  [36,] 180.1 180.1
#>  [37,] 180.1 180.1
#>  [38,] 184.9 184.9
#>  [39,] 184.9 184.9
#>  [40,] 184.9 184.9
#>  [41,] 188.1 188.1
#>  [42,] 188.1 188.1
#>  [43,] 191.0 191.0
#>  [44,] 191.0 191.0
#>  [45,] 191.0 191.0
#>  [46,] 199.9 199.9
#>  [47,] 199.9 199.9
#>  [48,] 199.9 199.9
#>  [49,] 201.0 201.0
#>  [50,] 203.1 203.1
#>  [51,] 203.1 203.1
#>  [52,] 229.0 229.0
#>  [53,] 229.0 229.0
#>  [54,] 229.0 229.0
#>  [55,] 242.1 242.1
#>  [56,] 242.1 242.1
#>  [57,] 243.1 243.1
#>  [58,] 243.1 243.1
#>  [59,] 259.0 259.0
#>  [60,] 259.0 259.0
#>  [61,] 266.1 266.1
#>  [62,] 266.1 266.1
#>  [63,] 267.1 267.1
#>  [64,] 267.1 267.1
#>  [65,] 275.1 275.1
#>  [66,] 275.1 275.1
#>  [67,] 275.1 275.1
#>  [68,] 282.1 282.1
#>  [69,] 282.1 282.1
#>  [70,] 322.0 322.0
#>  [71,] 322.0 322.0
#>  [72,] 323.0 323.0
#>  [73,] 323.0 323.0
#>  [74,] 323.0 323.0
#>  [75,] 338.9 338.9
#>  [76,] 338.9 338.9
#>  [77,] 338.9 338.9
#>  [78,] 346.1 346.1
#>  [79,] 346.1 346.1
#>  [80,] 346.1 346.1
#>  [81,] 347.0 347.0
#>  [82,] 347.0 347.0
#>  [83,] 347.0 347.0
#>  [84,] 362.1 362.1
#>  [85,] 362.1 362.1
#>  [86,] 362.1 362.1
#>  [87,] 388.9 388.9
#>  [88,] 388.9 388.9
#>  [89,] 388.9 388.9
#>  [90,] 402.0 402.0
#>  [91,] 402.0 402.0
#>  [92,] 402.0 402.0
#>  [93,] 402.9 402.9
#>  [94,] 402.9 402.9
#>  [95,] 402.9 402.9
#>  [96,] 426.0 426.0
#>  [97,] 426.0 426.0
#>  [98,] 426.0 426.0
#>  [99,] 442.0 442.0
#> [100,] 442.0 442.0
#> [101,] 442.0 442.0
#> [102,] 481.9 481.9
#> [103,] 481.9 481.9
#> [104,] 481.9 481.9
#> [105,] 482.9 482.9
#> [106,] 482.9 482.9
#> [107,] 482.9 482.9
#> [108,] 505.9 505.9
#> [109,] 505.9 505.9
#> [110,] 505.9 505.9
#> [111,] 521.9 521.9
#> [112,] 521.9 521.9
#> [113,] 521.9 521.9
#> [114,] 565.1 565.1
#> [115,] 565.1 565.1
#> [116,] 565.1 565.1
#> [117,] 604.1 604.1
#> [118,] 604.1 604.1
#> [119,] 604.1 604.1
#> [120,] 606.1 606.1
#> [121,] 606.1 606.1
#> [122,] 606.1 606.1
#> [123,] 611.1 611.1
#> [124,] 611.1 611.1
#> [125,] 611.1 611.1
#> [126,] 662.1 662.1
#> [127,] 662.1 662.1
#> [128,] 662.1 662.1
#> [129,] 664.1 664.1
#> [130,] 664.1 664.1
#> [131,] 664.1 664.1
#> [132,] 742.1 742.1
#> [133,] 742.1 742.1
#> [134,] 808.1 808.1
#> [135,] 808.1 808.1
#> [136,]  89.0  89.0
#> [137,]  89.0  89.0

## Access the product m/z.
productMz(mrm)
#>          mzmin   mzmax
#>   [1,]  26.996  26.996
#>   [2,]  70.996  70.996
#>   [3,]  72.996  72.996
#>   [4,]  98.996  98.996
#>   [5,] 114.996 114.996
#>   [6,]  70.996  70.996
#>   [7,] 106.996 106.996
#>   [8,]  91.996  91.996
#>   [9,]  64.996  64.996
#>  [10,]  91.996  91.996
#>  [11,]  79.896  79.896
#>  [12,]  94.896  94.896
#>  [13,] 100.996 100.996
#>  [14,]  56.996  56.996
#>  [15,] 108.996 108.996
#>  [16,] 127.096 127.096
#>  [17,] 102.096 102.096
#>  [18,] 127.996 127.996
#>  [19,]  31.996  31.996
#>  [20,]  46.996  46.996
#>  [21,] 107.996 107.996
#>  [22,]  41.896  41.896
#>  [23,] 116.096 116.096
#>  [24,] 142.096 142.096
#>  [25,]  62.896  62.896
#>  [26,]  78.896  78.896
#>  [27,] 123.996 123.996
#>  [28,]  41.896  41.896
#>  [29,]  95.996  95.996
#>  [30,] 150.896 150.896
#>  [31,]  78.896  78.896
#>  [32,]  96.896  96.896
#>  [33,] 131.096 131.096
#>  [34,] 156.096 156.096
#>  [35,] 119.096 119.096
#>  [36,] 162.996 162.996
#>  [37,] 162.996 162.996
#>  [38,] 167.096 167.096
#>  [39,]  78.896  78.896
#>  [40,]  96.896  96.896
#>  [41,] 102.096 102.096
#>  [42,] 127.996 127.996
#>  [43,] 110.996 110.996
#>  [44,] 172.996 172.996
#>  [45,]  86.996  86.996
#>  [46,] 135.996 135.996
#>  [47,]  73.996  73.996
#>  [48,]  80.896  80.896
#>  [49,]  88.996  88.996
#>  [50,] 116.096 116.096
#>  [51,] 142.096 142.096
#>  [52,] 138.896 138.896
#>  [53,]  78.896  78.896
#>  [54,]  96.896  96.896
#>  [55,] 108.996 108.996
#>  [56,]  41.996  41.996
#>  [57,] 109.996 109.996
#>  [58,] 199.996 199.996
#>  [59,] 138.896 138.896
#>  [60,]  78.896  78.896
#>  [61,] 106.996 106.996
#>  [62,] 134.096 134.096
#>  [63,] 107.996 107.996
#>  [64,] 134.996 134.996
#>  [65,] 145.096 145.096
#>  [66,] 196.096 196.096
#>  [67,] 257.096 257.096
#>  [68,] 132.996 132.996
#>  [69,] 149.996 149.996
#>  [70,]  78.896  78.896
#>  [71,]  96.896  96.896
#>  [72,] 110.996 110.996
#>  [73,]  78.896  78.896
#>  [74,]  96.896  96.896
#>  [75,] 240.996 240.996
#>  [76,]  78.896  78.896
#>  [77,]  96.896  96.896
#>  [78,] 134.096 134.096
#>  [79,]  78.896  78.896
#>  [80,]  96.896  96.896
#>  [81,] 134.996 134.996
#>  [82,]  78.896  78.896
#>  [83,]  96.896  96.896
#>  [84,] 132.996 132.996
#>  [85,] 210.996 210.996
#>  [86,]  78.896  78.896
#>  [87,] 176.896 176.896
#>  [88,] 290.896 290.896
#>  [89,]  78.896  78.896
#>  [90,] 158.896 158.896
#>  [91,] 383.996 383.996
#>  [92,]  78.896  78.896
#>  [93,] 110.996 110.996
#>  [94,] 158.896 158.896
#>  [95,]  78.896  78.896
#>  [96,] 134.096 134.096
#>  [97,] 158.896 158.896
#>  [98,]  78.896  78.896
#>  [99,] 149.996 149.996
#> [100,] 158.896 158.896
#> [101,]  78.896  78.896
#> [102,] 158.896 158.896
#> [103,] 383.996 383.996
#> [104,]  78.896  78.896
#> [105,] 158.896 158.896
#> [106,] 384.096 384.096
#> [107,]  78.896  78.896
#> [108,] 158.896 158.896
#> [109,] 407.996 407.996
#> [110,]  78.896  78.896
#> [111,] 158.896 158.896
#> [112,] 423.996 423.996
#> [113,]  78.896  78.896
#> [114,] 158.896 158.896
#> [115,] 322.996 322.996
#> [116,]  78.896  78.896
#> [117,] 158.896 158.896
#> [118,] 423.996 423.996
#> [119,]  78.896  78.896
#> [120,] 158.896 158.896
#> [121,] 272.896 272.896
#> [122,]  78.896  78.896
#> [123,] 142.996 142.996
#> [124,] 272.096 272.096
#> [125,] 306.096 306.096
#> [126,] 158.896 158.896
#> [127,] 540.096 540.096
#> [128,]  78.896  78.896
#> [129,] 396.996 396.996
#> [130,] 407.996 407.996
#> [131,]  78.896  78.896
#> [132,] 407.996 407.996
#> [133,] 619.996 619.996
#> [134,] 407.996 407.996
#> [135,]  78.896  78.896
#> [136,]  40.996  40.996
#> [137,]  42.996  42.996

## Plot one chromatogram
plot(mrm[1, ])