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Combine duplicate peaks

Source: R/combine_peaks.R
combine_peaks.Rd

Identifies groups of duplicate peaks in a peak table and retains a single representative peak from each group. Peaks are considered duplicates when their retention times differ by less than tol and their spectral correlation exceeds min_cor. Use it to collapse a compound that was integrated at more than one wavelength into a single feature.

Usage

combine_peaks(
  peak_table,
  tol = 0.01,
  min_cor = 0.9,
  choose = c("max", "least_sparse", "lambda"),
  lambda = NULL,
  verbose = getOption("verbose"),
  min.cor = NULL
)

Arguments

peak_table

Peak table from get_peaktable.

tol

Tolerance for matching retention times (maximum retention time difference), in minutes. Defaults to 0.01.

min_cor

Minimum spectral correlation to confirm a match. Defaults to 0.9.

choose

Method used to select a representative peak from each group of duplicate peaks. "max" retains the peak with the greatest total intensity, "least_sparse" retains the peak detected in the greatest number of samples, and "lambda" retains peaks matching the preferred wavelength(s).

lambda

Character vector of preferred wavelength(s) to retain when choose = "lambda". The function keeps the duplicate peak whose integration wavelength matches one of the supplied values; if several match, it keeps the first in the peak table, whatever the order of lambda. A group with no match falls back to choose = "max". An error is thrown if none of the supplied values match any peak in the peak table.

verbose

Logical. Whether to print status to the console.

min.cor

The min.cor argument is deprecated. Please use min_cor instead.

Value

A peak table derived from the original, but with columns corresponding to duplicate peaks combined according to the specified criteria.

See also

get_peaks

Other utility functions: merge_peaks(), reshape_chroms(), reshape_peaktable()

Author

Ethan Bass

Examples

data(pk_tab)
data(Sa_warp)
pk_tab <- attach_ref_spectra(pk_tab)
combine_peaks(pk_tab, tol = 0.02, min_cor = 0.9)
#>           V1       V2        V3        V4        V5        V6        V7
#> 119 0.000000 5.104960 0.0000000 0.6009758 15.228827 0.4598398  80.38146
#> 121 0.000000 3.989016 0.8661555 0.5518728  7.734209 0.0000000  57.49868
#> 122 3.360145 8.139282 0.9361464 2.0773758 25.864168 2.2679018  59.76982
#> 458 0.000000 5.696499 1.7732372 1.8204290 14.969887 0.2980591 110.89038
#>           V8       V9      V10      V11      V12      V13       V14      V15
#> 119 2.909701 42.02479 1.425470 1.561397 2.446028 37.29032 14.016502 33.91009
#> 121 1.080224 18.42549 0.000000 1.021819 8.088705 20.28485  8.652057 22.63074
#> 122 1.164881 36.05080 0.000000 1.552761 4.585314 32.38382 12.627866 28.68807
#> 458 4.284673 33.86360 4.100628 2.969487 5.969776 43.45102 24.337351 25.50186
#>          V16      V17       V18       V19      V20      V21         V22
#> 119 4.463381 5.263536 1.9309993 12.848093 14.94647 2.406808 0.000000000
#> 121 1.219043 1.823485 0.1217485  6.788176 12.21597 0.740373 0.007342364
#> 122 2.452972 3.209959 0.5920201  8.346982 14.60876 2.760261 0.000000000
#> 458 5.262720 5.705804 0.4092139 12.684912 15.18446 2.299992 0.000000000
#>             V23       V24      V25       V26       V27       V28       V29
#> 119 0.088458294 0.0000000 17.56996 1.7764505 0.0000000 1.2744367 0.8476725
#> 121 0.027751603 0.4036467 14.27335 0.5863850 0.5314740 0.4319262 0.5374353
#> 122 0.080516724 0.0000000 16.53137 0.8943947 1.0992387 0.0000000 1.1170351
#> 458 0.003952009 0.0000000 24.12003 0.9896030 0.9328859 1.4820802 1.5240373
#>          V30       V31      V32        V33       V34       V35       V38
#> 119 1.568035 0.9404432 1.450265 0.00000000 0.1798730 0.4618064 0.1179606
#> 121 1.087723 0.0000000 1.850937 0.00000000 0.5016980 0.2508542 0.0000000
#> 122 1.206059 0.0000000 3.916146 0.09581451 0.5626279 0.3415882 0.3624550
#> 458 0.000000 3.3193129 3.663237 0.17479033 0.6311858 0.5666003 0.0000000
#>            V39       V49       V50         V55       V58       V60       V61
#> 119 0.10407311 2.3029954 1.2029546 0.000000000 0.1794781 0.3020769 0.6494688
#> 121 0.20955663 0.8001079 0.5176482 0.003438554 0.1411927 0.1795083 0.9209173
#> 122 0.00000000 1.2558211 1.2144860 0.004641440 0.2659416 0.0000000 0.9074791
#> 458 0.08872707 3.0731105 1.8331265 0.021059462 0.2412048 0.2994864 0.9530536