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Process Bruker MALDI Biotyper spectra à la Strejcek et al. (2018)

Source: R/process_spectra.R
process_spectra.Rd

Process Bruker MALDI Biotyper spectra à la Strejcek et al. (2018)

Usage

process_spectra(
  spectra_list,
  spectra_names = get_spectra_names(spectra_list),
  rds_prefix = deprecated()
)

Arguments

spectra_list

A list of MALDIquant::MassSpectrum objects.

spectra_names

A tibble::tibble (or data.frame) of sanitized spectra names by default from get_spectra_names. If provided manually, the column sanitized_name will be used to name the spectra.

rds_prefix

[Deprecated] Writing to disk as RDS is no longer supported. A character indicating the prefix for the .RDS output files to be written in the processed directory. By default, no prefix are given and thus no files are written.

Value

A named list of three objects:

  • spectra: a list the length of the spectra list of MALDIquant::MassSpectrum objects.

  • peaks: a list the length of the spectra list of MALDIquant::MassPeaks objects.

  • metadata: a tibble indicating the median signal-to-noise ratio (SNR) and peaks number for all spectra list (peaks), with spectra names in the name column.

Details

Based on the original implementation, the function performs the following tasks:

  1. Square-root transformation

  2. Mass range trimming to 4-10 kDa as they were deemed most determinant by Strejcek et al. (2018)

  3. Signal smoothing using the Savitzky-Golay method and a half window size of 20

  4. Baseline correction with the SNIP procedure

  5. Normalization by Total Ion Current

  6. Peak detection using the SuperSmoother procedure and with a signal-to-noise ratio above 3

  7. Peak filtering. This step has been added to discard peaks with a negative signal-to-noise ratio probably due to being on the edge of the mass range.

Note

The original R code on which this function is based is accessible at: https://github.com/strejcem/MALDIvs16S

References

Strejcek M, Smrhova T, Junkova P & Uhlik O (2018). “Whole-Cell MALDI-TOF MS versus 16S rRNA Gene Analysis for Identification and Dereplication of Recurrent Bacterial Isolates.” Frontiers in Microbiology 9 doi:10.3389/fmicb.2018.01294.

See also

import_biotyper_spectra and check_spectra for the inputs and merge_processed_spectra for further analysis.

Examples

# Get an example directory of six Bruker MALDI Biotyper spectra
directory_biotyper_spectra <- system.file(
  "toy-species-spectra",
  package = "maldipickr"
)
# Import the six spectra
spectra_list <- import_biotyper_spectra(directory_biotyper_spectra)
# Transform the spectra signals according to Strejcek et al. (2018)
processed <- process_spectra(spectra_list)
# Overview of the list architecture that is returned
#  with the list of processed spectra, peaks identified and the
#  metadata table
str(processed, max.level = 2)
#> List of 3
#>  $ spectra :List of 6
#>   ..$ species1_G2 :Formal class 'MassSpectrum' [package "MALDIquant"] with 3 slots
#>   ..$ species2_E11:Formal class 'MassSpectrum' [package "MALDIquant"] with 3 slots
#>   ..$ species2_E12:Formal class 'MassSpectrum' [package "MALDIquant"] with 3 slots
#>   ..$ species3_F7 :Formal class 'MassSpectrum' [package "MALDIquant"] with 3 slots
#>   ..$ species3_F8 :Formal class 'MassSpectrum' [package "MALDIquant"] with 3 slots
#>   ..$ species3_F9 :Formal class 'MassSpectrum' [package "MALDIquant"] with 3 slots
#>  $ peaks   :List of 6
#>   ..$ species1_G2 :Formal class 'MassPeaks' [package "MALDIquant"] with 4 slots
#>   ..$ species2_E11:Formal class 'MassPeaks' [package "MALDIquant"] with 4 slots
#>   ..$ species2_E12:Formal class 'MassPeaks' [package "MALDIquant"] with 4 slots
#>   ..$ species3_F7 :Formal class 'MassPeaks' [package "MALDIquant"] with 4 slots
#>   ..$ species3_F8 :Formal class 'MassPeaks' [package "MALDIquant"] with 4 slots
#>   ..$ species3_F9 :Formal class 'MassPeaks' [package "MALDIquant"] with 4 slots
#>  $ metadata: tibble [6 × 3] (S3: tbl_df/tbl/data.frame)
# A detailed view of the metadata with the median signal-to-noise
#  ratio (SNR) and the number of peaks
processed$metadata
#> # A tibble: 6 × 3
#>   name           SNR peaks
#>   <chr>        <dbl> <int>
#> 1 species1_G2   5.09    21
#> 2 species2_E11  5.54    22
#> 3 species2_E12  5.63    23
#> 4 species3_F7   4.89    26
#> 5 species3_F8   5.56    25
#> 6 species3_F9   5.40    25