ASICS {ASICS} | R Documentation

## Automatic Statistical Identification in Complex Spectra

### Description

Quantification of 1D 1H NMR spectra with ASICS method using a library of pure metabolite spectra. The method is presented in Tardivel et al. (2017).

### Usage

    ASICS(
      spectra_obj,
      exclusion.areas = matrix(c(4.5, 5.1), ncol = 2),
      max.shift = 0.02,
      pure.library = NULL,
      noise.thres = 0.02,
      joint.align = TRUE,
      threshold.noise = NULL,
      combine = NULL,
      add.noise = 0.15,
      mult.noise = 0.172,
      quantif.method = c("FWER", "Lasso", "both"),
      clean.thres = 1,
      ref.spectrum = NULL,
      seed = 1234,
      ncores = 1,
      verbose = TRUE
    )

### Arguments

`spectra_obj` | An object of class Spectra obtained with the function createSpectra.
`exclusion.areas` | Definition domain of spectra that has to be excluded for the quantification (ppm). By default, the water region is excluded (4.5-5.1 ppm).
`max.shift` | Maximum chemical shift allowed (in ppm). Default to 0.02.
`pure.library` | An object of class PureLibrary containing the reference spectra (pure metabolite spectra). If `NULL`, the library included in the package (that contains 191 reference spectra) is used.
`noise.thres` | Threshold for signal noise. Default to 0.02.
`joint.align` | Logical. If `TRUE`, information from all spectra is taken into account to align individual library.
`threshold.noise` | DEPRECATED, use `noise.thres` instead.
`combine` | DEPRECATED, use `joint.align` instead.
`add.noise, mult.noise` | additive and multiplicative noises. To set these noises, you can compute the standard deviation in a noisy area for `add.noise` or the standard deviation in a peak area for `mult.noise` when several spectra of the same sample are available. By default, `add.noise = 0.15` and `mult.noise = 0.172`
`quantif.method` | either `"FWER"` to perform an independent quantification (the method available in ASICS since the beginning), `"Lasso"` to perform a joint quantification (all the spectra together) or `"both"` to perform a joint quantification after the FWER selection of the independent quantification. More details can be founded in the user's guide.
`clean.thres` | if `quantif.method == "both"` the percentage of spectra in which the metabolite needs to be identified by the FWER selection. Default to 1, i.e. metabolite is quantified if it was identified in at least 1% of the spectra.
`ref.spectrum` | index of the reference spectrum used for the alignment. Default to `NULL`, i.e. the reference spectrum is automatically detected.
`seed` | Random seed to control randomness in the algorithm (used in the estimation of the significativity of a given metabolite concentration).
`ncores` | Number of cores used in parallel evaluation. Default to `1`.
`verbose` | A Boolean value to allow print out process information.

### Value

An object of type ASICSResults containing the quantification results.

### Note

Since version 2.3.1 small changes were applied in order to improve the speed of metabolite selection algorithm, which can slightly impact outputs of the method.

### References

Tardivel P., Canlet C., Lefort G., Tremblay-Franco M., Debrauwer L., Concordet D., Servien R. (2017). ASICS: an automatic method for identification and quantification of metabolites in complex 1D 1H NMR spectra. Metabolomics, 13(10): 109. https://doi.org/10.1007/s11306-017-1244-5

### See Also

ASICSResults `pure_library` `createSpectra`

### Examples

    # Import data and create object
    current_path <- system.file("extdata", package = "ASICS")
    spectra_data <- importSpectra(name.dir = current_path,
                         name.file = "spectra_example.txt", type.import = "txt")
    spectra_obj <- createSpectra(spectra_data)

    # Estimation of relative quantifications
    to_exclude <- matrix(c(4.5, 10), ncol = 2)
    resASICS <- ASICS(spectra_obj, exclusion.areas = to_exclude,
                      joint.align = FALSE, quantif.method = "FWER")

[Package ASICS version 2.6.1 Index]