ASICS: Automatic Statistical Identification in Complex Spectra

In ASICS: Automatic Statistical Identification in Complex Spectra

Description

Quantification of 1D 1H NMR spectrum with ASICS method using a library of 175 pure metabolite spectra. The method is presented in Tardivel et al. (2017).

Usage

ASICS(path, exclusion.areas = matrix(c(4.5, 5.1), ncol = 2),
  max.shift = 0.02, which.spectra = "last", library.metabolites = NULL,
  threshold.noise = 0.02, seed = 1234, nb.iter.signif = 400)

Arguments

path	folder path of the Bruker files
exclusion.areas	definition domain of spectra to exclude (ppm)
max.shift	maximum chemical shift allowed (in ppm)
which.spectra	if more than one spectra by sample, spectra used to perform the quantification (either "first", "last" or its number). Default to "last"
library.metabolites	path of the library containing the references (pure metabolite spectra). If NULL, the library included in the package is used
threshold.noise	threshold for signal noise
seed	random seed to control randomness in the algorithm (used in the estimation of significativity of a given metabolite concentration)
nb.iter.signif	number of iterations for the estimation of significativity of a given metabolite concentration. Default to 400

Value

An object of type resASICS-class

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

resASICS-class ASICS_multiFiles pure_library

Examples

## Not run: 
cur_path <- system.file("extdata", "example_spectra", "AG_faq_Beck01",
                        package = "ASICS")
to_exclude <- matrix(c(4.5,5.1,5.5,6.5), ncol = 2, byrow = TRUE)
result <- ASICS(path = cur_path, exclusion.areas = to_exclude)

## End(Not run)

ASICS documentation built on Jan. 23, 2018, 5:51 p.m.