ASICS

This vignette provides an overview of the package ASICS. ASICS is a fully automated procedure to identify and quantify metabolites in $^1$H NMR spectra of biological mixtures. It will enable empowering NMR-based metabolomics by quickly and accurately helping experts to obtain metabolic profiles.

library(ASICS)

Library of pure NMR metabolites spectra

A dataset with spectra of 175 pure metabolites is available in the package. It is automatically loaded at package start and available metabolites are displayed with:

head(pure_library$name, n = 20)

Identification and quantification of metabolites on one or more Bruker files with ASICS

The identification and the quantification are carried out using only one function ASICS directly from raw files (Bruker files):

# part of the spectrum to exclude (water)
to_exclude <- matrix(c(4.5,5.1,5.5,6.5), ncol = 2, byrow = TRUE)
result <- ASICS(path = system.file("extdata", "example_spectra",
                                   "AG_faq_Beck01", package = "ASICS"),
                exclusion.areas = to_exclude)
result

The quality of the results can be assessed by stacking the original and the recomposed spectrum on one plot. A pure metabolite spectrum can also be added for visual comparison.

plot(result, xmin = 1, xmax = 1.5, ymax = 10, add_metab = "Lactate")

Relative concentrations of identified metabolites are saved in:

present_metabolites(result)

User's guide

More details on ASICS functionnalities can be obtain in the user's guide :

ASICSUsersGuide()

Reference

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

Session information

This vignette has been created with the following system configuration

sessionInfo()


Try the ASICS package in your browser

Any scripts or data that you put into this service are public.

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