AlpsNMR: Automated spectraL Processing System for NMR

AlpsNMR allows you to import NMR spectra into R and provides automated and efficient signal processing for untargeted NMR metabolomics.

Details

The following functions can be combined with the pipe. They create or modify the nmr_dataset object.

• nmr_read_samples_dir() or nmr_read_samples()

• nmr_interpolate_1D()

• nmr_exclude_region()

• nmr_normalize()

• plot()

There are also functions to extract the metadata and submit the samples to irods, see the example below.

The nmr_dataset object is essentially a list, so it is easy to access its components for further analysis.

See also

Useful links:

• https://sipss.github.io/AlpsNMR/

• https://github.com/sipss/AlpsNMR

• Report bugs at https://github.com/sipss/AlpsNMR/issues

Author

Maintainer: Sergio Oller Moreno sergioller@gmail.com (ORCID)

Authors:

• Ivan Montoliu Roura Ivan.MontoliuRoura@rd.nestle.com

• Francisco Madrid Gambin fmadrid@ibecbarcelona.eu (ORCID)

• Luis Fernandez lfernandez@ibecbarcelona.eu (ORCID)

• Héctor Gracia Cabrera hgracia@ibecbarcelona.eu

• Santiago Marco Colás smarco@ibecbarcelona.eu (ORCID)

Other contributors:

• Laura López Sánchez [contributor]

• Nestlé Institute of Health Sciences [copyright holder]

• Institute for Bioengineering of Catalonia [copyright holder]

Examples

dir_to_demo_dataset <- system.file("dataset-demo", package = "AlpsNMR")
dataset <- nmr_read_samples_dir(dir_to_demo_dataset)
my_nmr_dataset <- dataset %>%
    nmr_interpolate_1D(axis = c(0.4, 10)) %>%
    nmr_exclude_region(exclude = list(water = c(4.6, 5))) %>%
    nmr_normalize(method = "pqn") %>%
    plot()
#> Warning: There are not enough samples for reliably estimating the median spectra
#> ℹ The Probabalistic Quotient Normalization requires several samples to compute the median spectra. Your number of samples is low
#> ℹ Review your peaks before and after normalization to ensure there are no big distortions