recipe bioconductor-alpsnmr

Automated spectraL Processing System for NMR






Reads Bruker NMR data directories both zipped and unzipped. It provides automated and efficient signal processing for untargeted NMR metabolomics. It is able to interpolate the samples, detect outliers, exclude regions, normalize, detect peaks, align the spectra, integrate peaks, manage metadata and visualize the spectra. After spectra proccessing, it can apply multivariate analysis on extracted data. Efficient plotting with 1-D data is also available. Basic reading of 1D ACD/Labs exported JDX samples is also available.

package bioconductor-alpsnmr

(downloads) docker_bioconductor-alpsnmr



depends bioconductor-biocparallel:


depends bioconductor-mixomics:


depends r-base:


depends r-baseline:


depends r-cli:

depends r-dplyr:


depends r-fs:


depends r-future:


depends r-generics:

depends r-ggplot2:


depends r-glue:


depends r-htmltools:


depends r-magrittr:


depends r-matrixstats:


depends r-pcapp:


depends r-purrr:


depends r-readxl:


depends r-reshape2:


depends r-rlang:


depends r-rmarkdown:


depends r-scales:


depends r-signal:


depends r-speaq:


depends r-stringr:


depends r-tibble:


depends r-tidyr:


depends r-tidyselect:

depends r-vctrs:




You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install bioconductor-alpsnmr

and update with::

   mamba update bioconductor-alpsnmr

To create a new environment, run:

mamba create --name myenvname bioconductor-alpsnmr

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull<tag>

(see `bioconductor-alpsnmr/tags`_ for valid values for ``<tag>``)

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