recipe r-speaq

Makes Nuclear Magnetic Resonance spectroscopy (NMR spectroscopy) data analysis as easy as possible by only requiring a small set of functions to perform an entire analysis. 'speaq' offers the possibility of raw spectra alignment and quantitation but also an analysis based on features whereby the spectra are converted to peaks which are then grouped and turned into features. These features can be processed with any number of statistical tools either included in 'speaq' or available elsewhere on CRAN. More detail can be found in Vu et al. (2011) <doi:10.1186/1471-2105-12-405> and Beirnaert et al. (2018) <doi:10.1371/journal.pcbi.1006018>.

Homepage:

https://CRAN.R-project.org/package=speaq

License:

APACHE / Apache-2.0

Recipe:

/r-speaq/meta.yaml

package r-speaq

(downloads) docker_r-speaq

versions:
2.7.0-3,  2.7.0-2,  2.7.0-1,  2.7.0-0,  2.6.1-3,  2.6.1-2,  2.6.1-1,  2.6.1-0,  2.6.0-0, 

2.7.0-3,  2.7.0-2,  2.7.0-1,  2.7.0-0,  2.6.1-3,  2.6.1-2,  2.6.1-1,  2.6.1-0,  2.6.0-0,  2.3.3-1,  2.3.3-0,  2.1.0-0,  1.2.3-0,  1.2.1-1,  1.2.1-0

depends bioconductor-impute:

depends bioconductor-massspecwavelet:

depends r-base:

>=4.4,<4.5.0a0

depends r-cluster:

depends r-data.table:

depends r-dosnow:

depends r-foreach:

depends r-ggplot2:

depends r-gridextra:

depends r-missforest:

depends r-reshape2:

depends r-rfast:

depends r-rvest:

depends r-xml2:

requirements:

additional platforms:

Installation

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 r-speaq

and update with::

   mamba update r-speaq

To create a new environment, run:

mamba create --name myenvname r-speaq

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 quay.io/biocontainers/r-speaq:<tag>

(see `r-speaq/tags`_ for valid values for ``<tag>``)

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