recipe bioconductor-pcamethods

A collection of PCA methods



GPL (>= 3)




biotools: pcamethods, doi: 10.1093/bioinformatics/btm069

Provides Bayesian PCA, Probabilistic PCA, Nipals PCA, Inverse Non-Linear PCA and the conventional SVD PCA. A cluster based method for missing value estimation is included for comparison. BPCA, PPCA and NipalsPCA may be used to perform PCA on incomplete data as well as for accurate missing value estimation. A set of methods for printing and plotting the results is also provided. All PCA methods make use of the same data structure (pcaRes) to provide a common interface to the PCA results. Initiated at the Max-Planck Institute for Molecular Plant Physiology, Golm, Germany.

package bioconductor-pcamethods

(downloads) docker_bioconductor-pcamethods



depends bioconductor-biobase:


depends bioconductor-biobase:


depends bioconductor-biocgenerics:


depends bioconductor-biocgenerics:


depends libblas:


depends libgcc-ng:


depends liblapack:


depends libstdcxx-ng:


depends r-base:


depends r-mass:

depends r-rcpp:




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-pcamethods

and update with::

   mamba update bioconductor-pcamethods

To create a new environment, run:

mamba create --name myenvname bioconductor-pcamethods

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-pcamethods/tags`_ for valid values for ``<tag>``)

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