Package Recipe 'bioconductor-pcamethods'

recipe bioconductor-pcamethods

A collection of PCA methods

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/pcaMethods.html
License:: GPL (>= 3)
Recipe:: /bioconductor-pcamethods/meta.yaml
Links:: 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¶

Versions:

2.2.0-0, 1.98.0-1, 1.98.0-0, 1.94.0-1, 1.94.0-0, 1.92.0-0, 1.90.0-1, 1.90.0-0, 1.86.0-2,

2.2.0-0, 1.98.0-1, 1.98.0-0, 1.94.0-1, 1.94.0-0, 1.92.0-0, 1.90.0-1, 1.90.0-0, 1.86.0-2, 1.86.0-1, 1.86.0-0, 1.84.0-0, 1.82.0-1, 1.82.0-0, 1.80.0-0, 1.78.0-0, 1.76.0-1, 1.74.0-0, 1.72.0-0, 1.70.0-0, 1.68.0-0, 1.64.0-2, 1.64.0-1, 1.64.0-0

Depends:

on bioconductor-biobase >=2.70.0,<2.71.0
on bioconductor-biobase >=2.70.0,<2.71.0a0
on bioconductor-biocgenerics >=0.56.0,<0.57.0
on bioconductor-biocgenerics >=0.56.0,<0.57.0a0
on libblas >=3.9.0,<4.0a0
on libgcc >=14
on liblapack >=3.9.0,<4.0a0
on liblzma >=5.8.2,<6.0a0
on libstdcxx >=14
on libzlib >=1.3.1,<2.0a0
on r-base >=4.5,<4.6.0a0
on r-mass
on r-rcpp >=0.11.3

Additional platforms:

linux-aarch64, osx-arm64

Installation¶

You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).

Pixi¶

With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:

pixi global install bioconductor-pcamethods

to add into an existing workspace instead, run:

pixi add bioconductor-pcamethods

In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:

pixi workspace channel add conda-forge
pixi workspace channel add bioconda

Conda¶

With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:

conda install bioconductor-pcamethods

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-pcamethods

with envname being the name of the desired environment.

Container¶

Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:

docker pull quay.io/biocontainers/bioconductor-pcamethods:<tag>

(see bioconductor-pcamethods/tags for valid values for <tag>).

Integrated deployment¶

Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.

Download stats¶

Link to this page¶

Render an badge with the following MarkDown:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/bioconductor-pcamethods/README.html)