recipe bioconductor-pvca

Principal Variance Component Analysis (PVCA)

Homepage

https://bioconductor.org/packages/3.11/bioc/html/pvca.html

License

LGPL (>= 2.0)

Recipe

/bioconductor-pvca/meta.yaml

Links

biotools: pvca, doi: 10.1002/9780470685983.ch12

This package contains the function to assess the batch sourcs by fitting all “sources” as random effects including two-way interaction terms in the Mixed Model(depends on lme4 package) to selected principal components, which were obtained from the original data correlation matrix. This package accompanies the book “Batch Effects and Noise in Microarray Experiements, chapter 12.

package bioconductor-pvca

Versions

1.28.0-0, 1.26.0-0, 1.24.0-1, 1.22.0-0, 1.20.0-0, 1.18.0-0

Depends

• bioconductor-biobase >=2.48.0,<2.49.0

• bioconductor-vsn >=3.56.0,<3.57.0

• r-base >=4.0,<4.1.0a0

• r-lme4

• r-matrix

Required By

• bioconductor-probatch

• r-statvisual

Installation

With an activated Bioconda channel (see 2. Set up channels), install with:

conda install bioconductor-pvca

and update with:

conda update bioconductor-pvca

or use the docker container:

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

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

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-pvca/README.html)