recipe bioconductor-scpca

Sparse Contrastive Principal Component Analysis

Homepage

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

License

MIT + file LICENSE

Recipe

/bioconductor-scpca/meta.yaml

A toolbox for sparse contrastive principal component analysis (scPCA) of high-dimensional biological data. scPCA combines the stability and interpretability of sparse PCA with contrastive PCA's ability to disentangle biological signal from techical noise through the use of control data. Also implements and extends cPCA.

package bioconductor-scpca

Versions

1.2.0-0,  1.0.0-0

Depends

• bioconductor-biocparallel >=1.22.0,<1.23.0

• r-assertthat

• r-base >=4.0,<4.1.0a0

• r-cluster

• r-dplyr

• r-elasticnet

• r-kernlab

• r-matrixstats

• r-origami

• r-purrr

• r-rdpack

• r-sparsepca

• r-stringr

• r-tibble

Required By

Installation

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

conda install bioconductor-scpca

and update with:

conda update bioconductor-scpca

or use the docker container:

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

(see bioconductor-scpca/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-scpca/README.html)