recipe bioconductor-scpca

Sparse Contrastive Principal Component Analysis

Homepage:

https://bioconductor.org/packages/3.20/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 unwanted variation through the use of control data. Also implements and extends cPCA.

package bioconductor-scpca

versions:

1.20.0-0,  1.16.0-0,  1.14.0-0,  1.12.0-0,  1.8.0-0,  1.6.2-0,  1.4.0-1,  1.4.0-0,  1.2.0-0, 

1.20.0-0,  1.16.0-0,  1.14.0-0,  1.12.0-0,  1.8.0-0,  1.6.2-0,  1.4.0-1,  1.4.0-0,  1.2.0-0,  1.0.0-0

depends bioconductor-biocparallel:

>=1.40.0,<1.41.0

depends bioconductor-delayedarray:

>=0.32.0,<0.33.0

depends bioconductor-matrixgenerics:

>=1.18.0,<1.19.0

depends bioconductor-scaledmatrix:

>=1.14.0,<1.15.0

depends r-assertthat:

depends r-base:

>=4.4,<4.5.0a0

depends r-cluster:

depends r-coop:

depends r-dplyr:

depends r-elasticnet:

depends r-kernlab:

depends r-matrix:

depends r-matrixstats:

depends r-origami:

depends r-purrr:

depends r-rdpack:

depends r-rspectra:

depends r-sparsepca:

depends r-stringr:

depends r-tibble:

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 bioconductor-scpca

and update with::

   mamba update bioconductor-scpca

To create a new environment, run:

mamba create --name myenvname bioconductor-scpca

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/bioconductor-scpca:<tag>

(see `bioconductor-scpca/tags`_ for valid values for ``<tag>``)

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