recipe bioconductor-corral

Correspondence Analysis for Single Cell Data

Homepage:

https://bioconductor.org/packages/3.18/bioc/html/corral.html

License:

GPL-2

Recipe:

/bioconductor-corral/meta.yaml

Correspondence analysis (CA) is a matrix factorization method, and is similar to principal components analysis (PCA). Whereas PCA is designed for application to continuous, approximately normally distributed data, CA is appropriate for non-negative, count-based data that are in the same additive scale. The corral package implements CA for dimensionality reduction of a single matrix of single-cell data, as well as a multi-table adaptation of CA that leverages data-optimized scaling to align data generated from different sequencing platforms by projecting into a shared latent space. corral utilizes sparse matrices and a fast implementation of SVD, and can be called directly on Bioconductor objects (e.g., SingleCellExperiment) for easy pipeline integration. The package also includes additional options, including variations of CA to address overdispersion in count data (e.g., Freeman-Tukey chi-squared residual), as well as the option to apply CA-style processing to continuous data (e.g., proteomic TOF intensities) with the Hellinger distance adaptation of CA.

package bioconductor-corral

versions:

1.12.0-0,  1.10.0-0,  1.8.0-0,  1.4.0-0,  1.2.0-0,  1.0.0-2,  1.0.0-1

depends bioconductor-multiassayexperiment:

>=1.28.0,<1.29.0

depends bioconductor-singlecellexperiment:

>=1.24.0,<1.25.0

depends bioconductor-summarizedexperiment:

>=1.32.0,<1.33.0

depends r-base:

>=4.3,<4.4.0a0

depends r-ggplot2:

depends r-ggthemes:

depends r-gridextra:

depends r-irlba:

depends r-matrix:

depends r-pals:

depends r-reshape2:

depends r-transport:

requirements:

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-corral

and update with::

   mamba update bioconductor-corral

To create a new environment, run:

mamba create --name myenvname bioconductor-corral

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-corral:<tag>

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

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