recipe bioconductor-scbfa

A dimensionality reduction tool using gene detection pattern to mitigate noisy expression profile of scRNA-seq



GPL-3 + file LICENSE



This package is designed to model gene detection pattern of scRNA-seq through a binary factor analysis model. This model allows user to pass into a cell level covariate matrix X and gene level covariate matrix Q to account for nuisance variance(e.g batch effect), and it will output a low dimensional embedding matrix for downstream analysis.

package bioconductor-scbfa

(downloads) docker_bioconductor-scbfa



depends bioconductor-deseq2:


depends bioconductor-singlecellexperiment:


depends bioconductor-summarizedexperiment:


depends bioconductor-zinbwave:


depends r-base:


depends r-copula:

depends r-ggplot2:

depends r-mass:

depends r-matrix:

depends r-seurat:



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-scbfa

and update with::

   mamba update bioconductor-scbfa

To create a new environment, run:

mamba create --name myenvname bioconductor-scbfa

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<tag>

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

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