recipe bioconductor-scmerge

scMerge: Merging multiple batches of scRNA-seq data

Homepage:

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

License:

GPL-3

Recipe:

/bioconductor-scmerge/meta.yaml

Like all gene expression data, single-cell data suffers from batch effects and other unwanted variations that makes accurate biological interpretations difficult. The scMerge method leverages factor analysis, stably expressed genes (SEGs) and (pseudo-) replicates to remove unwanted variations and merge multiple single-cell data. This package contains all the necessary functions in the scMerge pipeline, including the identification of SEGs, replication-identification methods, and merging of single-cell data.

package bioconductor-scmerge

versions:

1.18.0-0,  1.16.0-0,  1.14.0-0,  1.10.0-0,  1.8.0-0,  1.6.0-1,  1.6.0-0,  1.4.0-0,  1.2.0-0, 

1.18.0-0,  1.16.0-0,  1.14.0-0,  1.10.0-0,  1.8.0-0,  1.6.0-1,  1.6.0-0,  1.4.0-0,  1.2.0-0,  1.0.0-1

depends bioconductor-batchelor:

>=1.18.0,<1.19.0

depends bioconductor-biocneighbors:

>=1.20.0,<1.21.0

depends bioconductor-biocparallel:

>=1.36.0,<1.37.0

depends bioconductor-biocsingular:

>=1.18.0,<1.19.0

depends bioconductor-delayedarray:

>=0.28.0,<0.29.0

depends bioconductor-delayedmatrixstats:

>=1.24.0,<1.25.0

depends bioconductor-m3drop:

>=1.28.0,<1.29.0

depends bioconductor-s4vectors:

>=0.40.0,<0.41.0

depends bioconductor-scater:

>=1.30.0,<1.31.0

depends bioconductor-scran:

>=1.30.0,<1.31.0

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-cluster:

depends r-cvtools:

depends r-distr:

depends r-igraph:

depends r-proxyc:

depends r-ruv:

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-scmerge

and update with::

   mamba update bioconductor-scmerge

To create a new environment, run:

mamba create --name myenvname bioconductor-scmerge

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-scmerge:<tag>

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

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