recipe bioconductor-slalom

Factorial Latent Variable Modeling of Single-Cell RNA-Seq Data

Homepage:

https://bioconductor.org/packages/3.20/bioc/html/slalom.html

License:

GPL-2

Recipe:

/bioconductor-slalom/meta.yaml

slalom is a scalable modelling framework for single-cell RNA-seq data that uses gene set annotations to dissect single-cell transcriptome heterogeneity, thereby allowing to identify biological drivers of cell-to-cell variability and model confounding factors. The method uses Bayesian factor analysis with a latent variable model to identify active pathways (selected by the user, e.g. KEGG pathways) that explain variation in a single-cell RNA-seq dataset. This an R/C++ implementation of the f-scLVM Python package. See the publication describing the method at https://doi.org/10.1186/s13059-017-1334-8.

package bioconductor-slalom

versions:

1.28.0-0,  1.24.0-0,  1.22.0-0,  1.20.0-1,  1.20.0-0,  1.16.0-2,  1.16.0-1,  1.16.0-0,  1.14.0-0, 

1.28.0-0,  1.24.0-0,  1.22.0-0,  1.20.0-1,  1.20.0-0,  1.16.0-2,  1.16.0-1,  1.16.0-0,  1.14.0-0,  1.12.0-1,  1.12.0-0,  1.10.0-0,  1.8.0-0,  1.6.0-1,  1.4.1-0,  1.4.0-0

depends bioconductor-gseabase:

>=1.68.0,<1.69.0

depends bioconductor-gseabase:

>=1.68.0,<1.69.0a0

depends bioconductor-singlecellexperiment:

>=1.28.0,<1.29.0

depends bioconductor-singlecellexperiment:

>=1.28.0,<1.29.0a0

depends bioconductor-summarizedexperiment:

>=1.36.0,<1.37.0

depends bioconductor-summarizedexperiment:

>=1.36.0,<1.37.0a0

depends libblas:

>=3.9.0,<4.0a0

depends libgcc:

>=13

depends liblapack:

>=3.9.0,<4.0a0

depends libstdcxx:

>=13

depends r-base:

>=4.4,<4.5.0a0

depends r-bh:

depends r-ggplot2:

depends r-rcpp:

>=0.12.8

depends r-rcpparmadillo:

depends r-rsvd:

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-slalom

and update with::

   mamba update bioconductor-slalom

To create a new environment, run:

mamba create --name myenvname bioconductor-slalom

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-slalom:<tag>

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

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