recipe bioconductor-scfeatures

scFeatures: Multi-view representations of single-cell and spatial data for disease outcome prediction

Homepage:

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

License:

GPL-3

Recipe:

/bioconductor-scfeatures/meta.yaml

scFeatures constructs multi-view representations of single-cell and spatial data. scFeatures is a tool that generates multi-view representations of single-cell and spatial data through the construction of a total of 17 feature types. These features can then be used for a variety of analyses using other software in Biocondutor.

package bioconductor-scfeatures

versions:

1.2.0-0,  1.0.0-0

depends bioconductor-aucell:

>=1.24.0,<1.25.0

depends bioconductor-biocparallel:

>=1.36.0,<1.37.0

depends bioconductor-delayedarray:

>=0.28.0,<0.29.0

depends bioconductor-delayedmatrixstats:

>=1.24.0,<1.25.0

depends bioconductor-ensdb.hsapiens.v79:

>=2.99.0,<2.100.0

depends bioconductor-ensdb.mmusculus.v79:

>=2.99.0,<2.100.0

depends bioconductor-ensembldb:

>=2.26.0,<2.27.0

depends bioconductor-gsva:

>=1.50.0,<1.51.0

depends bioconductor-matrixgenerics:

>=1.14.0,<1.15.0

depends bioconductor-singlecellsignalr:

>=1.14.0,<1.15.0

depends bioconductor-spatialexperiment:

>=1.12.0,<1.13.0

depends bioconductor-summarizedexperiment:

>=1.32.0,<1.33.0

depends r-ape:

depends r-base:

>=4.3,<4.4.0a0

depends r-cli:

depends r-dplyr:

depends r-dt:

depends r-glue:

depends r-gtools:

depends r-msigdbr:

depends r-proxyc:

depends r-reshape2:

depends r-rmarkdown:

depends r-seurat:

depends r-spatstat.explore:

depends r-spatstat.geom:

depends r-tidyr:

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-scfeatures

and update with::

   mamba update bioconductor-scfeatures

To create a new environment, run:

mamba create --name myenvname bioconductor-scfeatures

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-scfeatures:<tag>

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

Download stats

Link to this page

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