recipe bioconductor-feast

FEAture SelcTion (FEAST) for Single-cell clustering

Homepage:

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

License:

GPL-2

Recipe:

/bioconductor-feast/meta.yaml

Cell clustering is one of the most important and commonly performed tasks in single-cell RNA sequencing (scRNA-seq) data analysis. An important step in cell clustering is to select a subset of genes (referred to as “features”), whose expression patterns will then be used for downstream clustering. A good set of features should include the ones that distinguish different cell types, and the quality of such set could have significant impact on the clustering accuracy. FEAST is an R library for selecting most representative features before performing the core of scRNA-seq clustering. It can be used as a plug-in for the etablished clustering algorithms such as SC3, TSCAN, SHARP, SIMLR, and Seurat. The core of FEAST algorithm includes three steps: 1. consensus clustering; 2. gene-level significance inference; 3. validation of an optimized feature set.

package bioconductor-feast

versions:

1.10.0-0,  1.8.0-0,  1.6.0-1,  1.6.0-0,  1.2.0-2,  1.2.0-1,  1.2.0-0,  1.0.0-0

depends bioconductor-biocparallel:

>=1.36.0,<1.37.0

depends bioconductor-biocparallel:

>=1.36.0,<1.37.0a0

depends bioconductor-sc3:

>=1.30.0,<1.31.0

depends bioconductor-sc3:

>=1.30.0,<1.31.0a0

depends bioconductor-singlecellexperiment:

>=1.24.0,<1.25.0

depends bioconductor-singlecellexperiment:

>=1.24.0,<1.25.0a0

depends bioconductor-summarizedexperiment:

>=1.32.0,<1.33.0

depends bioconductor-summarizedexperiment:

>=1.32.0,<1.33.0a0

depends bioconductor-tscan:

>=1.40.0,<1.41.0

depends bioconductor-tscan:

>=1.40.0,<1.41.0a0

depends libblas:

>=3.9.0,<4.0a0

depends libgcc-ng:

>=12

depends liblapack:

>=3.9.0,<4.0a0

depends r-base:

>=4.3,<4.4.0a0

depends r-irlba:

depends r-matrixstats:

depends r-mclust:

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-feast

and update with::

   mamba update bioconductor-feast

To create a new environment, run:

mamba create --name myenvname bioconductor-feast

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-feast:<tag>

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

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