recipe bioconductor-feast

FEAture SelcTion (FEAST) for Single-cell clustering

Homepage

https://bioconductor.org/packages/3.14/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

1.2.0-1,  1.2.0-0,  1.0.0-0

Depends

• bioconductor-biocparallel >=1.28.0,<1.29.0

• bioconductor-sc3 >=1.22.0,<1.23.0

• bioconductor-singlecellexperiment >=1.16.0,<1.17.0

• bioconductor-summarizedexperiment >=1.24.0,<1.25.0

• bioconductor-tscan >=1.32.0,<1.33.0

• libblas >=3.8.0,<4.0a0

• libgcc-ng >=10.3.0

• liblapack >=3.8.0,<4.0a0

• r-base >=4.1,<4.2.0a0

• r-irlba

• r-matrixstats

• r-mclust

Required By

Installation

With an activated Bioconda channel (see 2. Set up channels), install with:

conda install bioconductor-feast

and update with:

conda update bioconductor-feast

or use the docker container:

docker pull quay.io/biocontainers/bioconductor-feast:<tag>

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

Download stats

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