- recipe bioconductor-feast
FEAture SelcTion (FEAST) for Single-cell clustering
- Homepage:
- License:
GPL-2
- Recipe:
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:
1.6.0-0
,1.2.0-2
,1.2.0-1
,1.2.0-0
,1.0.0-0
- Depends:
bioconductor-biocparallel
>=1.32.0,<1.33.0
bioconductor-sc3
>=1.26.0,<1.27.0
bioconductor-singlecellexperiment
>=1.20.0,<1.21.0
bioconductor-summarizedexperiment
>=1.28.0,<1.29.0
bioconductor-tscan
>=1.36.0,<1.37.0
libblas
>=3.9.0,<4.0a0
libgcc-ng
>=12
liblapack
>=3.9.0,<4.0a0
r-base
>=4.2,<4.3.0a0
- Required By:
Installation
With an activated Bioconda channel (see 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¶
Link to this page¶
Render an badge with the following MarkDown:
[](http://bioconda.github.io/recipes/bioconductor-feast/README.html)