FEAST

FEAture SelcTion (FEAST) for Single-cell clustering


Bioconductor version: Release (3.20)

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.

Author: Kenong Su [aut, cre], Hao Wu [aut]

Maintainer: Kenong Su <kenong.su at emory.edu>

Citation (from within R, enter citation("FEAST")):

Installation

To install this package, start R (version "4.4") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("FEAST")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("FEAST")
The FEAST User's Guide HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews Clustering, FeatureExtraction, Sequencing, SingleCell, Software
Version 1.14.0
In Bioconductor since BioC 3.13 (R-4.1) (3.5 years)
License GPL-2
Depends R (>= 4.1), mclust, BiocParallel, SummarizedExperiment
Imports SingleCellExperiment, methods, stats, utils, irlba, TSCAN, SC3, matrixStats
System Requirements
URL
Bug Reports https://github.com/suke18/FEAST/issues
See More
Suggests rmarkdown, Seurat, ggpubr, knitr, testthat (>= 3.0.0), BiocStyle
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package FEAST_1.14.0.tar.gz
Windows Binary (x86_64) FEAST_1.14.0.zip
macOS Binary (x86_64) FEAST_1.14.0.tgz
macOS Binary (arm64) FEAST_1.13.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/FEAST
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/FEAST
Bioc Package Browser https://code.bioconductor.org/browse/FEAST/
Package Short Url https://bioconductor.org/packages/FEAST/
Package Downloads Report Download Stats