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This is the development version of FEAST; for the stable release version, see FEAST.

FEAture SelcTion (FEAST) for Single-cell clustering

Bioconductor version: Development (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 < at>

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


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

if (!require("BiocManager", quietly = TRUE))

# The following initializes usage of Bioc devel


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


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

The FEAST User's Guide HTML R Script
Reference Manual PDF


biocViews Clustering, FeatureExtraction, Sequencing, SingleCell, Software
Version 1.13.0
In Bioconductor since BioC 3.13 (R-4.1) (3 years)
License GPL-2
Depends R (>= 4.1), mclust, BiocParallel, SummarizedExperiment
Imports SingleCellExperiment, methods, stats, utils, irlba, TSCAN, SC3, matrixStats
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Suggests rmarkdown, Seurat, ggpubr, knitr, testthat (>= 3.0.0), BiocStyle
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Source Package FEAST_1.13.0.tar.gz
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