FEAST

DOI: 10.18129/B9.bioc.FEAST  

FEAture SelcTion (FEAST) for Single-cell clustering

Bioconductor version: Release (3.16)

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>

Installation

To install this package, start R (version "4.2") 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")

 

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

Details

biocViews	Clustering, FeatureExtraction, Sequencing, SingleCell, Software
Version	1.6.0
In Bioconductor since	BioC 3.13 (R-4.1) (2 years)
License	GPL-2
Depends	R (>= 4.1), mclust, BiocParallel, SummarizedExperiment
Imports	SingleCellExperiment, methods, stats, utils, irlba, TSCAN, SC3, matrixStats
LinkingTo
Suggests	rmarkdown, Seurat, ggpubr, knitr, testthat (>= 3.0.0), BiocStyle
SystemRequirements
Enhances
URL
BugReports	https://github.com/suke18/FEAST/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report

Package Archives

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

Source Package	FEAST_1.6.0.tar.gz
Windows Binary	FEAST_1.6.0.zip (64-bit only)
macOS Binary (x86_64)	FEAST_1.6.0.tgz
macOS Binary (arm64)	FEAST_1.6.0.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