Bioconductor version: Release (3.14)
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")
):
To install this package, start R (version "4.1") 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.
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 |
Reference Manual | ||
Text | NEWS |
biocViews | Clustering, FeatureExtraction, Sequencing, SingleCell, Software |
Version | 1.2.0 |
In Bioconductor since | BioC 3.13 (R-4.1) (1 year) |
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 |
Follow Installation instructions to use this package in your R session.
Source Package | FEAST_1.2.0.tar.gz |
Windows Binary | FEAST_1.2.0.zip (32- & 64-bit) |
macOS 10.13 (High Sierra) | FEAST_1.2.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/FEAST |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/FEAST |
Package Short Url | https://bioconductor.org/packages/FEAST/ |
Package Downloads Report | Download Stats |
Old Source Packages for BioC 3.14 | Source Archive |
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