# --------------------------------------------
# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# --------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "FEAST" in publications use:'
type: software
license: GPL-2.0-only
title: 'FEAST: FEAture SelcTion (FEAST) for Single-cell clustering'
version: 1.13.0
abstract: '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.'
authors:
- family-names: Su
  given-names: Kenong
  email: kenong.su@emory.edu
- family-names: Wu
  given-names: Hao
  email: hao.wu@emory.edu
preferred-citation:
  type: article
  title: Accurate feature selection improves single-cell RNA-seq cell clustering
  authors:
  - family-names: Su
    given-names: Kenong
    email: kenong.su@emory.edu
  - family-names: Yu
    given-names: Tianwei
  - family-names: Wu
    given-names: Hao
    email: hao.wu@emory.edu
  year: '2021'
  journal: Briefings in Bioinformatics
repository: https://bioc.r-universe.dev
repository-code: https://github.com/suke18/FEAST
url: https://github.com/suke18/FEAST
date-released: '2021-09-07'
contact:
- family-names: Su
  given-names: Kenong
  email: kenong.su@emory.edu