# --------------------------------------------
# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# --------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "baySeq" in publications use:'
type: software
license: GPL-3.0-only
title: 'baySeq: Empirical Bayesian analysis of patterns of differential expression
  in count data'
version: 2.39.0
doi: 10.18129/B9.bioc.baySeq
identifiers:
- type: doi
  value: 10.32614/CRAN.package.baySeq
abstract: This package identifies differential expression in high-throughput 'count'
  data, such as that derived from next-generation sequencing machines, calculating
  estimated posterior likelihoods of differential expression (or more complex hypotheses)
  via empirical Bayesian methods.
authors:
- family-names: Hardcastle
  given-names: Thomas J.
- family-names: Granjeaud
  given-names: Samuel
  email: samuel.granjeaud@inserm.fr
  orcid: https://orcid.org/0000-0001-9245-1535
preferred-citation:
  type: manual
  title: 'baySeq: empirical Bayesian methods for identifying differential expression
    in sequence count data.'
  authors:
  - name: Hardcastle
  - family-names: J
    given-names: Thomas
  year: '2024'
  url: http://www.bioconductor.org/packages/baySeq
  notes: https://github.com/SamGG/baySeq/baySeq - R package version 2.39.0
  doi: 10.18129/B9.bioc.baySeq
repository: https://bioc.r-universe.dev
repository-code: https://github.com/samgg/baySeq
commit: c69daa17a6e39813c7c81e1a1b9d8bc74e15f9e9
url: https://github.com/samgg/baySeq
date-released: '2012-12-20'
contact:
- family-names: Granjeaud
  given-names: Samuel
  email: samuel.granjeaud@inserm.fr
  orcid: https://orcid.org/0000-0001-9245-1535
references:
- type: article
  title: Generalized empirical Bayesian methods for discovery of differential data
    in high-throughput biology.
  authors:
  - name: Hardcastle
  - family-names: J
    given-names: Thomas
  year: 2016 Jan 15
  journal: Bioinformatics
  doi: 10.1093/bioinformatics/btv569
  url: https://academic.oup.com/bioinformatics/article/32/2/195/1744387
- type: article
  title: 'baySeq: empirical Bayesian methods for identifying differential expression
    in sequence count data.'
  authors:
  - name: Hardcastle
  - family-names: J
    given-names: Thomas
  - name: Kelly
  - family-names: A
    given-names: Krystyna
  year: 2010 Aug 10
  journal: BMC Bioinformatics
  doi: 10.1186/1471-2105-11-422
  url: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-11-422