Hardcastle, J T (2024). baySeq: empirical Bayesian methods for identifying differential expression in sequence count data.. doi:10.18129/B9.bioc.baySeq, https://github.com/SamGG/baySeq/baySeq - R package version 2.41.0, http://www.bioconductor.org/packages/baySeq.
Hardcastle, J T (2016 Jan 15). “Generalized empirical Bayesian methods for discovery of differential data in high-throughput biology.” Bioinformatics. doi:10.1093/bioinformatics/btv569, https://academic.oup.com/bioinformatics/article/32/2/195/1744387.
Hardcastle, J T, Kelly, A K (2010 Aug 10). “baySeq: empirical Bayesian methods for identifying differential expression in sequence count data.” BMC Bioinformatics. doi:10.1186/1471-2105-11-422, https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-11-422.