A survey of statistical software for analysing RNA-seq data

Dexiang Gao, Jihye Kim, Hyunmin Kim, Tzu L. Phang, Heather Selby, Aik-Choon Tan, Tiejun Tong

Research output: Contribution to journalArticle

13 Citations (Scopus)


High-throughput RNA sequencing is rapidly emerging as a favourite method for gene expression studies. We review three software packages - edgeR, DEGseq and baySeq - from Bioconductor http://bioconductor.org for analysing RNA-sequencing data. We focus on three aspects: normalisation, statistical models and the testing employed on these methods. We also discuss the advantages and limitations of these software packages.

Original languageEnglish
Pages (from-to)56-60
Number of pages5
JournalHuman Genomics
Issue number1
Publication statusPublished - 2010 Oct 1
Externally publishedYes



  • normalisation
  • RNA-sequencing analysis
  • sequencing data
  • statistical software

ASJC Scopus subject areas

  • Drug Discovery
  • Genetics
  • Molecular Biology
  • Molecular Medicine

Cite this

Gao, D., Kim, J., Kim, H., Phang, T. L., Selby, H., Tan, A-C., & Tong, T. (2010). A survey of statistical software for analysing RNA-seq data. Human Genomics, 5(1), 56-60.