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 journalReview article

15 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


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

ASJC Scopus subject areas

  • Molecular Medicine
  • Molecular Biology
  • Genetics
  • Drug Discovery

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  • 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. https://doi.org/10.1186/1479-7364-5-1-56