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

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

20 Citations (Scopus)

Abstract

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
Volume5
Issue number1
DOIs
Publication statusPublished - 1 Oct 2010

Scopus Subject Areas

  • Molecular Medicine
  • Molecular Biology
  • Genetics
  • Drug Discovery

User-Defined Keywords

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

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