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

doi:10.1186/1479-7364-5-1-56

A survey of statistical software for analysing RNA-seq data

Hum Genomics. 2010 Oct;5(1):56-60. doi: 10.1186/1479-7364-5-1-56.

Authors

Dexiang Gao¹, Jihye Kim, Hyunmin Kim, Tzu L Phang, Heather Selby, Aik Choon Tan, Tiejun Tong

Affiliation

¹ Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO 80045, USA. Dexiang.Gao@UCDenver.edu

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.

Publication types

Evaluation Study

MeSH terms

Databases, Nucleic Acid*
Gene Expression Profiling / methods*
Gene Expression Regulation*
Models, Statistical*
Software*