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Briefings in Bioinformatics Advance Access originally published online on May 23, 2006
Briefings in Bioinformatics 2007 8(1):6-21; doi:10.1093/bib/bbl015
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© The Author 2006. Published by Oxford University Press. For Permissions, please email: journals.permissions@oxfordjournals.org

A hitchhiker's guide to expressed sequence tag (EST) analysis

Shivashankar H. Nagaraj, Robin B. Gasser and Shoba Ranganathan

Corresponding author. Prof. Shoba Ranganathan, Department of Chemistry and Biomolecular Sciences & Biotechnology Research Institute, Macquarie University, NSW 2109, Australia, Tel: +61-2-9850 6262; Fax: +61-2-9850 8313; E-mail: shoba{at}els.mq.edu.au

Expressed sequence tag (EST) sequencing projects are underway for numerous organisms, generating millions of short, single-pass nucleotide sequence reads, accumulating in EST databases. Extensive computational strategies have been developed to organize and analyse both small- and large-scale EST data for gene discovery, transcript and single nucleotide polymorphism analysis as well as functional annotation of putative gene products.

We provide an overview of the significance of ESTs in the genomic era, their properties and the applications of ESTs. Methods adopted for each step of EST analysis by various research groups have been compared. Challenges that lie ahead in organizing and analysing the ever increasing EST data have also been identified.

The most appropriate software tools for EST pre-processing, clustering and assembly, database matching and functional annotation have been compiled (available online from http://biolinfo.org/EST). We propose a road map for EST analysis to accelerate the effective analyses of EST data sets. An investigation of EST analysis platforms reveals that they all terminate prior to downstream functional annotation including gene ontologies, motif/pattern analysis and pathway mapping.

Keywords: expressed sequence tags, sequence assembly and clustering, database similarity searches, functional annotation, conceptual translation, transcriptome analysis


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