Evaluation of RNA-Seq software in gene expression quantification

Yan Ji, Ziliang Qian, Jia Wei

Innovation Center China, AstraZeneca, Shanghai, China.
R & D Information, AstraZeneca, Shanghai, China.

DOI: 10.4236/jbise.2013.64059                

Abstract

High-throughput RNA sequencing (RNA-Seq) promises a complete annotation and quantification of all genes and their isoforms across samples. Because sequencing reads from this new technology are shorter than transcripts from which they are derived, expression estimation with RNA-Seq requires increasingly complex computational methods. In recent years, a number of expression quantification methods have been published from both public and commercial sources. Here we presented an overview of these attempts on quantifying gene expression. We then defined a set of criteria and compared the performance of several programs based on these criteria, and we further provided advices on selecting suitable tools for different biological applications.

Keywords

RNA-Seq; Next Generation Sequencing

Conflicts of Interest

The authors declare no conflicts of interest.

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