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BioMed Research International
Volume 2014 (2014), Article ID 309650, 16 pages
Research Article

Evaluation and Comparison of Multiple Aligners for Next-Generation Sequencing Data Analysis

1Center for Systems Biology, Soochow University, 1st Shizi Street, Suzhou, Jiangsu 215006, China
2Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou 215123, China
3School of Computer Science and Technology, Soochow University, Suzhou 215006, China

Received 17 December 2013; Accepted 4 February 2014; Published 23 March 2014

Academic Editor: Junfeng Xia

Copyright © 2014 Jing Shang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Next-generation sequencing (NGS) technology has rapidly advanced and generated the massive data volumes. To align and map the NGS data, biologists often randomly select a number of aligners without concerning their suitable feature, high performance, and high accuracy as well as sequence variations and polymorphisms existing on reference genome. This study aims to systematically evaluate and compare the capability of multiple aligners for NGS data analysis. To explore this capability, we firstly performed alignment algorithms comparison and classification. We further used long-read and short-read datasets from both real-life and in silico NGS data for comparative analysis and evaluation of these aligners focusing on three criteria, namely, application-specific alignment feature, computational performance, and alignment accuracy. Our study demonstrated the overall evaluation and comparison of multiple aligners for NGS data analysis. This serves as an important guiding resource for biologists to gain further insight into suitable selection of aligners for specific and broad applications.