Journal of Applied Bioinformatics & Computational BiologyISSN: 2329-9533

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Research Article, J Appl Bioinform Comput Biol Vol: 1 Issue: 1

Speeding Up Large-Scale Next Generation Sequencing Data Analysis with pBWA

Darren Peters1, Xuemei Luo2, Ke Qiu1 and Ping Liang2*
1Department of Computer Science, Brock University, St. Catharines, Ontario,Canada
2Department of Biological Sciences, Brock University, St. Catharines, Ontario,Canada
Corresponding author : Dr. Ping Liang, PhD
Department of Biological Sciences, Brock University, St. Catharines, Ontario, L2S 3A1, Canada
Tel: 905-688-5550; Fax: 905-658-1855
E-mail: [email protected]
Received: October 10, 2012 Accepted: November 23, 2012 Published: November 28, 2012
Citation: Peters D, Luo X, Qiu K, Liang P (2012) Speeding Up Large-Scale Next Generation Sequencing Data Analysis with pBWA. J Appl Bioinform Comput Biol 1:1. doi:10.4172/2329-9533.1000101

Abstract

Speeding Up Large-Scale Next Generation Sequencing Data Analysis with pBWA

Newly available DNA sequencing technologies can generate billions of DNA sequences in a single machine run, making it feasible to obtain an individual’s entire genome sequences very quickly and at a very affordable cost. These personal genome sequences can be used to identify genetic variations associated with variable traits, but they must first be aligned to a reference genome sequence using computer algorithms that make use of approximate string matching methods.

Keywords: Next-Generation sequencing; Burrows-Wheeler Transform (BWT); Parallel computing; Cluster computing; Short sequence alignment

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