A survey of sequence alignment algorithms for next-generation sequencing.

Brief Bioinform
Authors
Keywords
Abstract

Rapidly evolving sequencing technologies produce data on an unparalleled scale. A central challenge to the analysis of this data is sequence alignment, whereby sequence reads must be compared to a reference. A wide variety of alignment algorithms and software have been subsequently developed over the past two years. In this article, we will systematically review the current development of these algorithms and introduce their practical applications on different types of experimental data. We come to the conclusion that short-read alignment is no longer the bottleneck of data analyses. We also consider future development of alignment algorithms with respect to emerging long sequence reads and the prospect of cloud computing.

Year of Publication
2010
Journal
Brief Bioinform
Volume
11
Issue
5
Pages
473-83
Date Published
2010 Sep
ISSN
1477-4054
URL
DOI
10.1093/bib/bbq015
PubMed ID
20460430
PubMed Central ID
PMC2943993
Links
Grant list
1U01HG005208-01 / HG / NHGRI NIH HHS / United States
1U01HG005210-01 / HG / NHGRI NIH HHS / United States