Skip Navigation


Bioinformatics Advance Access originally published online on April 8, 2009
Bioinformatics 2009 25(11):1363-1369; doi:10.1093/bioinformatics/btp236
This Article
Right arrow Full Text Freely available
Right arrow FREE Full Text (Print PDF) Freely available
Right arrowOA All Versions of this Article:
25/11/1363    most recent
btp236v1
Right arrow Comments: Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when Comments are posted
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Search for citing articles in:
ISI Web of Science (1)
Google Scholar
Right arrow Articles by Schatz, M. C.
PubMed
Right arrow PubMed Citation
Right arrow Articles by Schatz, M. C.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© 2009 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

CloudBurst: highly sensitive read mapping with MapReduce

Michael C. Schatz *

Center for Bioinformatics and Computational Biology, University of Maryland, College Park MD 20742, USA

*To whom correspondence should be addressed.


  Abstract

Motivation: Next-generation DNA sequencing machines are generating an enormous amount of sequence data, placing unprecedented demands on traditional single-processor read-mapping algorithms. CloudBurst is a new parallel read-mapping algorithm optimized for mapping next-generation sequence data to the human genome and other reference genomes, for use in a variety of biological analyses including SNP discovery, genotyping and personal genomics. It is modeled after the short read-mapping program RMAP, and reports either all alignments or the unambiguous best alignment for each read with any number of mismatches or differences. This level of sensitivity could be prohibitively time consuming, but CloudBurst uses the open-source Hadoop implementation of MapReduce to parallelize execution using multiple compute nodes.

Results: CloudBurst's running time scales linearly with the number of reads mapped, and with near linear speedup as the number of processors increases. In a 24-processor core configuration, CloudBurst is up to 30 times faster than RMAP executing on a single core, while computing an identical set of alignments. Using a larger remote compute cloud with 96 cores, CloudBurst improved performance by >100-fold, reducing the running time from hours to mere minutes for typical jobs involving mapping of millions of short reads to the human genome.

Availability: CloudBurst is available open-source as a model for parallelizing algorithms with MapReduce at http://cloudburst-bio.sourceforge.net/.

Contact: mschatz{at}umiacs.umd.edu

Associate Editor: Alfenso Valencia

Received on November 25, 2008; revised on March 12, 2009; accepted on April 3, 2009

Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 BioinformaticsHome page
A. D. Smith, W.-Y. Chung, E. Hodges, J. Kendall, G. Hannon, J. Hicks, Z. Xuan, and M. Q. Zhang
Updates to the RMAP short-read mapping software
Bioinformatics, November 1, 2009; 25(21): 2841 - 2842.
[Abstract] [Full Text] [PDF]

Home page
 Brief BioinformHome page
D. S. Horner, G. Pavesi, T. Castrignano, P. D. De Meo, S. Liuni, M. Sammeth, E. Picardi, and G. Pesole
Bioinformatics approaches for genomics and post genomics applications of next-generation sequencing
Brief Bioinform, October 27, 2009; (2009) bbp046v1.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
H. Li and R. Durbin
Fast and accurate short read alignment with Burrows-Wheeler transform
Bioinformatics, July 15, 2009; 25(14): 1754 - 1760.
[Abstract] [Full Text] [PDF]


Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.