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Bioinformatics Advance Access originally published online on June 23, 2009
Bioinformatics 2009 25(17):2194-2199; doi:10.1093/bioinformatics/btp383
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© 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.

Swift: primary data analysis for the Illumina Solexa sequencing platform

Nava Whiteford 1,*,{dagger}, Tom Skelly 1, Christina Curtis 2, Matt E. Ritchie 3, Andrea Löhr 4, Alexander Wait Zaranek 5, Irina Abnizova 1 and Clive Brown 1,{dagger}

1 Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, 2 Department of Oncology, University of Cambridge, CRUK Cambridge Research Institute, Li Ka Shing Centre, Robinson Way Cambridge CB2 0RE, UK, 3 Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria 3052, Australia, 4 Harvard-Smithsonian Center for Astrophysics, 60 Garden Street Cambridge, MA 02138 and 5 Harvard Medical School, Genetics, 77 Avenue Louis Pasteur, Boston, MA 02115, USA

* To whom correspondence should be addressed.


  Abstract

Motivation: Primary data analysis methods are of critical importance in second generation DNA sequencing. Improved methods have the potential to increase yield and reduce the error rates. Openly documented analysis tools enable the user to understand the primary data, this is important for the optimization and validity of their scientific work.

Results: In this article, we describe Swift, a new tool for performing primary data analysis on the Illumina Solexa Sequencing Platform. Swift is the first tool, outside of the vendors own software, which completes the full analysis process, from raw images through to base calls. As such it provides an alternative to, and independent validation of, the vendor supplied tool. Our results show that Swift is able to increase yield by 13.8%, at comparable error rate.

Availability and Implementation: Swift is implemented in C++and supported under Linux. It is supplied under an open source license (LGPL3), allowing researchers to build upon the platform. Swift is available from http://swiftng.sourceforge.net.

Contact: new{at}sgenomics.org; nava.whiteford{at}nanoporetech.com

Supplementary information: Supplementary data are available at Bioinformatics online.

{dagger}Present Address: Oxford Nanopore Technologies Sandy Lane, Kidlington, OX5 1PF, UK.

Associate Editor: Joaquin Dopazo

Received on February 22, 2009; revised on May 4, 2009; accepted on June 18, 2009

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