Nucleic Acids Research Advance Access originally published online on March 15, 2008
Nucleic Acids Research 2008 36(8):2630-2638; doi:10.1093/nar/gkn105
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Nucleic Acids Research, 2008, Vol. 36, No. 8 2630-2638
© 2008 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.
Computational Biology |
A space-efficient and accurate method for mapping and aligning cDNA sequences onto genomic sequence
1Department of Intelligence Science and Technology, Graduate School of Informatics, Kyoto University, Yoshida Honmachi, Sakyo-ku, Kyoto 606-8501 and 2National Institute of Advanced Industrial Science and Technology, Computational Biology Research Center, 2-42 Aomi, Koto-ku, Tokyo 135-0064, Japan
*To whom correspondence should be addressed. Tel: +81 75 753 9109; Fax: +81 75 753 9110; Email: o.gotoh{at}i.kyoto-u.ac.jp
Received November 22, 2007. Revised January 30, 2008. Accepted February 25, 2008.
The mapping and alignment of transcripts (cDNA, expressed sequence tag or amino acid sequences) onto a genomic sequence is a fundamental step for genome annotation, including gene finding and analyses of transcriptional activity, alternative splicing and nucleotide polymorphisms. As DNA sequence data of genomes and transcripts are accumulating at an unprecedented rate, steady improvement in accuracy, speed and space requirement in the computational tools for mapping/alignment is desired. We devised a multi-phase heuristic algorithm and implemented it in the development of the stand-alone computer program Spaln (space-efficient spliced alignment). Spaln is reasonably fast and space efficient; it requires <1 Gb of memory to map and align >120 000 Unigene sequences onto the unmasked whole human genome with a conventional computer, finishing the job in <6 h. With artificially introduced noise of various levels, Spaln significantly outperforms other leading alignment programs currently available with respect to the accuracy of mapped exon–intron structures. This performance is achieved without extensive learning procedures to adjust parameter values to a particular organism. According to the handiness and accuracy, Spaln may be used for studies on a wide area of genome analyses.
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