Article

OASIS: an online and accurate technique for local-alignment searches on biological sequences

Authors:

Jignesh M. Patel,

Shruti KasettyAuthors Info & Claims

VLDB '03: Proceedings of the 29th international conference on Very large data bases - Volume 29

Pages 910 - 921

Published: 09 September 2003 Publication History

Abstract

A common query against large protein and gene sequence data sets is to locate targets that are similar to an input query sequence. The current set of popular search tools, such as BLAST, employ heuristics to improve the speed of such searches. However, such heuristics can sometimes miss targets, which in many cases is undesirable. The alternative to BLAST is to use an accurate algorithm, such as the Smith-Waterman (S-W) algorithm. However, these accurate algorithms are computationally very expensive, which limits their use in practice. This paper takes on the challenge of designing an accurate and efficient algorithm for evaluating local-alignment searches.

To meet this goal, we propose a novel search algorithm, called OASIS. This algorithm employs a dynamic programming A^*-search driven by a suffix-tree index that is built on the input data set. We experimentally evaluate OASIS and demonstrate that for an important class of searches, in which the query sequence lengths are small, OASIS is more than an order of magnitude faster than S-W. In addition, the speed of OASIS is comparable to BLAST. Furthermore, OASIS returns results in decreasing order of the matching score, making it possible to use OASIS in an online setting. Consequently, we believe that it may now be practically feasible to query large biological sequence data sets using an accurate local-alignment search algorithm.

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Index Terms

OASIS: an online and accurate technique for local-alignment searches on biological sequences

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VLDB '03: Proceedings of the 29th international conference on Very large data bases - Volume 29

September 2003

1134 pages

ISBN:0127224424

Sponsors

VLDB Endowment: Very Large Database Endowment

Publisher

VLDB Endowment

Publication History

Published: 09 September 2003

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VLDB '03

Sponsor:

VLDB Endowment

VLDB '03: Very large data bases

September 9 - 12, 2003

Berlin, Germany

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Cited By

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Shun JBlelloch G(2014)A simple parallel cartesian tree algorithm and its application to parallel suffix tree constructionACM Transactions on Parallel Computing10.1145/26616531:1(1-20)Online publication date: 3-Oct-2014
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Comin MFarreras MDongarra JBlas JCarretero J(2013)Efficient parallel construction of suffix trees for genomes larger than main memoryProceedings of the 20th European MPI Users' Group Meeting10.1145/2488551.2488579(211-216)Online publication date: 15-Sep-2013
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Comin MAntonello M(2013)Fast computation of entropic profiles for the detection of conservation in genomesProceedings of the 8th IAPR international conference on Pattern Recognition in Bioinformatics10.1007/978-3-642-39159-0_25(277-288)Online publication date: 17-Jun-2013
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Yang XLiu HWang B(2012)ALAEProceedings of the VLDB Endowment10.14778/2350229.23502655:11(1507-1518)Online publication date: 1-Jul-2012
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Hoang DKin S(2011)Compressed directed acyclic word graph with application in local alignmentProceedings of the 17th annual international conference on Computing and combinatorics10.5555/2033094.2033138(503-518)Online publication date: 14-Aug-2011
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Ghoting AMakarychev K(2010)I/O efficient algorithms for serial and parallel suffix tree constructionACM Transactions on Database Systems10.1145/1862919.186292235:4(1-37)Online publication date: 12-Oct-2010
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