Abstract
DNA sequences are translated into protein coding sequences and then further assigned to protein families in metagenomic analyses, because of the need for sensitivity. However, huge amounts of sequence data create the problem that even general homology search analyses using BLASTX become difficult in terms of computational cost. We designed a new homology search algorithm that finds seed sequences based on the suffix arrays of a query and a database, and have implemented it as GHOSTX. GHOSTX achieved approximately 131-165 times acceleration over a BLASTX search at similar levels of sensitivity. GHOSTX is distributed under the BSD 2-clause license and is available for download at http://www.bi.cs.titech.ac.jp/ghostx/. Currently, sequencing technology continues to improve, and sequencers are increasingly producing larger and larger quantities of data. This explosion of sequence data makes computational analysis with contemporary tools more difficult. We offer this tool as a potential solution to this problem.
Keywords
Sequence databaseComputer scienceCompressed suffix arraySmith–Waterman algorithmAlgorithmDatabase search engineSuffix arraySequence alignmentHomology (biology)MetagenomicsSearch algorithmSuffix treeData miningComputational biologyData structureBiologySearch engineInformation retrievalGeneticsPeptide sequence
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Publication Info
- Year
- 2014
- Type
- article
- Volume
- 9
- Issue
- 8
- Pages
- e103833-e103833
- Citations
- 91
- Access
- Closed
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Cite This
Shuji Suzuki,
Masanori Kakuta,
Takashi Ishida
et al.
(2014).
GHOSTX: An Improved Sequence Homology Search Algorithm Using a Query Suffix Array and a Database Suffix Array.
PLoS ONE
, 9
(8)
, e103833-e103833.
https://doi.org/10.1371/journal.pone.0103833
Identifiers
- DOI
- 10.1371/journal.pone.0103833