GHOSTX: An Improved Sequence Homology Search Algorithm Using a Query Suffix Array and a Database Suffix Array

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...

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Veröffentlicht in:PloS one Jg. 9; H. 8; S. e103833
Hauptverfasser: Suzuki, Shuji, Kakuta, Masanori, Ishida, Takashi, Akiyama, Yutaka
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States Public Library of Science 06.08.2014
Public Library of Science (PLoS)
Schlagworte:
Algorithms
Alternating current
Analysis
Arrays
Bioinformatics
Biology and Life Sciences
Computer applications
Cost analysis
Data bases
Data processing
Databases, Genetic
Deoxyribonucleic acid
DNA
Downloading
Engineering
Gene sequencing
Genomes
Homology
Information science
Nucleotide sequence
Protein families
Proteins
Queries
Research and Analysis Methods
Search algorithms
Seeds
Sensitivity
Sensitivity analysis
Sequence Alignment - methods
Sequence Homology
Software
Japan
ISSN:1932-6203, 1932-6203
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Zusammenfassung: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.
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Competing Interests: The authors have declared that no competing interests exist.
Conceived and designed the experiments: SS MK TI YA. Performed the experiments: SS. Analyzed the data: SS. Contributed reagents/materials/analysis tools: SS MK TI. Contributed to the writing of the manuscript: SS MK TI YA.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0103833