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

• Published in: PloS one Vol. 9; no. 8; p. e103833
• Main Authors: Suzuki, Shuji, Kakuta, Masanori, Ishida, Takashi, Akiyama, Yutaka
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 06.08.2014; Public Library of Science (PLoS)
• Subjects: 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
• DOI: 10.1371/journal.pone.0103833

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.