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
Affiliated Institutions
Related Publications
GAGE: A critical evaluation of genome assemblies and assembly algorithms
New sequencing technology has dramatically altered the landscape of whole-genome sequencing, allowing scientists to initiate numerous projects to decode the genomes of previousl...
Protein homology detection by HMM–HMM comparison
Abstract Motivation: Protein homology detection and sequence alignment are at the basis of protein structure prediction, function prediction and evolution. Results: We have gene...
VSEARCH: a versatile open source tool for metagenomics
Background VSEARCH is an open source and free of charge multithreaded 64-bit tool for processing and preparing metagenomics, genomics and population genomics nucleotide sequence...
pGenTHREADER and pDomTHREADER: new methods for improved protein fold recognition and superfamily discrimination
Abstract Motivation: Generation of structural models and recognition of homologous relationships for unannotated protein sequences are fundamental problems in bioinformatics. Im...
Search and clustering orders of magnitude faster than BLAST
Abstract Motivation: Biological sequence data is accumulating rapidly, motivating the development of improved high-throughput methods for sequence classification. Results: UBLAS...
Publication Info
- Year
- 2014
- Type
- article
- Volume
- 9
- Issue
- 8
- Pages
- e103833-e103833
- Citations
- 91
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
91
OpenAlex
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