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- Title
Faster sequence homology searches by clustering subsequences.
- Authors
Shuji Suzuki; Masanori Kakuta; Takashi Ishida; Yutaka Akiyama
- Abstract
Motivation: Sequence homology searches are used in various fields. New sequencing technologies produce huge amounts of sequence data, which continuously increase the size of sequence databases. As a result, homology searches require large amounts of computational time, especially for metagenomic analysis. Results: We developed a fast homology search method based on database subsequence clustering, and implemented it as GHOSTZ. This method clusters similar subsequences from a database to perform an efficient seed search and ungapped extension by reducing alignment candidates based on triangle inequality. The database subsequence clustering technique achieved an ~2-fold increase in speed without a large decrease in search sensitivity. When we measured with metagenomic data, GHOSTZ is ~2.2-2.8 times faster than RAPSearch and is ~185-261 times faster than BLASTX.
- Subjects
SEQUENCE alignment; GENETIC techniques; AMINO acid sequence; NUCLEOTIDE sequencing; RNA sequencing
- Publication
Bioinformatics, 2015, Vol 31, Issue 8, p1183
- ISSN
1367-4803
- Publication type
Article
- DOI
10.1093/bioinformatics/btu780