ArticleBMC bioinformatics2018
TOPAZ: asymmetric suffix array neighbourhood search for massive protein databases.
Article in BMC bioinformatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- mimicDetector: a pipeline for protein motif mimicry detection in host-pathogen interactions.Bioinformatics (Oxford, England) · 2026Article
- Activity-based metaproteomics driven discovery and enzymological characterization of potential α-galactosidases in the mouse gut microbiome.Communications chemistry · 2024Article
- Proteinortho6: pseudo-reciprocal best alignment heuristic for graph-based detection of (co-)orthologs.Frontiers in bioinformatics · 2023Article
- Novel NGS pipeline for virus discovery from a wide spectrum of hosts and sample types.Virus evolution · 2020Article
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2 authors.
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Abstract
backgroundProtein homology search is an important, yet time-consuming, step in everything from protein annotation to metagenomics. Its application, however, has become increasingly challenging, due to the exponential growth of protein databases. In order to perform homology search at the required scale, many methods have been proposed as alternatives to BLAST that make an explicit trade-off between sensitivity and speed. One such method, SANSparallel, uses a parallel implementation of the suffix array neighbourhood search (SANS) technique to achieve high speed and provides several modes to allow for greater sensitivity at the expense of performance.
resultsWe present a new approach called asymmetric SANS together with scored seeds and an alternative suffix array ordering scheme called optimal substitution ordering. These techniques dramatically improve both the sensitivity and speed of the SANS approach. Our implementation, TOPAZ, is one of the top performing methods in terms of speed, sensitivity and scalability. In our benchmark, searching UniProtKB for homologous proteins to the Dickeya solani proteome, TOPAZ took less than 3 minutes to achieve a sensitivity of 0.84 compared to BLAST.
conclusionsDespite the trade-off homology search methods have to make between sensitivity and speed, TOPAZ stands out as one of the most sensitive and highest performance methods currently available.
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