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- W2912358796 abstract "Abstract Introduction Gene homology type classification is a requisite for many types of genome analyses, including comparative genomics, phylogenetics, and protein function annotation. A large variety of tools have been developed to perform homology classification across genomes of different species. However, when applied to large genomic datasets, these tools require high memory and CPU usage, typically available only in costly computational clusters. To address this problem, we developed a new graph-based orthology analysis tool, SwiftOrtho, which is optimized for speed and memory usage when applied to large-scale data. Results In our tests, SwiftOrtho is the only tool that completed orthology analysis of 1,760 bacterial genomes on a computer with only 4GB RAM. Using various standard orthology datasets, we also show that SwiftOrtho has a high accuracy. SwiftOrtho enables the accurate comparative genomic analyses of thousands of genomes using low memory computers. Availability https://github.com/Rinoahu/SwiftOrtho" @default.
- W2912358796 created "2019-02-21" @default.
- W2912358796 creator A5041597050 @default.
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- W2912358796 date "2019-02-08" @default.
- W2912358796 modified "2023-09-23" @default.
- W2912358796 title "SwiftOrtho: a Fast, Memory-Efficient, Multiple Genome Orthology Classifier" @default.
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- W2912358796 doi "https://doi.org/10.1101/543223" @default.
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