Improved metagenomic analysis with Kraken 2
Derrick E. WoodCenter for Computational Biology, Johns Hopkins University, Baltimore, MD, USAJennifer LuCenter for Computational Biology, Johns Hopkins University, Baltimore, MD, USABen LangmeadCenter for Computational Biology, Johns Hopkins University, Baltimore, MD, USA. [email protected]
2019en
ABI
Аннотация
Although Kraken's k-mer-based approach provides a fast taxonomic classification of metagenomic sequence data, its large memory requirements can be limiting for some applications. Kraken 2 improves upon Kraken 1 by reducing memory usage by 85%, allowing greater amounts of reference genomic data to be used, while maintaining high accuracy and increasing speed fivefold. Kraken 2 also introduces a translated search mode, providing increased sensitivity in viral metagenomics analysis.
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