{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Wood DE"],"funding":["Directorate for Computer and Information Science and Engineering","National Institute of General Medical Sciences","NIGMS NIH HHS"],"pagination":["257"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC6883579"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["20(1)"],"pubmed_abstract":["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."],"journal":["Genome biology"],"pubmed_title":["Improved metagenomic analysis with Kraken 2."],"pmcid":["PMC6883579"],"funding_grant_id":["R01 GM118568","IIS-1349906","R01-GM118568","R35-GM130151"],"pubmed_authors":["Langmead B","Wood DE","Lu J"],"additional_accession":[]},"is_claimable":false,"name":"Improved metagenomic analysis with Kraken 2.","description":"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.","dates":{"release":"2019-01-01T00:00:00Z","publication":"2019 Nov","modification":"2026-05-01T10:31:56.345Z","creation":"2020-05-21T21:08:08Z"},"accession":"S-EPMC6883579","cross_references":{"pubmed":["31779668"],"doi":["10.1186/s13059-019-1891-0"]}}