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      Improved metagenomic analysis with Kraken 2

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          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.

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          Bracken: estimating species abundance in metagenomics data

          Jennifer Lu, Florian P. Breitwieser, Peter Thielen … (2017)
          Metagenomic experiments attempt to characterize microbial communities using high-throughput DNA sequencing. Identification of the microorganisms in a sample provides information about the genetic profile, population structure, and role of microorganisms within an environment. Until recently, most metagenomics studies focused on high-level characterization at the level of phyla, or alternatively sequenced the 16S ribosomal RNA gene that is present in bacterial species. As the cost of sequencing has fallen, though, metagenomics experiments have increasingly used unbiased shotgun sequencing to capture all the organisms in a sample. This approach requires a method for estimating abundance directly from the raw read data. Here we describe a fast, accurate new method that computes the abundance at the species level using the reads collected in a metagenomics experiment. Bracken (Bayesian Reestimation of Abundance after Classification with KrakEN) uses the taxonomic assignments made by Kraken, a very fast read-level classifier, along with information about the genomes themselves to estimate abundance at the species level, the genus level, or above. We demonstrate that Bracken can produce accurate species- and genus-level abundance estimates even when a sample contains multiple near-identical species.
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            Scaling read aligners to hundreds of threads on general-purpose processors

            Ben Langmead, Christopher Wilks, Valentin Antonescu … (2018)
            Abstract Motivation General-purpose processors can now contain many dozens of processor cores and support hundreds of simultaneous threads of execution. To make best use of these threads, genomics software must contend with new and subtle computer architecture issues. We discuss some of these and propose methods for improving thread scaling in tools that analyze each read independently, such as read aligners. Results We implement these methods in new versions of Bowtie, Bowtie 2 and HISAT. We greatly improve thread scaling in many scenarios, including on the recent Intel Xeon Phi architecture. We also highlight how bottlenecks are exacerbated by variable-record-length file formats like FASTQ and suggest changes that enable superior scaling. Availability and implementation Experiments for this study: https://github.com/BenLangmead/bowtie-scaling . Bowtie http://bowtie-bio.sourceforge.net . Bowtie 2 http://bowtie-bio.sourceforge.net/bowtie2 . HISAT http://www.ccb.jhu.edu/software/hisat Supplementary information Supplementary data are available at Bioinformatics online.
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              Bacillus anthracis, Bacillus cereus, and Bacillus thuringiensis--one species on the basis of genetic evidence.

              E Helgason, O A Okstad, D A Caugant … (2000)
              Bacillus anthracis, Bacillus cereus, and Bacillus thuringiensis are members of the Bacillus cereus group of bacteria, demonstrating widely different phenotypes and pathological effects. B. anthracis causes the acute fatal disease anthrax and is a potential biological weapon due to its high toxicity. B. thuringiensis produces intracellular protein crystals toxic to a wide number of insect larvae and is the most commonly used biological pesticide worldwide. B. cereus is a probably ubiquitous soil bacterium and an opportunistic pathogen that is a common cause of food poisoning. In contrast to the differences in phenotypes, we show by multilocus enzyme electrophoresis and by sequence analysis of nine chromosomal genes that B. anthracis should be considered a lineage of B. cereus. This determination is not only a formal matter of taxonomy but may also have consequences with respect to virulence and the potential of horizontal gene transfer within the B. cereus group.
              Article 0 comments Cited 227 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Ben Langmead:
                ORCID: http://orcid.org/0000-0003-2437-1976
                langmea@cs.jhu.edu
                Journal
                Journal ID (nlm-ta): Genome Biol
                Journal ID (iso-abbrev): Genome Biol
                Title: Genome Biology
                Publisher: BioMed Central (London )
                ISSN (Print): 1474-7596
                ISSN (Electronic): 1474-760X
                Publication date (Electronic): 28 November 2019
                Publication date PMC-release: 28 November 2019
                Publication date Collection: 2019
                Volume: 20
                Electronic Location Identifier: 257
                Affiliations
                [1 ]ISNI 0000 0001 2171 9311, GRID grid.21107.35, Department of Computer Science, Whiting School of Engineering, , Johns Hopkins University, ; Baltimore, MD USA
                [2 ]ISNI 0000 0001 2171 9311, GRID grid.21107.35, Center for Computational Biology, , Johns Hopkins University, ; Baltimore, MD USA
                [3 ]ISNI 0000 0001 2171 9311, GRID grid.21107.35, Department of Biomedical Engineering, Whiting School of Engineering, , Johns Hopkins University, ; Baltimore, MD USA
                Author information
                http://orcid.org/0000-0003-2437-1976
                Article
                Publisher ID: 1891
                DOI: 10.1186/s13059-019-1891-0
                PMC ID: 6883579
                PubMed ID: 31779668
                SO-VID: dc903212-0a03-4f80-b0bb-b2d7b926d2a7
                Copyright © © The Author(s). 2019
                License:

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                Date received : 20 September 2019
                Date accepted : 18 November 2019
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000083, Directorate for Computer and Information Science and Engineering;
                Award ID: IIS-1349906
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000057, National Institute of General Medical Sciences;
                Award ID: R01-GM118568
                Award ID: R35-GM130151
                Award Recipient :
                Categories
                Subject: Short Report
                Custom metadata
                issue-copyright-statement © The Author(s) 2019

                ScienceOpen disciplines: Genetics
                Keywords: metagenomics,metagenomics classification,microbiome,probabilistic data structures,alignment-free methods,minimizers
                Data availability:
                ScienceOpen disciplines: Genetics
                Keywords: metagenomics, metagenomics classification, microbiome, probabilistic data structures, alignment-free methods, minimizers

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