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Bracken: estimating species abundance in metagenomics data.

作者信息

Lu Jennifer, Breitwieser Florian P, Thielen Peter, Salzberg Steven L

机构信息

Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States.

Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD, United States.

出版信息

PeerJ Comput Sci. 2017;3. doi: 10.7717/peerj-cs.104. Epub 2017 Jan 2.


DOI:10.7717/peerj-cs.104
PMID:40271438
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12016282/
Abstract

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.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87f2/12016282/74790bd6ed65/nihms-2071674-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87f2/12016282/599fc49a97bb/nihms-2071674-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87f2/12016282/e5dd7bf62000/nihms-2071674-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87f2/12016282/7a155ff54310/nihms-2071674-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87f2/12016282/3cc7ddbfc085/nihms-2071674-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87f2/12016282/74790bd6ed65/nihms-2071674-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87f2/12016282/599fc49a97bb/nihms-2071674-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87f2/12016282/e5dd7bf62000/nihms-2071674-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87f2/12016282/7a155ff54310/nihms-2071674-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87f2/12016282/3cc7ddbfc085/nihms-2071674-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87f2/12016282/74790bd6ed65/nihms-2071674-f0005.jpg

相似文献

[1]
Bracken: estimating species abundance in metagenomics data.

PeerJ Comput Sci. 2017

[2]
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[10]
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[5]
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[6]
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[7]
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[8]
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[9]
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[10]
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本文引用的文献

[1]
Pseudoalignment for metagenomic read assignment.

Bioinformatics. 2017-7-15

[2]
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Sci Rep. 2016-1-18

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BMC Bioinformatics. 2015-11-4

[4]
Impact of library preparation protocols and template quantity on the metagenomic reconstruction of a mock microbial community.

BMC Genomics. 2015-10-24

[5]
Genomic insights into the taxonomic status of the Bacillus cereus group.

Sci Rep. 2015-9-16

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ConStrains identifies microbial strains in metagenomic datasets.

Nat Biotechnol. 2015-10

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GenBank.

Nucleic Acids Res. 2015-1

[8]
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Stand Genomic Sci. 2014-1-1

[9]
Accurate genome relative abundance estimation for closely related species in a metagenomic sample.

BMC Bioinformatics. 2014-7-16

[10]
Kraken: ultrafast metagenomic sequence classification using exact alignments.

Genome Biol. 2014-3-3

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