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Accurate read-based metagenome characterization using a hierarchical suite of unique signatures

A major challenge in the field of shotgun metagenomics is the accurate identification of organisms present within a microbial community, based on classification of short sequence reads. Though existing microbial community profiling methods have attempted to rapidly classify the millions of reads out...

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Detalles Bibliográficos
Autores principales: Freitas, Tracey Allen K., Li, Po-E, Scholz, Matthew B., Chain, Patrick S. G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4446416/
https://www.ncbi.nlm.nih.gov/pubmed/25765641
http://dx.doi.org/10.1093/nar/gkv180
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author Freitas, Tracey Allen K.
Li, Po-E
Scholz, Matthew B.
Chain, Patrick S. G.
author_facet Freitas, Tracey Allen K.
Li, Po-E
Scholz, Matthew B.
Chain, Patrick S. G.
author_sort Freitas, Tracey Allen K.
collection PubMed
description A major challenge in the field of shotgun metagenomics is the accurate identification of organisms present within a microbial community, based on classification of short sequence reads. Though existing microbial community profiling methods have attempted to rapidly classify the millions of reads output from modern sequencers, the combination of incomplete databases, similarity among otherwise divergent genomes, errors and biases in sequencing technologies, and the large volumes of sequencing data required for metagenome sequencing has led to unacceptably high false discovery rates (FDR). Here, we present the application of a novel, gene-independent and signature-based metagenomic taxonomic profiling method with significantly and consistently smaller FDR than any other available method. Our algorithm circumvents false positives using a series of non-redundant signature databases and examines Genomic Origins Through Taxonomic CHAllenge (GOTTCHA). GOTTCHA was tested and validated on 20 synthetic and mock datasets ranging in community composition and complexity, was applied successfully to data generated from spiked environmental and clinical samples, and robustly demonstrates superior performance compared with other available tools.
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spelling pubmed-44464162016-03-04 Accurate read-based metagenome characterization using a hierarchical suite of unique signatures Freitas, Tracey Allen K. Li, Po-E Scholz, Matthew B. Chain, Patrick S. G. Nucleic Acids Res Methods Online A major challenge in the field of shotgun metagenomics is the accurate identification of organisms present within a microbial community, based on classification of short sequence reads. Though existing microbial community profiling methods have attempted to rapidly classify the millions of reads output from modern sequencers, the combination of incomplete databases, similarity among otherwise divergent genomes, errors and biases in sequencing technologies, and the large volumes of sequencing data required for metagenome sequencing has led to unacceptably high false discovery rates (FDR). Here, we present the application of a novel, gene-independent and signature-based metagenomic taxonomic profiling method with significantly and consistently smaller FDR than any other available method. Our algorithm circumvents false positives using a series of non-redundant signature databases and examines Genomic Origins Through Taxonomic CHAllenge (GOTTCHA). GOTTCHA was tested and validated on 20 synthetic and mock datasets ranging in community composition and complexity, was applied successfully to data generated from spiked environmental and clinical samples, and robustly demonstrates superior performance compared with other available tools. Oxford University Press 2015-05-26 2015-03-12 /pmc/articles/PMC4446416/ /pubmed/25765641 http://dx.doi.org/10.1093/nar/gkv180 Text en Published by Oxford University Press on behalf of Nucleic Acids Research 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.
spellingShingle Methods Online
Freitas, Tracey Allen K.
Li, Po-E
Scholz, Matthew B.
Chain, Patrick S. G.
Accurate read-based metagenome characterization using a hierarchical suite of unique signatures
title Accurate read-based metagenome characterization using a hierarchical suite of unique signatures
title_full Accurate read-based metagenome characterization using a hierarchical suite of unique signatures
title_fullStr Accurate read-based metagenome characterization using a hierarchical suite of unique signatures
title_full_unstemmed Accurate read-based metagenome characterization using a hierarchical suite of unique signatures
title_short Accurate read-based metagenome characterization using a hierarchical suite of unique signatures
title_sort accurate read-based metagenome characterization using a hierarchical suite of unique signatures
topic Methods Online
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4446416/
https://www.ncbi.nlm.nih.gov/pubmed/25765641
http://dx.doi.org/10.1093/nar/gkv180
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