Unsupervised discovery of microbial population structure within metagenomes using nucleotide base composition
An approach to infer the unknown microbial population structure within a metagenome is to cluster nucleotide sequences based on common patterns in base composition, otherwise referred to as binning. When functional roles are assigned to the identified populations, a deeper understanding of microbial...
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fthighwire:oai:open-archive.highwire.org:nar:40/5/e34 2023-05-15T13:36:07+02:00 Unsupervised discovery of microbial population structure within metagenomes using nucleotide base composition Saeed, Isaam Tang, Sen-Lin Halgamuge, Saman K. 2012-03-01 00:00:00.0 text/html http://nar.oxfordjournals.org/cgi/content/short/40/5/e34 https://doi.org/10.1093/nar/gkr1204 en eng Oxford University Press http://nar.oxfordjournals.org/cgi/content/short/40/5/e34 http://dx.doi.org/10.1093/nar/gkr1204 Copyright (C) 2012, Oxford University Press Methods Online TEXT 2012 fthighwire https://doi.org/10.1093/nar/gkr1204 2013-05-27T08:42:23Z An approach to infer the unknown microbial population structure within a metagenome is to cluster nucleotide sequences based on common patterns in base composition, otherwise referred to as binning. When functional roles are assigned to the identified populations, a deeper understanding of microbial communities can be attained, more so than gene-centric approaches that explore overall functionality. In this study, we propose an unsupervised, model-based binning method with two clustering tiers, which uses a novel transformation of the oligonucleotide frequency-derived error gradient and GC content to generate coarse groups at the first tier of clustering; and tetranucleotide frequency to refine these groups at the secondary clustering tier. The proposed method has a demonstrated improvement over PhyloPythia, S-GSOM, TACOA and TaxSOM on all three benchmarks that were used for evaluation in this study. The proposed method is then applied to a pyrosequenced metagenomic library of mud volcano sediment sampled in southwestern Taiwan, with the inferred population structure validated against complementary sequencing of 16S ribosomal RNA marker genes. Finally, the proposed method was further validated against four publicly available metagenomes, including a highly complex Antarctic whale-fall bone sample, which was previously assumed to be too complex for binning prior to functional analysis. Text Antarc* Antarctic HighWire Press (Stanford University) Antarctic Nucleic Acids Research 40 5 e34 e34 |
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Methods Online Saeed, Isaam Tang, Sen-Lin Halgamuge, Saman K. Unsupervised discovery of microbial population structure within metagenomes using nucleotide base composition |
topic_facet |
Methods Online |
description |
An approach to infer the unknown microbial population structure within a metagenome is to cluster nucleotide sequences based on common patterns in base composition, otherwise referred to as binning. When functional roles are assigned to the identified populations, a deeper understanding of microbial communities can be attained, more so than gene-centric approaches that explore overall functionality. In this study, we propose an unsupervised, model-based binning method with two clustering tiers, which uses a novel transformation of the oligonucleotide frequency-derived error gradient and GC content to generate coarse groups at the first tier of clustering; and tetranucleotide frequency to refine these groups at the secondary clustering tier. The proposed method has a demonstrated improvement over PhyloPythia, S-GSOM, TACOA and TaxSOM on all three benchmarks that were used for evaluation in this study. The proposed method is then applied to a pyrosequenced metagenomic library of mud volcano sediment sampled in southwestern Taiwan, with the inferred population structure validated against complementary sequencing of 16S ribosomal RNA marker genes. Finally, the proposed method was further validated against four publicly available metagenomes, including a highly complex Antarctic whale-fall bone sample, which was previously assumed to be too complex for binning prior to functional analysis. |
format |
Text |
author |
Saeed, Isaam Tang, Sen-Lin Halgamuge, Saman K. |
author_facet |
Saeed, Isaam Tang, Sen-Lin Halgamuge, Saman K. |
author_sort |
Saeed, Isaam |
title |
Unsupervised discovery of microbial population structure within metagenomes using nucleotide base composition |
title_short |
Unsupervised discovery of microbial population structure within metagenomes using nucleotide base composition |
title_full |
Unsupervised discovery of microbial population structure within metagenomes using nucleotide base composition |
title_fullStr |
Unsupervised discovery of microbial population structure within metagenomes using nucleotide base composition |
title_full_unstemmed |
Unsupervised discovery of microbial population structure within metagenomes using nucleotide base composition |
title_sort |
unsupervised discovery of microbial population structure within metagenomes using nucleotide base composition |
publisher |
Oxford University Press |
publishDate |
2012 |
url |
http://nar.oxfordjournals.org/cgi/content/short/40/5/e34 https://doi.org/10.1093/nar/gkr1204 |
geographic |
Antarctic |
geographic_facet |
Antarctic |
genre |
Antarc* Antarctic |
genre_facet |
Antarc* Antarctic |
op_relation |
http://nar.oxfordjournals.org/cgi/content/short/40/5/e34 http://dx.doi.org/10.1093/nar/gkr1204 |
op_rights |
Copyright (C) 2012, Oxford University Press |
op_doi |
https://doi.org/10.1093/nar/gkr1204 |
container_title |
Nucleic Acids Research |
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40 |
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5 |
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e34 |
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e34 |
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1766074653968695296 |