A Bayesian approach to inferring the phylogenetic structure of communities from metagenomic data
Metagenomics provides a powerful new tool set for investigating evolutionary interactions with the environment. However, an absence of model-based statistical methods means that researchers are often not able to make full use of this complex information. We present a Bayesian method for inferring th...
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ftdatacite:10.48550/arxiv.1306.6313 2023-05-15T13:50:55+02:00 A Bayesian approach to inferring the phylogenetic structure of communities from metagenomic data O'Brien, John Didelot, Xavier Iqbal, Zamin LucasAmenga-Etego Ahiska, Bartu Falush, Daniel 2013 https://dx.doi.org/10.48550/arxiv.1306.6313 https://arxiv.org/abs/1306.6313 unknown arXiv arXiv.org perpetual, non-exclusive license http://arxiv.org/licenses/nonexclusive-distrib/1.0/ Quantitative Methods q-bio.QM Populations and Evolution q-bio.PE FOS Biological sciences Preprint Article article CreativeWork 2013 ftdatacite https://doi.org/10.48550/arxiv.1306.6313 2022-04-01T13:26:03Z Metagenomics provides a powerful new tool set for investigating evolutionary interactions with the environment. However, an absence of model-based statistical methods means that researchers are often not able to make full use of this complex information. We present a Bayesian method for inferring the phylogenetic relationship among related organisms found within metagenomic samples. Our approach exploits variation in the frequency of taxa among samples to simultaneously infer each lineage haplotype, the phylogenetic tree connecting them, and their frequency within each sample. Applications of the algorithm to simulated data show that our method can recover a substantial fraction of the phylogenetic structure even in the presence of strong mixing among samples. We provide examples of the method applied to data from green sulfur bacteria recovered from an Antarctic lake, plastids from mixed Plasmodium falciparum infections, and virulent Neisseria meningitidis samples. : 25 pages, 7 figures Report Antarc* Antarctic DataCite Metadata Store (German National Library of Science and Technology) Antarctic |
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Quantitative Methods q-bio.QM Populations and Evolution q-bio.PE FOS Biological sciences |
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Quantitative Methods q-bio.QM Populations and Evolution q-bio.PE FOS Biological sciences O'Brien, John Didelot, Xavier Iqbal, Zamin LucasAmenga-Etego Ahiska, Bartu Falush, Daniel A Bayesian approach to inferring the phylogenetic structure of communities from metagenomic data |
topic_facet |
Quantitative Methods q-bio.QM Populations and Evolution q-bio.PE FOS Biological sciences |
description |
Metagenomics provides a powerful new tool set for investigating evolutionary interactions with the environment. However, an absence of model-based statistical methods means that researchers are often not able to make full use of this complex information. We present a Bayesian method for inferring the phylogenetic relationship among related organisms found within metagenomic samples. Our approach exploits variation in the frequency of taxa among samples to simultaneously infer each lineage haplotype, the phylogenetic tree connecting them, and their frequency within each sample. Applications of the algorithm to simulated data show that our method can recover a substantial fraction of the phylogenetic structure even in the presence of strong mixing among samples. We provide examples of the method applied to data from green sulfur bacteria recovered from an Antarctic lake, plastids from mixed Plasmodium falciparum infections, and virulent Neisseria meningitidis samples. : 25 pages, 7 figures |
format |
Report |
author |
O'Brien, John Didelot, Xavier Iqbal, Zamin LucasAmenga-Etego Ahiska, Bartu Falush, Daniel |
author_facet |
O'Brien, John Didelot, Xavier Iqbal, Zamin LucasAmenga-Etego Ahiska, Bartu Falush, Daniel |
author_sort |
O'Brien, John |
title |
A Bayesian approach to inferring the phylogenetic structure of communities from metagenomic data |
title_short |
A Bayesian approach to inferring the phylogenetic structure of communities from metagenomic data |
title_full |
A Bayesian approach to inferring the phylogenetic structure of communities from metagenomic data |
title_fullStr |
A Bayesian approach to inferring the phylogenetic structure of communities from metagenomic data |
title_full_unstemmed |
A Bayesian approach to inferring the phylogenetic structure of communities from metagenomic data |
title_sort |
bayesian approach to inferring the phylogenetic structure of communities from metagenomic data |
publisher |
arXiv |
publishDate |
2013 |
url |
https://dx.doi.org/10.48550/arxiv.1306.6313 https://arxiv.org/abs/1306.6313 |
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Antarctic |
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Antarctic |
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Antarc* Antarctic |
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Antarc* Antarctic |
op_rights |
arXiv.org perpetual, non-exclusive license http://arxiv.org/licenses/nonexclusive-distrib/1.0/ |
op_doi |
https://doi.org/10.48550/arxiv.1306.6313 |
_version_ |
1766254301785620480 |