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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2014
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Online Access: | http://wrap.warwick.ac.uk/109147/ https://doi.org/10.1534/genetics.114.161299 |
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ftuwarwick:oai:wrap.warwick.ac.uk:109147 2023-05-15T13:31:58+02:00 A Bayesian approach to inferring the phylogenetic structure of communities from metagenomic data O'Brien, J. D. Didelot, Xavier Iqbal, Z. Amenga-Etego, L. Ahiska, B. Falush, D. 2014-07-14 http://wrap.warwick.ac.uk/109147/ https://doi.org/10.1534/genetics.114.161299 unknown Genetics Society of America O'Brien, J. D., Didelot, Xavier, Iqbal, Z., Amenga-Etego, L., Ahiska, B. and Falush, D. (2014) A Bayesian approach to inferring the phylogenetic structure of communities from metagenomic data. Genetics, 197 (3). pp. 925-937. doi:10.1534/genetics.114.161299 <http://dx.doi.org/10.1534/genetics.114.161299> Journal Article NonPeerReviewed 2014 ftuwarwick https://doi.org/10.1534/genetics.114.161299 2022-03-16T21:24:44Z 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 high rates of migration among sample sites. 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 Article in Journal/Newspaper Antarc* Antarctic The University of Warwick: WRAP - Warwick Research Archive Portal Antarctic Genetics 197 3 925 937 |
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The University of Warwick: WRAP - Warwick Research Archive Portal |
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ftuwarwick |
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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 high rates of migration among sample sites. 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 |
format |
Article in Journal/Newspaper |
author |
O'Brien, J. D. Didelot, Xavier Iqbal, Z. Amenga-Etego, L. Ahiska, B. Falush, D. |
spellingShingle |
O'Brien, J. D. Didelot, Xavier Iqbal, Z. Amenga-Etego, L. Ahiska, B. Falush, D. A Bayesian approach to inferring the phylogenetic structure of communities from metagenomic data |
author_facet |
O'Brien, J. D. Didelot, Xavier Iqbal, Z. Amenga-Etego, L. Ahiska, B. Falush, D. |
author_sort |
O'Brien, J. D. |
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 |
Genetics Society of America |
publishDate |
2014 |
url |
http://wrap.warwick.ac.uk/109147/ https://doi.org/10.1534/genetics.114.161299 |
geographic |
Antarctic |
geographic_facet |
Antarctic |
genre |
Antarc* Antarctic |
genre_facet |
Antarc* Antarctic |
op_relation |
O'Brien, J. D., Didelot, Xavier, Iqbal, Z., Amenga-Etego, L., Ahiska, B. and Falush, D. (2014) A Bayesian approach to inferring the phylogenetic structure of communities from metagenomic data. Genetics, 197 (3). pp. 925-937. doi:10.1534/genetics.114.161299 <http://dx.doi.org/10.1534/genetics.114.161299> |
op_doi |
https://doi.org/10.1534/genetics.114.161299 |
container_title |
Genetics |
container_volume |
197 |
container_issue |
3 |
container_start_page |
925 |
op_container_end_page |
937 |
_version_ |
1766023315600703488 |