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...
Published in: | Genetics |
---|---|
Main Authors: | , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Genetics
2016
|
Subjects: | |
Online Access: | https://doi.org/10.1534/genetics.114.161299 https://ora.ox.ac.uk/objects/uuid:5b3fb6b6-d51b-4538-ac9a-784f2ce1027d |
id |
ftuloxford:oai:ora.ox.ac.uk:uuid:5b3fb6b6-d51b-4538-ac9a-784f2ce1027d |
---|---|
record_format |
openpolar |
spelling |
ftuloxford:oai:ora.ox.ac.uk:uuid:5b3fb6b6-d51b-4538-ac9a-784f2ce1027d 2023-05-15T13:54:08+02:00 A Bayesian approach to inferring the phylogenetic structure of communities from metagenomic data. O'Brien, J Didelot, X Iqbal, Z Amenga-Etego, L Ahiska, B Falush, D 2016-07-28 https://doi.org/10.1534/genetics.114.161299 https://ora.ox.ac.uk/objects/uuid:5b3fb6b6-d51b-4538-ac9a-784f2ce1027d eng eng Genetics doi:10.1534/genetics.114.161299 https://ora.ox.ac.uk/objects/uuid:5b3fb6b6-d51b-4538-ac9a-784f2ce1027d https://doi.org/10.1534/genetics.114.161299 info:eu-repo/semantics/embargoedAccess Journal article 2016 ftuloxford https://doi.org/10.1534/genetics.114.161299 2022-06-28T20:13:07Z 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 ORA - Oxford University Research Archive Antarctic Genetics 197 3 925 937 |
institution |
Open Polar |
collection |
ORA - Oxford University Research Archive |
op_collection_id |
ftuloxford |
language |
English |
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 Didelot, X Iqbal, Z Amenga-Etego, L Ahiska, B Falush, D |
spellingShingle |
O'Brien, J Didelot, X 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 Didelot, X Iqbal, Z Amenga-Etego, L Ahiska, B Falush, D |
author_sort |
O'Brien, J |
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 |
publishDate |
2016 |
url |
https://doi.org/10.1534/genetics.114.161299 https://ora.ox.ac.uk/objects/uuid:5b3fb6b6-d51b-4538-ac9a-784f2ce1027d |
geographic |
Antarctic |
geographic_facet |
Antarctic |
genre |
Antarc* Antarctic |
genre_facet |
Antarc* Antarctic |
op_relation |
doi:10.1534/genetics.114.161299 https://ora.ox.ac.uk/objects/uuid:5b3fb6b6-d51b-4538-ac9a-784f2ce1027d https://doi.org/10.1534/genetics.114.161299 |
op_rights |
info:eu-repo/semantics/embargoedAccess |
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_ |
1766259780194664448 |