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: | Text |
Language: | English |
Published: |
Genetics Society of America
2014
|
Subjects: | |
Online Access: | http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4096371 http://www.ncbi.nlm.nih.gov/pubmed/24793089 https://doi.org/10.1534/genetics.114.161299 |
id |
ftpubmed:oai:pubmedcentral.nih.gov:4096371 |
---|---|
record_format |
openpolar |
spelling |
ftpubmed:oai:pubmedcentral.nih.gov:4096371 2023-05-15T13:39:17+02:00 A Bayesian Approach to Inferring the Phylogenetic Structure of Communities from Metagenomic Data O’Brien, John D. Didelot, Xavier Iqbal, Zamin Amenga-Etego, Lucas Ahiska, Bartu Falush, Daniel 2014-07 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4096371 http://www.ncbi.nlm.nih.gov/pubmed/24793089 https://doi.org/10.1534/genetics.114.161299 en eng Genetics Society of America http://www.ncbi.nlm.nih.gov/pmc/articles/PMC http://www.ncbi.nlm.nih.gov/pubmed/24793089 http://dx.doi.org/10.1534/genetics.114.161299 Copyright © 2014 by the Genetics Society of America Available freely online through the author-supported open access option. Investigations Text 2014 ftpubmed https://doi.org/10.1534/genetics.114.161299 2014-07-20T00:58:49Z 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. Text Antarc* Antarctic PubMed Central (PMC) Antarctic Genetics 197 3 925 937 |
institution |
Open Polar |
collection |
PubMed Central (PMC) |
op_collection_id |
ftpubmed |
language |
English |
topic |
Investigations |
spellingShingle |
Investigations O’Brien, John D. Didelot, Xavier Iqbal, Zamin Amenga-Etego, Lucas Ahiska, Bartu Falush, Daniel A Bayesian Approach to Inferring the Phylogenetic Structure of Communities from Metagenomic Data |
topic_facet |
Investigations |
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 |
Text |
author |
O’Brien, John D. Didelot, Xavier Iqbal, Zamin Amenga-Etego, Lucas Ahiska, Bartu Falush, Daniel |
author_facet |
O’Brien, John D. Didelot, Xavier Iqbal, Zamin Amenga-Etego, Lucas Ahiska, Bartu Falush, Daniel |
author_sort |
O’Brien, John 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://www.ncbi.nlm.nih.gov/pmc/articles/PMC4096371 http://www.ncbi.nlm.nih.gov/pubmed/24793089 https://doi.org/10.1534/genetics.114.161299 |
geographic |
Antarctic |
geographic_facet |
Antarctic |
genre |
Antarc* Antarctic |
genre_facet |
Antarc* Antarctic |
op_relation |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC http://www.ncbi.nlm.nih.gov/pubmed/24793089 http://dx.doi.org/10.1534/genetics.114.161299 |
op_rights |
Copyright © 2014 by the Genetics Society of America Available freely online through the author-supported open access option. |
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_ |
1766116840253161472 |