PhyloSift: phylogenetic analysis of genomes and metagenomes.
Aaron E. Darling,Aaron E. Darling,Guillaume Jospin,Eric Lowe,Frederick A. Matsen,Holly M. Bik,Jonathan A. Eisen +6 more
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TLDR
This work presents an approach to leverage phylogenetic analysis of metagenomic sequence data to conduct phylogeny-driven Bayesian hypothesis tests for the presence of an organism in a sample and applies new tools to analyze the phylogenetic diversity of microbial communities.Abstract:
Like all organisms on the planet, environmental microbes are subject to the forces of molecular evolution. Metagenomic sequencing provides a means to access the DNA sequence of uncultured microbes. By combining DNA sequencing of microbial communities with evolutionary modeling and phylogenetic analysis we might obtain new insights into microbiology and also provide a basis for practical tools such as forensic pathogen detection. In this work we present an approach to leverage phylogenetic analysis of metagenomic sequence data to conduct several types of analysis. First, we present a method to conduct phylogeny-driven Bayesian hypothesis tests for the presence of an organism in a sample. Second, we present a means to compare community structure across a collection of many samples and develop direct associations between the abundance of certain organisms and sample metadata. Third, we apply new tools to analyze the phylogenetic diversity of microbial communities and again demonstrate how this can be associated to sample metadata. These analyses are implemented in an open source software pipeline called PhyloSift. As a pipeline, PhyloSift incorporates several other programs including LAST, HMMER, and pplacer to automate phylogenetic analysis of protein coding and RNA sequences in metagenomic datasets generated by modern sequencing platforms (e.g., Illumina, 454).read more
Citations
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CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes
TL;DR: An objective measure of genome quality is proposed that can be used to select genomes suitable for specific gene- and genome-centric analyses of microbial communities and is shown to provide accurate estimates of genome completeness and contamination and to outperform existing approaches.
Journal ArticleDOI
Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea
Robert M. Bowers,Nikos C. Kyrpides,Ramunas Stepanauskas,Miranda Harmon-Smith,Devin F. R. Doud,T. B. K. Reddy,Frederik Schulz,Jessica K. Jarett,Adam R. Rivers,Adam R. Rivers,Emiley A. Eloe-Fadrosh,Susannah G. Tringe,Susannah G. Tringe,Natalia Ivanova,Alex Copeland,Alicia Clum,Eric D. Becraft,Rex R. Malmstrom,Bruce W. Birren,Mircea Podar,Peer Bork,George M. Weinstock,George M. Garrity,Jeremy A. Dodsworth,Shibu Yooseph,Granger G. Sutton,Frank Oliver Gloeckner,Jack A. Gilbert,William C. Nelson,Steven J. Hallam,Sean P. Jungbluth,Sean P. Jungbluth,Thijs J. G. Ettema,Scott Tighe,Konstantinos T. Konstantinidis,Wen Tso Liu,Brett J. Baker,Thomas Rattei,Jonathan A. Eisen,Brian P. Hedlund,Katherine D. McMahon,Noah Fierer,Rob Knight,Robert D. Finn,Guy Cochrane,Ilene Karsch-Mizrachi,Gene W. Tyson,Christian Rinke,Alla Lapidus,Folker Meyer,Pelin Yilmaz,Donovan H. Parks,A. M. Eren,Lynn M. Schriml,Jillian F. Banfield,Philip Hugenholtz,Tanja Woyke +56 more
TL;DR: Two standards developed by the Genomic Standards Consortium (GSC) for reporting bacterial and archaeal genome sequences are presented, including the Minimum Information about a Single Amplified Genome (MISAG) and the Minimum information about a Metagenome-Assembled Genomes (MIMAG), including estimates of genome completeness and contamination.
Journal ArticleDOI
UBCG: Up-to-date bacterial core gene set and pipeline for phylogenomic tree reconstruction
TL;DR: This work presents the up-to-date bacterial core gene set, named UBCG, and software suites to accommodate necessary steps to generate and evaluate phylogenetic trees, successfully used to infer phylogenomic relationship of Escherichia and related taxa.
Journal ArticleDOI
Characterization of the Gut Microbiome Using 16S or Shotgun Metagenomics.
Juan Jovel,Jordan Patterson,Weiwei Wang,Naomi Hotte,Sandra O'Keefe,Troy Mitchel,Troy Perry,Dina Kao,Andrew Mason,Karen L. Madsen,Gane Ka-Shu Wong +10 more
TL;DR: The two main approaches for analyzing the microbiome, 16S ribosomal RNA gene amplicons and shotgun metagenomics, are illustrated with analyses of libraries designed to highlight their strengths and weaknesses and several methods for taxonomic classification of bacterial sequences are discussed.
Journal ArticleDOI
An introduction to the analysis of shotgun metagenomic data.
TL;DR: This review describes the analytical strategies and specific tools that can be applied to metagenomic data and the considerations and caveats associated with their use and documents how metagenomes can be analyzed to quantify community structure and diversity.
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