IMG/M: a data management and analysis system for metagenomes
Victor M. Markowitz,Natalia Ivanova,Ernest Szeto,Krishna Palaniappan,Ken Chu,Daniel Dalevi,I-Min A. Chen,Yuri Grechkin,Inna Dubchak,Iain Anderson,Athanasios Lykidis,Konstantinos Mavromatis,Philip Hugenholtz,Nikos C. Kyrpides +13 more
TLDR
IMG/M as mentioned in this paper is a data management and analysis system for microbial community genomes (metagenomes) hosted at the Department of Energy's (DOE) Joint Genome Institute (JGI).Abstract:
IMG/M is a data management and analysis system for microbial community genomes (metagenomes) hosted at the Department of Energy's (DOE) Joint Genome Institute (JGI). IMG/M consists of metagenome data integrated with isolate microbial genomes from the Integrated Microbial Genomes (IMG) system. IMG/M provides IMG's comparative data analysis tools extended to handle metagenome data, together with metagenome-specific analysis tools. IMG/M is available at http://img.jgi.doe.gov/mread more
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STAMP: statistical analysis of taxonomic and functional profiles
TL;DR: UNLABELLED STAMP is a graphical software package that provides statistical hypothesis tests and exploratory plots for analysing taxonomic and functional profiles and a user-friendly graphical interface permits easy exploration of statistical results and generation of publication-quality plots.
Journal ArticleDOI
Ab initio Gene Identification in Metagenomic Sequences
TL;DR: An algorithm for gene identification in DNA sequences derived from shotgun sequencing of microbial communities and its accuracy is described and several thousands of new genes could be added to existing annotations of several human and mouse gut metagenomes.
Journal ArticleDOI
The minimum information about a genome sequence (MIGS) specification.
Dawn Field,George M. Garrity,Tanya Gray,Norman Morrison,Jeremy D. Selengut,Peter Sterk,Tatiana Tatusova,Nicholas R. Thomson,Michael J. Allen,Samuel V. Angiuoli,Michael Ashburner,Nelson Axelrod,Sandra L. Baldauf,S. Ballard,Jeffrey L. Boore,Guy Cochrane,James R. Cole,Peter Dawyndt,Paul De Vos,Claude W. dePamphilis,Robert Edwards,Nadeem Faruque,Robert G. Feldman,Jack A. Gilbert,Paul Gilna,Frank Oliver Glöckner,Philip Goldstein,Robert P. Guralnick,Daniel H. Haft,David Hancock,Henning Hermjakob,Christiane Hertz-Fowler,Phil Hugenholtz,Ian Joint,Leonid Kagan,Matthew D. Kane,Jessie Kennedy,George A. Kowalchuk,Renzo Kottmann,Eugene Kolker,Saul A. Kravitz,Nikos C. Kyrpides,Jim Leebens-Mack,Suzanna E. Lewis,Kelvin Li,Allyson L. Lister,Phillip Lord,Natalia Maltsev,Victor Markowitz,Jennifer B. H. Martiny,Barbara A. Methé,Ilene Mizrachi,Richard Moxon,Karen E. Nelson,Julian Parkhill,Lita M. Proctor,Owen White,Susanna-Assunta Sansone,Andrew J. Spiers,Robert Stevens,Paul Swift,Chris F. Taylor,Yoshio Tateno,Adrian Tett,Sarah L. Turner,David W. Ussery,Bob Vaughan,Naomi L. Ward,Trish Whetzel,Ingio San Gil,Gareth A. Wilson,Anil Wipat +71 more
TL;DR: Here, the minimum information about a genome sequence (MIGS) specification is introduced with the intent of promoting participation in its development and discussing the resources that will be required to develop improved mechanisms of metadata capture and exchange.
Journal ArticleDOI
The Genomes On Line Database (GOLD) in 2009: status of genomic and metagenomic projects and their associated metadata
Ioanna Pagani,Konstantinos Liolios,Jakob Jansson,I-Min A. Chen,Tatyana Smirnova,Bahador Nosrat,Victor Markowitz,Nikos C. Kyrpides +7 more
TL;DR: The Genomes On Line Database (GOLD) as mentioned in this paper is a comprehensive resource for centralized monitoring of genome and metagenome projects worldwide, containing information for more than 5800 sequencing projects.
Journal ArticleDOI
Metabolic Reconstruction for Metagenomic Data and Its Application to the Human Microbiome
Sahar Abubucker,Nicola Segata,Johannes B. Goll,Alyxandria M. Schubert,Jacques Izard,Brandi L. Cantarel,Beltran Rodriguez-Mueller,Jeremy Zucker,Mathangi Thiagarajan,Bernard Henrissat,Owen White,Scott T. Kelley,Barbara A. Methé,Patrick D. Schloss,Dirk Gevers,Makedonka Mitreva,Curtis Huttenhower,Curtis Huttenhower +17 more
Abstract: Microbial communities carry out the majority of the biochemical activity on the planet, and they play integral roles in processes including metabolism and immune homeostasis in the human microbiome. Shotgun sequencing of such communities' metagenomes provides information complementary to organismal abundances from taxonomic markers, but the resulting data typically comprise short reads from hundreds of different organisms and are at best challenging to assemble comparably to single-organism genomes. Here, we describe an alternative approach to infer the functional and metabolic potential of a microbial community metagenome. We determined the gene families and pathways present or absent within a community, as well as their relative abundances, directly from short sequence reads. We validated this methodology using a collection of synthetic metagenomes, recovering the presence and abundance both of large pathways and of small functional modules with high accuracy. We subsequently applied this method, HUMAnN, to the microbial communities of 649 metagenomes drawn from seven primary body sites on 102 individuals as part of the Human Microbiome Project (HMP). This provided a means to compare functional diversity and organismal ecology in the human microbiome, and we determined a core of 24 ubiquitously present modules. Core pathways were often implemented by different enzyme families within different body sites, and 168 functional modules and 196 metabolic pathways varied in metagenomic abundance specifically to one or more niches within the microbiome. These included glycosaminoglycan degradation in the gut, as well as phosphate and amino acid transport linked to host phenotype (vaginal pH) in the posterior fornix. An implementation of our methodology is available at http://huttenhower.sph.harvard.edu/humann. This provides a means to accurately and efficiently characterize microbial metabolic pathways and functional modules directly from high-throughput sequencing reads, enabling the determination of community roles in the HMP cohort and in future metagenomic studies.
References
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