Literature DB >> 29028872

A review of methods and databases for metagenomic classification and assembly.

Florian P Breitwieser, Jennifer Lu, Steven L Salzberg.   

Abstract

Microbiome research has grown rapidly over the past decade, with a proliferation of new methods that seek to make sense of large, complex data sets. Here, we survey two of the primary types of methods for analyzing microbiome data: read classification and metagenomic assembly, and we review some of the challenges facing these methods. All of the methods rely on public genome databases, and we also discuss the content of these databases and how their quality has a direct impact on our ability to interpret a microbiome sample.
© The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Keywords:  bacteria; databases; microbial genomics; microbiome; next-generation sequencing

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Year:  2019        PMID: 29028872      PMCID: PMC6781581          DOI: 10.1093/bib/bbx120

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  142 in total

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Authors:  Weizhong Li; Adam Godzik
Journal:  Bioinformatics       Date:  2006-05-26       Impact factor: 6.937

Review 2.  Past and future species definitions for Bacteria and Archaea.

Authors:  Ramon Rosselló-Móra; Rudolf Amann
Journal:  Syst Appl Microbiol       Date:  2015-02-20       Impact factor: 4.022

3.  Neurobrucellosis: Unexpected Answer From Metagenomic Next-Generation Sequencing.

Authors:  Kanokporn Mongkolrattanothai; Samia N Naccache; Jeffrey M Bender; Erik Samayoa; Elizabeth Pham; Guixia Yu; Jennifer Dien Bard; Steve Miller; Grace Aldrovandi; Charles Y Chiu
Journal:  J Pediatric Infect Dis Soc       Date:  2017-11-24       Impact factor: 3.164

Review 4.  Sequence assembly demystified.

Authors:  Niranjan Nagarajan; Mihai Pop
Journal:  Nat Rev Genet       Date:  2013-01-29       Impact factor: 53.242

5.  Metagenomics uncovers gaps in amplicon-based detection of microbial diversity.

Authors:  Emiley A Eloe-Fadrosh; Natalia N Ivanova; Tanja Woyke; Nikos C Kyrpides
Journal:  Nat Microbiol       Date:  2016-02-01       Impact factor: 17.745

6.  The PhyloPythiaS web server for taxonomic assignment of metagenome sequences.

Authors:  Kaustubh Raosaheb Patil; Linus Roune; Alice Carolyn McHardy
Journal:  PLoS One       Date:  2012-06-20       Impact factor: 3.240

7.  The truth about metagenomics: quantifying and counteracting bias in 16S rRNA studies.

Authors:  J Paul Brooks; David J Edwards; Michael D Harwich; Maria C Rivera; Jennifer M Fettweis; Myrna G Serrano; Robert A Reris; Nihar U Sheth; Bernice Huang; Philippe Girerd; Jerome F Strauss; Kimberly K Jefferson; Gregory A Buck
Journal:  BMC Microbiol       Date:  2015-03-21       Impact factor: 3.605

8.  The International Nucleotide Sequence Database Collaboration.

Authors:  Guy Cochrane; Ilene Karsch-Mizrachi; Toshihisa Takagi
Journal:  Nucleic Acids Res       Date:  2015-12-10       Impact factor: 16.971

9.  Assessment of Common and Emerging Bioinformatics Pipelines for Targeted Metagenomics.

Authors:  Léa Siegwald; Hélène Touzet; Yves Lemoine; David Hot; Christophe Audebert; Ségolène Caboche
Journal:  PLoS One       Date:  2017-01-04       Impact factor: 3.240

10.  A perspective on 16S rRNA operational taxonomic unit clustering using sequence similarity.

Authors:  Nam-Phuong Nguyen; Tandy Warnow; Mihai Pop; Bryan White
Journal:  NPJ Biofilms Microbiomes       Date:  2016-04-20       Impact factor: 7.290

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  100 in total

1.  Challenges in benchmarking metagenomic profilers.

Authors:  Zheng Sun; Shi Huang; Meng Zhang; Qiyun Zhu; Niina Haiminen; Anna Paola Carrieri; Yoshiki Vázquez-Baeza; Laxmi Parida; Ho-Cheol Kim; Rob Knight; Yang-Yu Liu
Journal:  Nat Methods       Date:  2021-05-13       Impact factor: 28.547

2.  Comparison of de-novo assembly tools for plasmid metagenome analysis.

Authors:  Sachin Kumar Gupta; Shahbaz Raza; Tatsuya Unno
Journal:  Genes Genomics       Date:  2019-06-11       Impact factor: 1.839

3.  Sensitive Identification of Bacterial DNA in Clinical Specimens by Broad-Range 16S rRNA Gene Enrichment.

Authors:  Sara Rassoulian Barrett; Noah G Hoffman; Christopher Rosenthal; Andrew Bryan; Desiree A Marshall; Joshua Lieberman; Alexander L Greninger; Vikas Peddu; Brad T Cookson; Stephen J Salipante
Journal:  J Clin Microbiol       Date:  2020-11-18       Impact factor: 5.948

4.  Comparison of Three Commercial Tools for Metagenomic Shotgun Sequencing Analysis.

Authors:  Matthew Thoendel; Patricio Jeraldo; Kerryl E Greenwood-Quaintance; Janet Yao; Nicholas Chia; Arlen D Hanssen; Matthew P Abdel; Robin Patel
Journal:  J Clin Microbiol       Date:  2020-02-24       Impact factor: 5.948

5.  Pavian: interactive analysis of metagenomics data for microbiome studies and pathogen identification.

Authors:  Florian P Breitwieser; Steven L Salzberg
Journal:  Bioinformatics       Date:  2020-02-15       Impact factor: 6.937

6.  Anomalous Phylogenetic Behavior of Ribosomal Proteins in Metagenome-Assembled Asgard Archaea.

Authors:  Sriram G Garg; Nils Kapust; Weili Lin; Michael Knopp; Fernando D K Tria; Shijulal Nelson-Sathi; Sven B Gould; Lu Fan; Ruixin Zhu; Chuanlun Zhang; William F Martin
Journal:  Genome Biol Evol       Date:  2021-01-07       Impact factor: 3.416

7.  MetaCompare: a computational pipeline for prioritizing environmental resistome risk.

Authors:  Min Oh; Amy Pruden; Chaoqi Chen; Lenwood S Heath; Kang Xia; Liqing Zhang
Journal:  FEMS Microbiol Ecol       Date:  2018-07-01       Impact factor: 4.194

8.  Expanding the taxonomic range in the fecal metagenome.

Authors:  Theo R Allnutt; Alexandra J Roth-Schulze; Leonard C Harrison
Journal:  BMC Bioinformatics       Date:  2021-06-09       Impact factor: 3.169

9.  Characterization of Grapevine Wood Microbiome Through a Metatranscriptomic Approach.

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Journal:  Microb Ecol       Date:  2021-06-30       Impact factor: 4.552

10.  The Nonsteroidal Anti-Inflammatory Drug Ketorolac Alters the Small Intestinal Microbiota and Bile Acids Without Inducing Intestinal Damage or Delaying Peristalsis in the Rat.

Authors:  Barbara Hutka; Bernadette Lázár; András S Tóth; Bence Ágg; Szilvia B László; Nóra Makra; Balázs Ligeti; Bálint Scheich; Kornél Király; Mahmoud Al-Khrasani; Dóra Szabó; Péter Ferdinandy; Klára Gyires; Zoltán S Zádori
Journal:  Front Pharmacol       Date:  2021-06-04       Impact factor: 5.810

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