A Bioinformatician's Guide to Metagenomics

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As random shotgun metagenomic projects proliferate and become the dominant source of publicly available sequence data, procedures for best practices in their execution and analysis become increasingly important. Based on our experience at the Joint Genome Institute, we describe step-by-step the chain of decisions accompanying a metagenomic project from the viewpoint of a bioinformatician. We guide the reader through a standard workflow for a metagenomic project beginning with pre-sequencing considerations such as community composition and sequence data type that will greatly influence downstream analyses. We proceed with recommendations for sampling and data generation including sample and metadata collection, community profiling, ... continued below

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Kunin, Victor; Copeland, Alex; Lapidus, Alla; Mavromatis, Konstantinos & Hugenholtz, Philip August 1, 2008.

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As random shotgun metagenomic projects proliferate and become the dominant source of publicly available sequence data, procedures for best practices in their execution and analysis become increasingly important. Based on our experience at the Joint Genome Institute, we describe step-by-step the chain of decisions accompanying a metagenomic project from the viewpoint of a bioinformatician. We guide the reader through a standard workflow for a metagenomic project beginning with pre-sequencing considerations such as community composition and sequence data type that will greatly influence downstream analyses. We proceed with recommendations for sampling and data generation including sample and metadata collection, community profiling, construction of shotgun libraries and sequencing strategies. We then discuss the application of generic sequence processing steps (read preprocessing, assembly, and gene prediction and annotation) to metagenomic datasets by contrast to genome projects. Different types of data analyses particular to metagenomes are then presented including binning, dominant population analysis and gene-centric analysis. Finally data management systems and issues are presented and discussed. We hope that this review will assist bioinformaticians and biologists in making better-informed decisions on their journey during a metagenomic project.

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  • Journal Name: PLoS

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  • Report No.: LBNL-916E
  • Grant Number: DE-AC02-05CH11231
  • Office of Scientific & Technical Information Report Number: 943447
  • Archival Resource Key: ark:/67531/metadc893039

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  • August 1, 2008

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  • Sept. 27, 2016, 1:39 a.m.

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  • Sept. 30, 2016, 6:20 p.m.

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Kunin, Victor; Copeland, Alex; Lapidus, Alla; Mavromatis, Konstantinos & Hugenholtz, Philip. A Bioinformatician's Guide to Metagenomics, article, August 1, 2008; Berkeley, California. (digital.library.unt.edu/ark:/67531/metadc893039/: accessed September 23, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.