title: An evaluation of the accuracy and speed of metagenome analysis tools.
abstract: Metagenome studies are becoming increasingly widespread, yielding important insights into microbial communities covering diverse environments from terrestrial and aquatic ecosystems to human skin and gut. With the advent of high-throughput sequencing platforms, the use of large scale shotgun sequencing approaches is now commonplace. However, a thorough independent benchmark comparing state-of-the-art metagenome analysis tools is lacking. Here, we present a benchmark where the most widely used tools are tested on complex, realistic data sets. Our results clearly show that the most widely used tools are not necessarily the most accurate, that the most accurate tool is not necessarily the most time consuming, and that there is a high degree of variability between available tools. These findings are important as the conclusions of any metagenomics study are affected by errors in the predicted community composition and functional capacity. Data sets and results are freely available from http://www.ucbioinformatics.org/metabenchmark.html.
authors.affiliation: Biomolecular Interaction Centre, University of Canterbury, Christchurch, New Zealand.|School of Biological Sciences, University of Canterbury, Christchurch, New Zealand.|Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
authors.forename: Stinus
authors.initials: S
authors.lastname: Lindgreen
authors.affiliation: Biomolecular Interaction Centre, University of Canterbury, Christchurch, New Zealand.|School of Biological Sciences, University of Canterbury, Christchurch, New Zealand.
authors.forename: Karen L
authors.initials: KL
authors.lastname: Adair
authors.affiliation: Biomolecular Interaction Centre, University of Canterbury, Christchurch, New Zealand.|School of Biological Sciences, University of Canterbury, Christchurch, New Zealand.
authors.forename: Paul P
authors.initials: PP
authors.lastname: Gardner
mesh_terms: D019295:Computational Biology / Q000379:methods; D017753:Ecosystem; D000069196:Gastrointestinal Microbiome / Q000235:genetics*; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D054892:Metagenome / Q000235:genetics*; D056186:Metagenomics / Q000379:methods*; D012867:Skin / Q000382:microbiology*; D012984:Software