ArticleFEMS microbiology ecology2016
Evaluating techniques for metagenome annotation using simulated sequence data.
Article in FEMS microbiology ecology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- Comparative evaluation of MG-RAST, MEGAN6 and Kraken2 for whole metagenome analysis of saffron corms for bacterial community structure and function.Molecular genetics and genomics : MGG · 2025Article
- Exploring protein natural diversity in environmental microbiomes with DeepMetagenome.Cell reports methods · 2024Article
- Multi-site analysis of biosynthetic gene clusters from the periodontitis oral microbiome.Journal of medical microbiology · 2024Article
- Differential interactions of Rickettsia species with tick microbiota in Rh. sanguineus and Rh. turanicus.Scientific reports · 2024Article
- Diverse bacterial consortia: key drivers of rhizosoil fertility modulating microbiome functions, plant physiology, nutrition, and soybean grain yield.Environmental microbiome · 2024Article
- Meta-omics integration approach reveals the effect of soil native microbiome diversity in the performance of inoculantFrontiers in plant science · 2023Article
- Bacterial communities of the psyllid pestPeerJ · 2023Article
- SeqScreen: accurate and sensitive functional screening of pathogenic sequences via ensemble learning.Genome biology · 2022Article
- Metagenomic community composition and resistome analysis in a full-scale cold climate wastewater treatment plant.Environmental microbiome · 2022Article
- Article
- Analyses of publicly availableVirulence · 2021Article
- Genome-resolved metagenomics using environmental and clinical samples.Briefings in bioinformatics · 2021Review
- Abundance and Compositions of B-Vitamin-Producing Microbes in the Mammalian Gut Vary Based on Feeding Strategies.mSystems · 2021Article
- Temperature Sensitivity and Composition of Nitrate-Reducing Microbiomes from a Full-Scale Woodchip Bioreactor Treating Agricultural Drainage Water.Microorganisms · 2021Article
- Plant Holobiont Theory: The Phytomicrobiome Plays a Central Role in Evolution and Success.Microorganisms · 2021Review
- Microbiome Structure and Function in Woodchip Bioreactors for Nitrate Removal in Agricultural Drainage Water.Frontiers in microbiology · 2021Article
- Novel microbiome dominated by Arcobacter during anoxic excurrent flow from an ocean blue hole in Andros Island, The Bahamas.PloS one · 2021Article
- Metagenomic analysis reveals rapid development of soil biota on fresh volcanic ash.Scientific reports · 2020Article
- Enteric Virome and Carcinogenesis in the Gut.Digestive diseases and sciences · 2020Review
- Rhizosphere Microbiome of Arid Land Medicinal Plants and Extra Cellular Enzymes Contribute to Their Abundance.Microorganisms · 2020Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The advent of next-generation sequencing has allowed huge amounts of DNA sequence data to be produced, advancing the capabilities of microbial ecosystem studies. The current challenge is to identify from which microorganisms and genes the DNA originated. Several tools and databases are available for annotating DNA sequences. The tools, databases and parameters used can have a significant impact on the results: naïve choice of these factors can result in a false representation of community composition and function. We use a simulated metagenome to show how different parameters affect annotation accuracy by evaluating the sequence annotation performances of MEGAN, MG-RAST, One Codex and Megablast. This simulated metagenome allowed the recovery of known organism and function abundances to be quantitatively evaluated, which is not possible for environmental metagenomes. The performance of each program and database varied, e.g. One Codex correctly annotated many sequences at the genus level, whereas MG-RAST RefSeq produced many false positive annotations. This effect decreased as the taxonomic level investigated increased. Selecting more stringent parameters decreases the annotation sensitivity, but increases precision. Ultimately, there is a trade-off between taxonomic resolution and annotation accuracy. These results should be considered when annotating metagenomes and interpreting results from previous studies.
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