ArticleBioMed research international2014
Comparative metagenomic analysis of human gut microbiome composition using two different bioinformatic pipelines.
Article in BioMed research international, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.
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Who cites it
42 citing papers in PubMed.
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- Guardians within: Cross-talk between the gut microbiome and host immune system.World journal of gastrointestinal pathophysiology · 2025Review
- Application of MSB selective enrichment followed by amplicon MinION sequencing for multipathogen detection in smoked salmon.NPJ science of food · 2025Article
- The unresolved struggle of 16S rRNA amplicon sequencing: a benchmarking analysis of clustering and denoising methods.Environmental microbiome · 2025Article
- Bisphenol A (BPA) toxicity assessment and insights into current remediation strategies.RSC advances · 2024Review
- Exploring the Rhizospheric Microbial Communities under Long-Term Precipitation Regime in Norway Spruce Seed Orchard.International journal of molecular sciences · 2024Article
- The "Dry-Lab" Side of Food Authentication: Benchmark of Bioinformatic Pipelines for the Analysis of Metabarcoding Data.Foods (Basel, Switzerland) · 2024Article
- A Review of Web-Based Metagenomics Platforms for Analysing Next-Generation Sequence Data.Biochemical genetics · 2024Review
- Comparative metagenomic study unveils new insights on bacterial communities in two pine-feedingFrontiers in microbiology · 2024Article
- Current progresses and challenges for microbiome research in human health: a perspective.Frontiers in cellular and infection microbiology · 2024Article
- Characterisation of Milk Microbiota from Subclinical Mastitis and Apparently Healthy Dairy Cattle in Free State Province, South Africa.Veterinary sciences · 2023Article
- A general framework for powerful confounder adjustment in omics association studies.Bioinformatics (Oxford, England) · 2023Article
- Soil bacterial community structure and functioning in a long-term conservation agriculture experiment under semi-arid rainfed production system.Frontiers in microbiology · 2023Article
- Changes in the Cervical Microbiota of Women with Different High-Risk Human Papillomavirus Loads.Viruses · 2022Article
- Microbiome Analysis via OTU and ASV-Based Pipelines-A Comparative Interpretation of Ecological Data in WWTP Systems.Bioengineering (Basel, Switzerland) · 2022Article
- Structural and functional changes in soil bacterial communities by drifting spray application of a commercial red seaweed extract as revealed by metagenomics.Archives of microbiology · 2021Article
- Bacterial structure and dynamics in mango (Mangifera indica) orchards after long term organic and conventional treatments under subtropical ecosystem.Scientific reports · 2021Article
- Microbiota of Cow's Milk with Udder Pathologies.Microorganisms · 2021Article
- Gut microbiota composition in health-care facility-and community-onset diarrheic patients with Clostridioides difficile infection.Scientific reports · 2021Article
Corrections and comments
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Authors and funding
4 authors.
Funding
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Abstract
Technological advances in next-generation sequencing-based approaches have greatly impacted the analysis of microbial community composition. In particular, 16S rRNA-based methods have been widely used to analyze the whole set of bacteria present in a target environment. As a consequence, several specific bioinformatic pipelines have been developed to manage these data. MetaGenome Rapid Annotation using Subsystem Technology (MG-RAST) and Quantitative Insights Into Microbial Ecology (QIIME) are two freely available tools for metagenomic analyses that have been used in a wide range of studies. Here, we report the comparative analysis of the same dataset with both QIIME and MG-RAST in order to evaluate their accuracy in taxonomic assignment and in diversity analysis. We found that taxonomic assignment was more accurate with QIIME which, at family level, assigned a significantly higher number of reads. Thus, QIIME generated a more accurate BIOM file, which in turn improved the diversity analysis output. Finally, although informatics skills are needed to install QIIME, it offers a wide range of metrics that are useful for downstream applications and, not less important, it is not dependent on server times.
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Registered trials
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