ReviewFrontiers in microbiology2025
A comprehensive comparison of web-based tools for amplicon-metagenomic analysis.
Review in Frontiers in microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Bioinformatic tools for microbiome analysis: from raw sequences to biological insights.Frontiers in microbiology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Amplicon sequencing provides a suitable approach for microbiome profiling, supported by a variety of R-based and web-based tools. In this review, we systematically evaluated eight freely accessible web-based tools suitable for users without scripting experience, comparing their performance across modules including alpha and beta diversity, taxonomic composition, differential comparison, network and correlation analysis, functional profiling, machine learning, tree-plot and user experience. While all tools exhibit limited data filtering and normalization options, performance varied considerably across modules. Mian and MicrobiomeAnalyst 2.0 excelled in alpha diversity analysis and taxonomic composition analysis, METAGENassist outperformed others in beta diversity, and MicrobiomeAnalyst 2.0 achieved the highest score in differential comparison and functional analysis. Namco and Mian outperform in network analysis and correlation analysis, respectively. Machine-learning functions were comparable across animalcules, MicrobiomeAnalyst 2.0 and METAGENassist, with the best treeplot visualization in animalcules and MicrobiomeAnalyst 2.0. And, user experience was highest for animalcules and Mian. Overall, MicrobiomeAnalyst 2.0 achieving the highest overall performance, followed by Mian and Namco. Several limitations among evaluated tools include inconsistent accessibility, diverse input data formats, restricted feature sets, and incomplete retention of key information in exported figures. Future development should integrate preprocessing, interactive visualization and figure export, alongside advanced statistical methods, multi-omics integration and meta-analytical capabilities, to enhance flexibility, reproducibility and interpretability. This comprehensive assessment provides a practical reference for researchers in selecting the most suitable web-based tools for specific microbiome analysis tasks, highlighting the importance of both module-specific performance and overall tool capabilities.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.