ArticleBriefings in bioinformatics2025
Elementary methods provide more replicable results in microbial differential abundance analysis.
Article in Briefings in bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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
11 citing papers in PubMed.
- Article
- Higher abundance ofmSystems · 2026Article
- Effects of Nutrient Limitation on Antarctic Microbial Community Diversity, Composition, and Interactions: A Cryoconite Microcosm Study.Microorganisms · 2026Article
- Bacterial communities in domestic washing machines associated with user-perceived odours.Applied microbiology and biotechnology · 2026Article
- Bacterial taxa associated with lung cancer cases in Southeast Asians: a pilot case-control study.Cellular oncology (Dordrecht, Netherlands) · 2026Article
- Lifestyle associates with unique resistome and microbiome signatures in children.BMC microbiology · 2026Article
- MaAsLin 3: refining and extending generalized multivariable linear models for meta-omic association discovery.Nature methods · 2026Article
- Microbiome differential abundance methodologies to detect relevant taxa associated with chemotherapy toxicity rate in colorectal cancer.Bioinformatics advances · 2026Article
- metadeconfoundR: Covariate analysis of high-dimensional cross-sectional omics data.Bioinformatics advances · 2026Article
- Gut microbiome diversity, genus-level variation, and associations with clinical features in critically ill patients.Frontiers in medicine · 2026Article
- Distinct patterns and interactions of microbiota and short-chain fatty acids in breast milk and infant gut from rural and urban dyads.Frontiers in microbiology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Differential abundance analysis (DAA) is a key component of microbiome studies. Although dozens of methods exist, there is currently no consensus on the preferred methods. While the correctness of results in DAA is an ambiguous concept and cannot be fully evaluated without setting the ground truth and employing simulated data, we argue that a well-performing method should be effective in producing highly reproducible results. We compared the performance of 14 DAA methods by employing datasets from 53 taxonomic profiling studies based on 16S rRNA gene or shotgun metagenomic sequencing. For each method, we examined how the results replicated between random partitions of each dataset and between datasets from separate studies. While certain methods showed good consistency, some widely used methods were observed to produce a substantial number of conflicting findings. Overall, when considering consistency together with sensitivity, the best performance was attained by analyzing relative abundances with a nonparametric method (Wilcoxon test or ordinal regression model) or linear regression/t-test. Moreover, a comparable performance was obtained by analyzing presence/absence of taxa with logistic regression.
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.