ReviewBriefings in bioinformatics2022
Statistical challenges in longitudinal microbiome data analysis.
Review in Briefings in bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 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
48 citing papers in PubMed.
- Impact of fiber-containing enteral nutrition on microbial community dynamics in critically ill trauma patients: a pilot-randomized trial.BMC medicine · 2025Trial
- Bile acid metabolites predict multiple sclerosis progression and supplementation is safe in progressive disease.Med (New York, N.Y.) · 2025Trial
- Dynamics of Gut Microbiota After Fecal Microbiota Transplantation in Ulcerative Colitis: Success Linked to Control of Prevotellaceae.Journal of Crohn's & colitis · 2025Trial
- Extracting host-specific developmental signatures from longitudinal microbiome data.PLoS computational biology · 2026Article
- Role of microbiome in ocular surface disease: interpreting biology in a low-biomass environment.Current opinion in ophthalmology · 2026Review
- Epigenetic regulation by gut microbiota-derived metabolites in celiac disease.Biochemistry and biophysics reports · 2026Review
- Quorum Sensing and Quorum Quenching in Pseudomonas aeruginosa and Staphylococcus aureus Infections: Therapeutic Potential, Limitations and Clinical Challenges.Antibiotics (Basel, Switzerland) · 2026Review
- Longitudinal change of lung microbiome in chronic obstructive pulmonary disease: a prospective cohort study.Respiratory research · 2026Article
- Longitudinal long-read microbiome profiling in a canine model reveals how age, diet, and birth mode shape gut community dynamics.mSystems · 2026Article
- A Bayesian functional concurrent zero-inflated Dirichlet-multinomial regression model with application to infant microbiome.Biostatistics (Oxford, England) · 2026Article
- Oral dysbiosis: methodological evolution, the mobile resistome and the future of machine learning in dentistry.Journal of oral microbiology · 2026Review
- Design, processing, and modeling for longitudinal multiomics microbiome data.Frontiers in cellular and infection microbiology · 2026Review
- A guide to network analysis, multi-omics integration, and applications in livestock microbiome research.World journal of microbiology & biotechnology · 2025Review
- Article
- A systematic longitudinal study of microbiome: integrating temporal-spatial dimensions with causal and deep learning models.BMC genomics · 2025Article
- The Pediatric Microbiota-Gut-Brain Axis: Implications for Neuropsychiatric Development and Intervention.Children (Basel, Switzerland) · 2025Review
- Article
- Single-cell quantification of the microbiota by flow cytometry: MicFLY.bioRxiv : the preprint server for biology · 2025Article
- Gut Microbiome-Based Strategies for the Control of Carbapenem-Resistant Enterobacteriaceae.Journal of microbiology and biotechnology · 2025Review
- Oral microbial signatures of head and neck cancer patients with diverse longitudinal oral mucositis severity patterns.bioRxiv : the preprint server for biology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The microbiome is a complex and dynamic community of microorganisms that co-exist interdependently within an ecosystem, and interact with its host or environment. Longitudinal studies can capture temporal variation within the microbiome to gain mechanistic insights into microbial systems; however, current statistical methods are limited due to the complex and inherent features of the data. We have identified three analytical objectives in longitudinal microbial studies: (1) differential abundance over time and between sample groups, demographic factors or clinical variables of interest; (2) clustering of microorganisms evolving concomitantly across time and (3) network modelling to identify temporal relationships between microorganisms. This review explores the strengths and limitations of current methods to fulfill these objectives, compares different methods in simulation and case studies for objectives (1) and (2), and highlights opportunities for further methodological developments. R tutorials are provided to reproduce the analyses conducted in this review.
Indexed as
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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.