ArticleAnnual review of statistics and its application2024
Analysis of Microbiome Data.
Article in Annual review of statistics and its application, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 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
17 citing papers in PubMed.
- Effects ofMicroorganisms · 2026Article
- Article
- Strain-Specific Fungal-Bacterial Co-Inoculation Regulates Rhizosphere Microecology and Plant-Soil-Microbiome Responses in Conifer Seedlings.Microorganisms · 2026Article
- Plant-Derived Foods and Medicines as Modulators of the Gut Microbiome: Molecular Interactions and Implications for Disease and Therapy.Molecules (Basel, Switzerland) · 2026Review
- Microbial Landscape of Bull (Animals : an open access journal from MDPI · 2026Article
- Multidimensional scaling informed by F-statistic: Visualizing grouped microbiome data with inference.PLoS computational biology · 2026Article
- The landscape of tissue-resident microbiota across normal, polyp, and colorectal cancer tissues.Nature communications · 2026Article
- Oral human papillomavirus infection aligns with a coordinated bacterial microbiome inferred virulence ecology.Frontiers in cellular and infection microbiology · 2026Article
- Microbiome mediation analysis: methods, assumptions, and practical considerations.Frontiers in cellular and infection microbiology · 2026Review
- Contribution of the Brain-Gut-Microbiome Axis to Intergenerational Abnormalities in a Rat Model of Perioperative Neurocognitive Disorder.Anesthesiology · 2025Article
- Bacterial communities of wild bee species and the western honey bee (Apis mellifera) (Hymenoptera: Apoidea): Alpine insights.Journal of insect science (Online) · 2025Article
- Oral microbial signatures of head and neck cancer patients with diverse longitudinal oral mucositis severity patterns.bioRxiv : the preprint server for biology · 2025Article
- Integrative systems biology approaches for analyzing microbiome dysbiosis and species interactions.Briefings in bioinformatics · 2025Review
- Machine learning models reveal Saccharomyces yeasts are associated with poor piglet growth in early development.Journal of animal science · 2025Article
- Quantifying uncertainty in microbiome-based prediction using Gaussian processes with microbial community dissimilarities.Bioinformatics advances · 2025Article
- Exploring the Interplay between the Hologenome and Complex Traits in Bovine and Porcine Animals Using Genome-Wide Association Analysis.International journal of molecular sciences · 2024Article
- Attempts to Understand Oral Mucositis in Head and Neck Cancer Patients through Omics Studies: A Narrative Review.International journal of molecular sciences · 2023Review
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
Abstract
The microbiome represents a hidden world of tiny organisms populating not only our surroundings but also our own bodies. By enabling comprehensive profiling of these invisible creatures, modern genomic sequencing tools have given us an unprecedented ability to characterize these populations and uncover their outsize impact on our environment and health. Statistical analysis of microbiome data is critical to infer patterns from the observed abundances. The application and development of analytical methods in this area require careful consideration of the unique aspects of microbiome profiles. We begin this review with a brief overview of microbiome data collection and processing and describe the resulting data structure. We then provide an overview of statistical methods for key tasks in microbiome data analysis, including data visualization, comparison of microbial abundance across groups, regression modeling, and network inference. We conclude with a discussion and highlight interesting future directions.
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.