ReviewFrontiers in genetics2019
Microbiome Multi-Omics Network Analysis: Statistical Considerations, Limitations, and Opportunities.
Review in Frontiers in genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 papers, 1 of them a synthesis that pooled it.
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
85 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Meta-analysis of microbiome association networks reveal patterns of dysbiosis in diseased microbiomes.Scientific reports · 2022Pooled it
- Effect ofNutrients · 2026Trial
- Personalized whole-body modeling links gut microbiota to metabolic perturbations in Alzheimer's disease.Gut microbes · 2026Article
- Integrating host-microbiome multi-omics with machine learning: methods, benchmarks, and translational applications.Science China. Life sciences · 2026Review
- Navigating multi-omic integration methods for human microbiome research.Nature 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
- Identifying High-Dimensional Genomic Factors Modulating Biological Networks Across MultiOmics Data.bioRxiv : the preprint server for biology · 2025Article
- Multi-Omics Insights into Microbial Interactions and Fermented Food Quality.Microorganisms · 2025Review
- The Gut Microbiome and Its Impact on Mood and Decision-Making: A Mechanistic and Therapeutic Review.Nutrients · 2025Review
- Spatio-Temporal Resolution of Microbial Functions and Taxa Associated With Cyanobacterial Harmful Algae Blooms Along a 500-Km Aquatic Continuum in the Lake Erie Watershed.Environmental microbiology · 2025Article
- Dietary Intervention with Cottonseed and Olive Oil Differentially Affect the Circulating Lipidome and Immunoregulatory Compounds-A Randomized Clinical Trial.Metabolites · 2025Article
- Do we need a standardized 16S rRNA gene amplicon sequencing analysis protocol for poultry microbiota research?Poultry science · 2025Review
- Recent advancements in artificial intelligence-powered cancer prediction from oral microbiome.Periodontology 2000 · 2025Review
- A generalized higher-order correlation analysis framework for multi-omics network inference.PLoS computational biology · 2025Article
- Omics in mini-livestock: a genomic perspective on the future of sustainable food systems.Frontiers in genetics · 2025Review
- Microbial influences on HPV infection and cervical carcinogenesis: emerging evidence from the vaginal microbiome.Frontiers in microbiology · 2025Review
- Semisynthetic simulation for microbiome data analysis.Briefings in bioinformatics · 2024Review
- AI in microbiome-related healthcare.Microbial biotechnology · 2024Review
- Exploration of the Changes in Facial Microbiota of Maskne Patients and Healthy Controls Before and After Wearing Masks Using 16 S rRNA Analysis.Journal of epidemiology and global health · 2024Article
25 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
The advent of large-scale microbiome studies affords newfound analytical opportunities to understand how these communities of microbes operate and relate to their environment. However, the analytical methodology needed to model microbiome data and integrate them with other data constructs remains nascent. This emergent analytical toolset frequently ports over techniques developed in other multi-omics investigations, especially the growing array of statistical and computational techniques for integrating and representing data through networks. While network analysis has emerged as a powerful approach to modeling microbiome data, oftentimes by integrating these data with other types of omics data to discern their functional linkages, it is not always evident if the statistical details of the approach being applied are consistent with the assumptions of microbiome data or how they impact data interpretation. In this review, we overview some of the most important network methods for integrative analysis, with an emphasis on methods that have been applied or have great potential to be applied to the analysis of multi-omics integration of microbiome data. We compare advantages and disadvantages of various statistical tools, assess their applicability to microbiome data, and discuss their biological interpretability. We also highlight on-going statistical challenges and opportunities for integrative network analysis of microbiome data.
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.