ReviewThe ISME journal2019
Use and abuse of correlation analyses in microbial ecology.
Review in The ISME journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 131 papers.
What it found
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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
131 citing papers in PubMed.
- Riboflavin Supplementation Promotes Butyrate Production in the Absence of Gross Compositional Changes in the Gut Microbiota.Antioxidants & redox signaling · 2023Trial
- Species Distribution Models Support Distinct and Non-Random Climatic Constraints on Globally Distributed Generalist Fungi.Biology · 2026Article
- Article
- Biochar-Associated Shifts in Nitrogen Status, Microbial Communities and Dissolved Organic Matter in Salt-Affected Maize Soil.Microorganisms · 2026Article
- Metagenomic surveillance identifies a high-risk antibiotic resistance profile in community wastewater: a pilot study from Pakistan.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Microbial co-occurrence patterns and community assembly in seamount sediment cores: disentangling the effects of assembly processes on β-diversity.Applied and environmental microbiology · 2026Article
- Article
- CAM-Net: a context-aware network for identifying reliable microbial relations via optimal consortium.Briefings in bioinformatics · 2026Article
- Niche Overlap Is Not Enough: Same Overlap, Contrasting Fluctuations.Ecology letters · 2026Article
- Diversity, ecology, cell biology and evolution of the Asgard archaea.Nature reviews. Microbiology · 2026Review
- Navigating complexity: key considerations for studying fungal-bacterial interactions.mSystems · 2026Article
- Microbial inoculants with straw mediate degradation-level-specific changes in soil carbon cycling genes and microbial community.Environmental microbiome · 2026Article
- Co-occurrence networks reveal candidate AMF-microbe assemblages for generalist and crop-specific inocula.Mycorrhiza · 2026Article
- SparCC co-occurrence networking reveals intracommunity dynamics of the microbiome following colorectal surgery.Microbiology spectrum · 2026Article
- Soil Microbiome of Tropical Seasonal and Permanent Small Wetlands.Environmental microbiology reports · 2026Article
- Article
- Microbiota and horizontal microbial transmission dynamics associated with bramble (Rubus spp.) flowers.Environmental microbiome · 2026Article
- rCCLasso: a robust framework for microbial correlation network analysis reveals age-related microbial dynamics.Frontiers in cellular and infection microbiology · 2026Article
- A hybrid framework for disease biomarker discovery in microbiome research combining Bayesian networks, machine learning, and network-based methods.Biology methods & protocols · 2026Article
- A guide to network analysis, multi-omics integration, and applications in livestock microbiome research.World journal of microbiology & biotechnology · 2025Review
71 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
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Correlation analyses are often included in bioinformatic pipelines as methods for inferring taxon-taxon interactions. In this perspective, we highlight the pitfalls of inferring interactions from covariance and suggest methods, study design considerations, and additional data types for improving high-throughput interaction inferences. We conclude that correlation, even when augmented by other data types, almost never provides reliable information on direct biotic interactions in real-world ecosystems. These bioinformatically inferred associations are useful for reducing the number of potential hypotheses that we might test, but will never preclude the necessity for experimental validation.
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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.