ArticleNature communications2022
Linear and nonlinear correlation estimators unveil undescribed taxa interactions in microbiome data.
Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 90 papers, 2 of them syntheses that pooled it.
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Who cites it
90 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Effect of bovine respiratory disease on the respiratory microbiome: a meta-analysis.Frontiers in cellular and infection microbiology · 2023Pooled it
- Pooled it
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- The Adult Aedes aegypti Bacterial Microbiota is Robust to Infection with the Obligate Microsporidian Parasite Edhazardia aedis.Environmental microbiology · 2026Article
- Lifestyle Impacts the Oral Microbiome of Classical and Post-Classical Societies in Italy.American journal of biological anthropology · 2026Article
- Effect ofMicrobiology spectrum · 2026Article
- Landscape-associated pesticide contamination shapes pollen provision microbiomes in Osmia cornifrons (Hymenoptera: Megachilidae).Journal of insect science (Online) · 2026Article
- Microbiome analysis and epigenetic patterns revealed distinct differences between two elm species with contrasting Dutch elm disease resistance.Microbiome · 2026Article
- Supporting crop yields under climate change by engineering innate soil microbiomes.Applied and environmental microbiology · 2026Article
- Sources and traits of bacteria and fungi found in the near-surface atmosphere.Applied and environmental microbiology · 2026Article
- Branched chain amino acid metabolism and microbiome in adolescents with obesity during weight loss therapy.The Journal of clinical investigation · 2026Observational
- A New Framework to Empower Ecosystem Assessment Through the Integration of eDNA Inventories, Graph Theory and Niche Modelling.Ecology letters · 2026Article
- TestNet: a method for inferring microbial networks with false discovery rate control for clustered and unclustered samples.Genome biology · 2026Article
- Network topology of the gut microbiome associates with metabolic health in obesity.Nature communications · 2026Article
- Insights into the role of crustose coralline algae microbiomes on coral larval settlement in the Great Barrier Reef.Environmental microbiome · 2026Article
- Anaerobic digestate fertilization reshapes the rhizosphere bacterial communities of Lolium perenne L. at compositional and predicted functional potential levels.World journal of microbiology & biotechnology · 2026Article
- Protocol for constructing correlation-based molecular networks from large-scale untargeted metabolomics data.bioRxiv : the preprint server for biology · 2026Article
- Unraveling the diagnostic and prognostic signatures of oral microbiota in head and neck cancer.BMC biology · 2026Article
30 more citing papers are in PubMed but not listed here.
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It is well-known that human gut microbiota form an ecosystem where microbes interact with each other. Due to complex underlying interactions, some microbes may correlate nonlinearly. There are no measures in the microbiome literature we know of that quantify these nonlinear relationships. Here, we develop a methodology called Sparse Estimation of Correlations among Microbiomes (SECOM) for estimating linear and nonlinear relationships among microbes while maintaining the sparsity. SECOM accounts for both sample and taxon-specific biases in its model. Its statistical properties are evaluated analytically and by comprehensive simulation studies. We test SECOM in two real data sets, namely, forehead and palm microbiome data from college-age adults, and Norwegian infant gut microbiome data. Given that forehead and palm are related to skin, as desired, SECOM discovers each genus to be highly correlated between the two sites, but that is not the case with any of the competing methods. It is well-known that infant gut evolves as the child grows. Using SECOM, for the first time in the literature, we characterize temporal changes in correlations among bacterial families during a baby's first year after birth.
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