ArticlePLoS computational biology2017
A Bayesian method for detecting pairwise associations in compositional data.
Article in PLoS computational biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Secretor status is a modifier of vaginal microbiota-associated preterm birth risk.Microbial genomics · 2024Article
- Niche differentiation in microbial communities with stable genomic traits over time in engineered systems.The ISME journal · 2024Article
- Geology defines microbiome structure and composition in nunataks and valleys of the Sør Rondane Mountains, East Antarctica.Frontiers in microbiology · 2024Article
- Candida expansion in the gut of lung cancer patients associates with an ecological signature that supports growth under dysbiotic conditions.Nature communications · 2023Article
- A Bayesian method for identifying associations between response variables and bacterial community composition.PLoS computational biology · 2022Article
- Chromosomally normal miscarriage is associated with vaginal dysbiosis and local inflammation.BMC medicine · 2022Article
- Modeling Microbial Community Networks: Methods and Tools.Current genomics · 2021Review
- A statistical model for describing and simulating microbial community profiles.PLoS computational biology · 2021Article
- BEEM-Static: Accurate inference of ecological interactions from cross-sectional microbiome data.PLoS computational biology · 2021Article
- NetCoMi: network construction and comparison for microbiome data in R.Briefings in bioinformatics · 2021Article
- A zero inflated log-normal model for inference of sparse microbial association networks.PLoS computational biology · 2021Article
- An Introduction to Next Generation Sequencing Bioinformatic Analysis in Gut Microbiome Studies.Biomolecules · 2021Review
- Experimentally-validated correlation analysis reveals new anaerobic methane oxidation partnerships with consortium-level heterogeneity in diazotrophy.The ISME journal · 2021Article
- DAnIEL: A User-Friendly Web Server for Fungal ITS Amplicon Sequencing Data.Frontiers in microbiology · 2021Article
- Antibiotics create a shift from mutualism to competition in human gut communities with a longer-lasting impact on fungi than bacteria.Microbiome · 2020Article
- Article
- A metagenome-wide association study of gut microbiome and visceral fat accumulation.Computational and structural biotechnology journal · 2020Article
- tmap: an integrative framework based on topological data analysis for population-scale microbiome stratification and association studies.Genome biology · 2019Article
- Mapping the microbial interactome: Statistical and experimental approaches for microbiome network inference.Experimental biology and medicine (Maywood, N.J.) · 2019Review
- Best practices for analysing microbiomes.Nature reviews. Microbiology · 2018Review
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Authors and funding
4 authors.
Funding
Abstract
Compositional data consist of vectors of proportions normalized to a constant sum from a basis of unobserved counts. The sum constraint makes inference on correlations between unconstrained features challenging due to the information loss from normalization. However, such correlations are of long-standing interest in fields including ecology. We propose a novel Bayesian framework (BAnOCC: Bayesian Analysis of Compositional Covariance) to estimate a sparse precision matrix through a LASSO prior. The resulting posterior, generated by MCMC sampling, allows uncertainty quantification of any function of the precision matrix, including the correlation matrix. We also use a first-order Taylor expansion to approximate the transformation from the unobserved counts to the composition in order to investigate what characteristics of the unobserved counts can make the correlations more or less difficult to infer. On simulated datasets, we show that BAnOCC infers the true network as well as previous methods while offering the advantage of posterior inference. Larger and more realistic simulated datasets further showed that BAnOCC performs well as measured by type I and type II error rates. Finally, we apply BAnOCC to a microbial ecology dataset from the Human Microbiome Project, which in addition to reproducing established ecological results revealed unique, competition-based roles for Proteobacteria in multiple distinct habitats.
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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.