Year: 2026
Type: article
Abstract: Environmental exposures such as air pollution may influence human health partly through microbiome, but statistical modeling is challenged by spatial dependence across regions and ecological correlations among taxa. We propose SpaMixed, a novel spatial mixed modeling framework for microbiome count data that incorporates both sources of dependence using conditional autoregressive priors. In simulations, SpaMixed achieved high feature selection power while maintaining low false positive rates and reduced estimation error relative to existing methods. Applied to two real studies with fine particulate matter (PM 2.5 ) exposures, SpaMixed identified biologically plausible PM 2.5 -associated taxa, supporting its utility for environmental microbiome research.
Source: Genome Medicine
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $5,290
Awards: The Oral Mycobiome and Risk of Pancreatic Cancer, The Oral Microbiome and Upper Aerodigestive Squamous Cell Cancer, BIOREPOSITORY OPTIMIZATION AND USE FOR ENDOTYPING CRITICALLY ILL SARS-COV-2 INFECTED PATIENTS, Maintenance and Enhancement of the Asian American enriched Cohort, Local microbiota signatures of pro-tumor immunity and checkpoint inhibition susceptibility in lung cancer, Age related loss of immune resilience during response to severe respiratory viral infections, Novel Computational Methods for Microbiome Data Analysis in Longitudinal Study, Microbial and host biomarker development for detection and prognosis of early stage non-small cell lung cancer
OpenAlex ID: W7165019748