ArticleFrontiers in microbiology2018
Negative Binomial Mixed Models for Analyzing Longitudinal Microbiome Data.
Article in Frontiers in microbiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
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
37 citing papers in PubMed.
- Correlates of antenatal care visits among expectant mothers in Malawi: application of generalised estimating equations and likelihood-based poisson and negative binomial mixed models.Reproductive health · 2026Article
- Longitudinal change of lung microbiome in chronic obstructive pulmonary disease: a prospective cohort study.Respiratory research · 2026Article
- Canine Tooth Microbiome Gingival Index: a new microbiome-derived measure of gingival health validated by nutritional intervention.Frontiers in veterinary science · 2026Article
- BIOMARKER DETECTION FOR DISEASE CLASSIFICATION IN LONGITUDINAL MICROBIOME DATA.The annals of applied statistics · 2025Article
- miRglmm: a generalized linear mixed model of isomiR-level counts improves estimation of miRNA-level differential expression and uncovers variable differential expression between isomiRs.Genome biology · 2025Article
- Robust phylogenetic tree-based microbiome association test using repeatedly measured data for composition bias.BMC bioinformatics · 2025Article
- Article
- Wise Roles and Future Visionary Endeavors of Current Emperor: Advancing Dynamic Methods for Longitudinal Microbiome Meta-Omics Data in Personalized and Precision Medicine.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Review
- Elucidating nematode diversity and prevalence in moose across a wide latitudinal gradient using DNA metabarcoding.International journal for parasitology. Parasites and wildlife · 2024Article
- Exploring associations between the teat apex metagenome andApplied and environmental microbiology · 2024Article
- A GLM-based zero-inflated generalized Poisson factor model for analyzing microbiome data.Frontiers in microbiology · 2024Article
- Longitudinal Analysis of Canine Oral Microbiome Using Whole Genome Sequencing in Aging Companion Dogs.Animals : an open access journal from MDPI · 2023Article
- Machine learning and statistical models for analyzing multilevel patent data.Scientific reports · 2023Article
- Infants' gut microbiome data: A Bayesian Marginal Zero-inflated Negative Binomial regression model for multivariate analyses of count data.Computational and structural biotechnology journal · 2023Article
- Statistical challenges in longitudinal microbiome data analysis.Briefings in bioinformatics · 2022Review
- A comparison of methods for multiple degree of freedom testing in repeated measures RNA-sequencing experiments.BMC medical research methodology · 2022Article
- Evaluation of an audit and feedback intervention to reduce gentamicin prescription errors in newborn treatment (ReGENT) in neonatal inpatient care in Kenya: a controlled interrupted time series study protocol.Implementation science : IS · 2022Article
- Functional response regression model on correlated longitudinal microbiome sequencing data.Statistical methods in medical research · 2022Article
- MiRKAT-MC: A Distance-Based Microbiome Kernel Association Test With Multi-Categorical Outcomes.Frontiers in genetics · 2022Article
- ARZIMM: A Novel Analytic Platform for the Inference of Microbial Interactions and Community Stability from Longitudinal Microbiome Study.Frontiers in genetics · 2022Article
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 metagenomics sequencing data provide valuable resources for investigating the associations between the microbiome and host environmental/clinical factors and the dynamic changes of microbial abundance over time. The distinct properties of microbiome measurements include varied total sequence reads across samples, over-dispersion and zero-inflation. Additionally, microbiome studies usually collect samples longitudinally, which introduces time-dependent and correlation structures among the samples and thus further complicates the analysis and interpretation of microbiome count data. In this article, we propose negative binomial mixed models (NBMMs) for longitudinal microbiome studies. The proposed NBMMs can efficiently handle over-dispersion and varying total reads, and can account for the dynamic trend and correlation among longitudinal samples. We develop an efficient and stable algorithm to fit the NBMMs. We evaluate and demonstrate the NBMMs method via extensive simulation studies and application to a longitudinal microbiome data. The results show that the proposed method has desirable properties and outperform the previously used methods in terms of flexible framework for modeling correlation structures and detecting dynamic effects. We have developed an R package NBZIMM to implement the proposed method, which is freely available from the public GitHub repository http://github.com//nyiuab//NBZIMM and provides a useful tool for analyzing longitudinal 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.