ArticlePLoS computational biology2020
Generalized estimating equation modeling on correlated microbiome sequencing data with longitudinal measures.
Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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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.
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Who cites it
7 citing papers in PubMed, 17 citations in OpenAlex.
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- Systemic Interplay of BDNF and Serotonin Pathways Defines Behavioral and Molecular Responses to Midbrain 5-HT7 Overexpression and Chronic Ethanol Consumption.Biomolecules · 2026Article
- metaGEENOME: an integrated framework for differential abundance analysis of microbiome data in cross-sectional and longitudinal studies.BMC bioinformatics · 2025Article
- Trends and correlates in HIV viral load monitoring and viral suppression among adolescents and young adults in Dar es Salaam, Tanzania.Tropical medicine & international health : TM & IH · 2024Article
- Assessing the effectiveness of targeted educational interventions on enhancing self-efficacy and foot care practices among diabetic women in Jordan.Frontiers in public health · 2024Article
- An analysis of socioeconomic factors on multiple chronic conditions and its economic burden: evidence from the National Health Service Survey in Yunnan Province, China.Frontiers in public health · 2023Article
- Functional response regression model on correlated longitudinal microbiome sequencing data.Statistical methods in medical research · 2022Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Existing models for assessing microbiome sequencing such as operational taxonomic units (OTUs) can only test predictors' effects on OTUs. There is limited work on how to estimate the correlations between multiple OTUs and incorporate such relationship into models to evaluate longitudinal OTU measures. We propose a novel approach to estimate OTU correlations based on their taxonomic structure, and apply such correlation structure in Generalized Estimating Equations (GEE) models to estimate both predictors' effects and OTU correlations. We develop a two-part Microbiome Taxonomic Longitudinal Correlation (MTLC) model for multivariate zero-inflated OTU outcomes based on the GEE framework. In addition, longitudinal and other types of repeated OTU measures are integrated in the MTLC model. Extensive simulations have been conducted to evaluate the performance of the MTLC method. Compared with the existing methods, the MTLC method shows robust and consistent estimation, and improved statistical power for testing predictors' effects. Lastly we demonstrate our proposed method by implementing it into a real human microbiome study to evaluate the obesity on twins.
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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.