A logistic normal multinomial regression model for microbiome compositional data analysis

F Xia, J Chen, WK Fung, H Li - Biometrics, 2013 - Wiley Online Library
Changes in human microbiome are associated with many human diseases. Next generation
sequencing technologies make it possible to quantify the microbial composition without the …

Zero-inflated generalized Dirichlet multinomial regression model for microbiome compositional data analysis

ZZ Tang, G Chen - Biostatistics, 2019 - academic.oup.com
There is heightened interest in using high-throughput sequencing technologies to quantify
abundances of microbial taxa and linking the abundance to human diseases and traits …

[HTML][HTML] Variable selection for sparse Dirichlet-multinomial regression with an application to microbiome data analysis

J Chen, H Li - The annals of applied statistics, 2013 - ncbi.nlm.nih.gov
With the development of next generation sequencing technology, researchers have now
been able to study the microbiome composition using direct sequencing, whose output are …

[HTML][HTML] Statistical analysis of metagenomics data

ML Calle - Genomics & informatics, 2019 - ncbi.nlm.nih.gov
Understanding the role of the microbiome in human health and how it can be modulated is
becoming increasingly relevant for preventive medicine and for the medical management of …

A two-part mixed-effects model for analyzing longitudinal microbiome compositional data

EZ Chen, H Li - Bioinformatics, 2016 - academic.oup.com
Motivation: The human microbial communities are associated with many human diseases
such as obesity, diabetes and inflammatory bowel disease. High-throughput sequencing …

An integrative Bayesian Dirichlet-multinomial regression model for the analysis of taxonomic abundances in microbiome data

WD Wadsworth, R Argiento, M Guindani… - BMC …, 2017 - Springer
Abstract Background The Human Microbiome has been variously associated with the
immune-regulatory mechanisms involved in the prevention or development of many non …

Generalized linear models with linear constraints for microbiome compositional data

J Lu, P Shi, H Li - Biometrics, 2019 - Wiley Online Library
Motivated by regression analysis for microbiome compositional data, this article considers
generalized linear regression analysis with compositional covariates, where a group of …

A marginalized two-part Beta regression model for microbiome compositional data

H Chai, H Jiang, L Lin, L Liu - PLoS computational biology, 2018 - journals.plos.org
In microbiome studies, an important goal is to detect differential abundance of microbes
across clinical conditions and treatment options. However, the microbiome compositional …

Comparative metagenomic analysis of human gut microbiome composition using two different bioinformatic pipelines

V D'Argenio, G Casaburi, V Precone… - BioMed research …, 2014 - Wiley Online Library
Technological advances in next‐generation sequencing‐based approaches have greatly
impacted the analysis of microbial community composition. In particular, 16S rRNA‐based …

Kernel methods for regression analysis of microbiome compositional data

J Chen, H Li - Topics in applied statistics: 2012 symposium of the …, 2013 - Springer
With the development of next generation sequencing technologies, the human microbiome
can now be studied using direct DNA sequencing. Many human diseases have been shown …