[HTML][HTML] Variable selection for sparse Dirichlet-multinomial regression with an application to microbiome data analysis
With the development of next generation sequencing technology, researchers have now
been able to study the microbiome composition using direct sequencing, whose output are …
been able to study the microbiome composition using direct sequencing, whose output are …
A logistic normal multinomial regression model for microbiome compositional data analysis
Changes in human microbiome are associated with many human diseases. Next generation
sequencing technologies make it possible to quantify the microbial composition without the …
sequencing technologies make it possible to quantify the microbial composition without the …
Zero-inflated generalized Dirichlet multinomial regression model for microbiome compositional data analysis
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 …
abundances of microbial taxa and linking the abundance to human diseases and traits …
A Dirichlet-tree multinomial regression model for associating dietary nutrients with gut microorganisms
T Wang, H Zhao - Biometrics, 2017 - academic.oup.com
Understanding the factors that alter the composition of the human microbiota may help
personalized healthcare strategies and therapeutic drug targets. In many sequencing …
personalized healthcare strategies and therapeutic drug targets. In many sequencing …
[HTML][HTML] An integrative Bayesian Dirichlet-multinomial regression model for the analysis of taxonomic abundances in microbiome data
Abstract Background The Human Microbiome has been variously associated with the
immune-regulatory mechanisms involved in the prevention or development of many non …
immune-regulatory mechanisms involved in the prevention or development of many non …
Dirichlet‐multinomial modelling outperforms alternatives for analysis of microbiome and other ecological count data
Molecular ecology regularly requires the analysis of count data that reflect the relative
abundance of features of a composition (eg, taxa in a community, gene transcripts in a …
abundance of features of a composition (eg, taxa in a community, gene transcripts in a …
Latent variable modeling for the microbiome
K Sankaran, SP Holmes - Biostatistics, 2019 - academic.oup.com
The human microbiome is a complex ecological system, and describing its structure and
function under different environmental conditions is important from both basic scientific and …
function under different environmental conditions is important from both basic scientific and …
Generalized linear models with linear constraints for microbiome compositional data
Motivated by regression analysis for microbiome compositional data, this article considers
generalized linear regression analysis with compositional covariates, where a group of …
generalized linear regression analysis with compositional covariates, where a group of …
Testing hypotheses about the microbiome using the linear decomposition model (LDM)
YJ Hu, GA Satten - Bioinformatics, 2020 - academic.oup.com
Motivation Methods for analyzing microbiome data generally fall into one of two groups: tests
of the global hypothesis of any microbiome effect, which do not provide any information on …
of the global hypothesis of any microbiome effect, which do not provide any information on …
[HTML][HTML] Identifying keystone species in the human gut microbiome from metagenomic timeseries using sparse linear regression
Human associated microbial communities exert tremendous influence over human health
and disease. With modern metagenomic sequencing methods it is now possible to follow the …
and disease. With modern metagenomic sequencing methods it is now possible to follow the …