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 …
Robust and scalable models of microbiome dynamics
Microbes are everywhere, including in and on our bodies, and have been shown to play key
roles in a variety of prevalent human diseases. Consequently, there has been intense …
roles in a variety of prevalent human diseases. Consequently, there has been intense …
Bayesian nonparametric ordination for the analysis of microbial communities
Human microbiome studies use sequencing technologies to measure the abundance of
bacterial species or Operational Taxonomic Units (OTUs) in samples of biological material …
bacterial species or Operational Taxonomic Units (OTUs) in samples of biological material …
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 …
Mimix: A bayesian mixed-effects model for microbiome data from designed experiments
Recent advances in bioinformatics have made high-throughput microbiome data widely
available, and new statistical tools are required to maximize the information gained from …
available, and new statistical tools are required to maximize the information gained from …
A common atoms model for the Bayesian nonparametric analysis of nested data
The use of large datasets for targeted therapeutic interventions requires new ways to
characterize the heterogeneity observed across subgroups of a specific population. In …
characterize the heterogeneity observed across subgroups of a specific population. In …
A Bayesian zero-inflated negative binomial regression model for the integrative analysis of microbiome data
Microbiome omics approaches can reveal intriguing relationships between the human
microbiome and certain disease states. Along with identification of specific bacteria taxa …
microbiome and certain disease states. Along with identification of specific bacteria taxa …
A Bayesian model of microbiome data for simultaneous identification of covariate associations and prediction of phenotypic outcomes
MD Koslovsky, KL Hoffman, CR Daniel… - The Annals of Applied …, 2020 - projecteuclid.org
One of the major research questions regarding human microbiome studies is the feasibility
of designing interventions that modulate the composition of the microbiome to promote …
of designing interventions that modulate the composition of the microbiome to promote …
Statistical challenges in longitudinal microbiome data analysis
The microbiome is a complex and dynamic community of microorganisms that co-exist
interdependently within an ecosystem, and interact with its host or environment. Longitudinal …
interdependently within an ecosystem, and interact with its host or environment. Longitudinal …
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 …