Predictive analysis methods for human microbiome data with application to Parkinson’s disease

Prediction analysis for microbiome sequencing data

(2019) Tao Wang et al.   BIOMETRICS

Intestinal infection triggers Parkinson’s disease-like symptoms in Pink1−/− mice

(2019) Diana Matheoud et al.   NATURE

The oral microbiome of early stage Parkinson’s disease and its relationship with functional measures of motor and non-motor function

(2019) Dragos Mihaila et al.   PLoS One

The Gut Microbiome Alterations and Inflammation-Driven Pathogenesis of Alzheimer’s Disease—a Critical Review

(2018) Marta Sochocka et al.   MOLECULAR NEUROBIOLOGY

Predictive Modeling of Microbiome Data Using a Phylogeny-Regularized Generalized Linear Mixed Model

(2018) Jian Xiao et al.   Frontiers in Microbiology

Constructing Predictive Microbial Signatures at Multiple Taxonomic Levels

(2017) Tao Wang et al.   JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

Parkinson's disease and Parkinson's disease medications have distinct signatures of the gut microbiome

(2017) Erin M. Hill-Burns et al.   MOVEMENT DISORDERS

High-resolution characterization of the human microbiome

(2017) Cecilia Noecker et al.   Translational Research

Increased weight gain by C-section: Functional significance of the primordial microbiome

(2017) Keith A. Martinez et al.   Science Advances

Regression analysis for microbiome compositional data

(2016) Pixu Shi et al.   Annals of Applied Statistics

Gut Microbiota Regulate Motor Deficits and Neuroinflammation in a Model of Parkinson’s Disease

(2016) Timothy R. Sampson et al.   CELL

Association of host genome with intestinal microbial composition in a large healthy cohort

(2016) Williams Turpin et al.   NATURE GENETICS

The microbiome of the urinary tract—a role beyond infection

(2015) Samantha A. Whiteside et al.   Nature Reviews Urology

Why significant variables aren’t automatically good predictors

(2015) Adeline Lo et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Assessment and Selection of Competing Models for Zero-Inflated Microbiome Data

(2015) Lizhen Xu et al.   PLoS One

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

(2013) Jun Chen et al.   Annals of Applied Statistics

A Logistic Normal Multinomial Regression Model for Microbiome Compositional Data Analysis

(2013) Fan Xia et al.   BIOMETRICS

Chromosome 9p21 genetic variation explains 13% of cardiovascular disease incidence but does not improve risk prediction

(2013) K. Gränsbo et al.   JOURNAL OF INTERNAL MEDICINE

Structure, function and diversity of the healthy human microbiome

(2012)   NATURE

Common polygenic variation contributes to risk of schizophrenia and bipolar disorder

(2009) Shaun M. Purcell et al.   NATURE

Genome-wide association study identifies common variants at four loci as genetic risk factors for Parkinson's disease

(2009) Wataru Satake et al.   NATURE GENETICS

Generalized linear mixed models: a practical guide for ecology and evolution

(2009) Benjamin M. Bolker et al.   TRENDS IN ECOLOGY & EVOLUTION

A clarifying comparison of methods for controlling the false discovery rate

(2008) Yaling Yin et al.   JOURNAL OF STATISTICAL PLANNING AND INFERENCE

Common variants at 30 loci contribute to polygenic dyslipidemia

(2008) Sekar Kathiresan et al.   NATURE GENETICS