Discrete False-Discovery Rate Improves Identification of Differentially Abundant Microbes

Normalization and microbial differential abundance strategies depend upon data characteristics

(2017) Sophie Weiss et al.   Microbiome

Balance Trees Reveal Microbial Niche Differentiation

(2017) James T. Morton et al.   mSystems

Reduced diversity and altered composition of the gut microbiome in individuals with myalgic encephalomyelitis/chronic fatigue syndrome

(2016) Ludovic Giloteaux et al.   Microbiome

Dog and human inflammatory bowel disease rely on overlapping yet distinct dysbiosis networks

(2016) Yoshiki Vázquez-Baeza et al.   Nature Microbiology

structSSI: Simultaneous and Selective Inference for Grouped or Hierarchically Structured Data

(2015) Kris Sankaran et al.   Journal of Statistical Software

The Treatment-Naive Microbiome in New-Onset Crohn’s Disease

(2014) Dirk Gevers et al.   Cell Host & Microbe

Inferring Correlation Networks from Genomic Survey Data

(2012) Jonathan Friedman et al.   PLoS Computational Biology

Finding consistent patterns: A nonparametric approach for identifying differential expression in RNA-Seq data

(2011) Jun Li et al.   STATISTICAL METHODS IN MEDICAL RESEARCH

Disordered Microbial Communities in the Upper Respiratory Tract of Cigarette Smokers

(2010) Emily S. Charlson et al.   PLoS One

Delivery mode shapes the acquisition and structure of the initial microbiota across multiple body habitats in newborns

(2010) M. G. Dominguez-Bello et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Metabolic Syndrome and Altered Gut Microbiota in Mice Lacking Toll-Like Receptor 5

(2010) M. Vijay-Kumar et al.   SCIENCE

On fuzzy familywise error rate and false discovery rate procedures for discrete distributions

(2009) E. Kulinskaya et al.   BIOMETRIKA