Author

Meredith A.J. Hullar

Fred Hutch Cancer CenterORCID 0000-0002-5322-9568Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:metagenomics· 3 Research Focus:differential expression· 2 Organism:human· 2 Approach:statistical model· 2 Organism:bacteria (other)· 1 Approach:Bayesian inference· 1 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1

Frequent Co-Authors

Johanna W. LampeiD· 2 shared Timothy W. RandolphiD· 2 shared Arghavan Bahadorinejad· 1 shared Christoph A. RettenmeieriD· 1 shared Ivan V. IvanoviD· 1 shared Jing MaiD· 1 shared John Shepard· 1 shared Keith R. CurtisiD· 1 shared

Activity by Year

2018-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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2 shared papersMicrobiology

Johanna W. LampeORCID

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Author profile →

3 papers

Recent·Most cited

Mediation Analysis with Compositional Exposures

Jing Ma, Poorbita Kundu, Timothy W. Randolph, Sandi L. Navarro, Meredith A.J. Hullar

The paper introduces a latent variable mediation framework to analyze the gut microbiome's indirect effects on clinical outcomes through compositional data structures.

bioRxiv · Sep 29, 2026 · PreprintBioinformatics

Gut Microbiota Mediates the Association between Diet Quality and Ectopic Adiposity: The Multiethnic Cohort Adiposity Phenotype Study

Songran Wang, Meredith A.J. Hullar, Keith R. Curtis, Sandi Alexander Kwee, Song‐Yi Park, Christoph A. Rettenmeier, Kristine R. Monroe, Thomas M. Ernst, John Shepard, Lynne Ross Wilkens, Loı̈c Le Marchand, Johanna W. Lampe, Unhee Lim, Timothy W. Randolph

This study shows that higher diet quality reduces ectopic adiposity, and this effect is partially mediated by gut microbiota, specifically four bacterial genera.

bioRxiv · Apr 10, 2026 · PreprintMicrobiology

Bayesian Classification of Microbial Communities Based on 16S rRNA Metagenomic Data

Arghavan Bahadorinejad, Ivan V. Ivanov, Johanna W. Lampe, Meredith A.J. Hullar, Robert S. Chapkin, Ulisses Braga-Neto

The paper introduces a Bayesian classifier for 16S rRNA metagenomic data, showing it outperforms existing methods when sample size to dimensionality ratio is small.

bioRxiv · Jun 6, 2018 · PreprintBioinformatics