Eric A. Franzosa

Microbial-associated acylated putrescines as immunomodulatory molecules in inflammatory bowel diseases

The paper identifies N-acyl putrescines, particularly NOP, as immunomodulatory metabolites produced by gut microbiota that suppress inflammation in IBD models.

Enhanced multi-omic viral profiling from microbial community sequencing with BAQLaVa

BAQLaVa improves viral profiling from metagenomes and metatranscriptomes, revealing reduced virome diversity in inflammatory bowel diseases and novel phage-host relationships.

MaAsLin 3: Refining and extending generalized multivariable linear models for meta-omic association discovery

MaAsLin 3 fits hurdle models separating microbial prevalence (augmented logistic) and abundance (median-adjusted log-linear) associations, improving precision over existing differential abundance tools and showing 77% of IBD associations are prevalence-driven.

Comparative Assessment of Large Language Models for Microbial Phenotype Annotation

This study evaluates LLMs for microbial phenotype annotation, finding varied performance across models and traits, with confidence scores correlating with accuracy.

Pan-microbiome analysis along the human respiratory axis reveals an ecological continuum in health and collapse in disease

The paper presents a global respiratory pan-microbiome atlas integrating over 4,000 metagenomes to reveal ecological patterns in health and disease.

Commonly used compositional data analysis implementations are not advantageous in microbial differential abundance analyses benchmarked against biological ground truth

The paper benchmarks differential abundance methods using microbiome datasets with known biological ground truth, finding that compositional methods are less effective than commonly used non-compositional approaches.

Quantifying Metagenomic Strain Associations fromMicrobiomes with Anpan

Anpan quantifies strain-level associations in microbiomes, identifying genetic elements and phylogenetic effects linked to colorectal cancer, with improved accuracy over existing methods.

Evaluating metagenomic analyses for undercharacterized environments: what's needed to light up the microbial dark matter?

The paper evaluates metagenomic analysis methods in simulated and real environmental data, finding that newer marker-based methods perform better at lower taxonomic levels.

Discovering and exploring the hidden diversity of human gut viruses using highly enriched virome samples

The paper presents a method to discover new human gut viruses using enriched virome samples and reports over 162,000 novel viral sequences.

Profiling novel lateral gene transfer events in the human microbiome

The paper develops and validates a method to detect novel lateral gene transfer events in human microbiomes, identifying over 100K putative LGT events across >2K metagenomes.

Extending and improving metagenomic taxonomic profiling with uncharacterized species with MetaPhlAn 4

Marker genes for 26,970 species-level genome bins, 4,992 defined only by metagenome-assembled genomes, let MetaPhlAn 4 quantify uncharacterized species and beat MetaPhlAn 3, mOTUs and Bracken on synthetic benchmarks.

High-sensitivity pattern discovery in large, paired multi-omic datasets

This paper introduces HAllA, a method for discovering associations in multi-omic datasets, showing it outperforms existing approaches and identifies new biological relationships.

A Statistical Model for Describing and Simulating Microbial Community Profiles

The paper introduces a statistical model to simulate microbial community profiles and evaluates its performance in benchmarking analysis methods.

Population Structure Discovery in Meta-Analyzed Microbial Communities and Inflammatory Bowel Disease

The paper develops MMUPHin for meta-analysis of microbial communities in IBD, identifying consistent microbial associations and showing no discrete microbiome types.