Tami D. Lieberman

AccuSNV is a deep learning tool for high-accuracy bacterial SNV calling that outperforms existing methods in simulated and real datasets.

This paper introduces SimPhyNI, a framework for microbial GWAS that improves precision and recall in detecting gene-gene and gene-trait associations in bacterial genomes.

The paper investigates the role of phage-mediated selection in shaping Cutibacterium acnes populations on human skin and finds weak phage pressure due to physical barriers limiting phage exposure.

PHLAME improves strain-resolved metagenomic analysis by combining reference-based methods with novelty detection, revealing new intraspecies associations in human microbiomes.

This study shows that de novo mutations in Burkholderia dolosa cause phenotypic switching, with O-antigen loss increasing immune cell uptake but reducing lung competitiveness, depending on infection duration and tissue localization.

The paper shows that intraspecies warfare limits strain coexistence in human skin microbiomes by analyzing interactions between Staphylococcus epidermidis isolates.

This paper compares microbiome analysis methods for low biomass skin samples, finding that metagenomics captures diversity better than 16S amplicon sequencing.

This study compares the facial skin microbiome of humans, chimpanzees, and gorillas, finding humans have a unique, low-diversity microbiome dominated by Cutibacterium, absent in other primates.

The paper reveals hidden strain dynamics in skin microbiome species, showing that while strains are transient, some are more stable and may be targets for therapeutic interventions.

The paper reanalyzes data from Shen et al. to argue that most synonymous mutations in yeast genes are not deleterious, challenging their original conclusions about fitness effects.