Tyler Funnell

The paper links sugar-rich foods to microbiome disruption during antibiotic treatment in patients and mice.

This study shows that higher dietary fiber intake improves survival and reduces GVHD in hematopoietic cell transplant patients, with microbiome-mediated effects.

The paper introduces DAMUTA, a model that distinguishes DNA damage and misrepair processes in mutational signatures, showing improved resolution over existing methods in pan-cancer analysis.

The paper introduces FLORAL, a method for analyzing longitudinal microbiome data to identify biomarkers associated with time-varying outcomes, showing improved sensitivity and FDR control in simulations and real-world applications.

FLORAL improves microbial feature selection for microbiome data by addressing survival endpoints, longitudinal samples, and sequencing biases, showing better false-positive control and sensitivity in simulations and real data.

The paper introduces a scalable Bayesian method for phylogenetic tree inference from single-cell whole genome sequencing data, demonstrating its application on three datasets.

This study introduces a machine learning method to infer mutation signatures from both single nucleotide and structural variations in DNA repair deficient cancers, identifying new age-related and HRD-associated signatures in breast and ovarian cancers.

The paper analyzes the interaction between tumor and immune clones in ovarian cancer, finding that immune contexture patterns mirror malignant spread and that foldback inversions correlate with poor outcomes.