Computational epigenetics & biomedical data science

Tiffany Eulalio, PhD

I study how genetic, epigenetic, and clinical variation shapes long-term human health.

I am an Assistant Professor at the University of South Florida. My research combines statistical genetics, molecular epidemiology, and reproducible computational analysis across large human cohorts, with a particular interest in cancer survivorship and complex disease.

Selected work View CV

Assistant Professor
University of South Florida

Across my workI connect molecular measurements with the clinical histories and lived trajectories they represent.

Selected work

Research highlights

A selection of research spanning cancer survivorship, regulatory genomics, and computational methods.

Conceptual illustration of childhood cancer treatment and molecular signals associated with long-term cardiometabolic health

Cancer survivorship

Epigenetics of long-term health after cancer therapy

I study how treatment exposures become biologically embedded, using DNA methylation and longitudinal clinical data to understand cardiometabolic health in survivors of childhood cancer.

DNA methylation · Clinical phenotypes · Mediation · RNA-seq

Related work

Illustration of bulk brain DNA methylation measurements resolving into four cell-type-specific signal patterns

Regulatory genomics

Cell-specific regulation in Alzheimer’s disease

My doctoral work mapped cell-type-specific methylation quantitative trait loci in the human brain and examined how regulatory variation contributes to Alzheimer’s disease biology.

meQTLs · Statistical genetics · Fine-mapping · Brain epigenomics

Related work

Illustration of CpG methylation patterns across a gene region transforming into two regional principal-component signals

Methods & software

Capturing regional DNA methylation signal

I developed regionalpcs, a Bioconductor R package that uses principal components to summarize patterns across CpGs within gene regions. The method captures more of the regional signal than simple averaging and improves sensitivity to methylation associations.

DNA methylation · Principal components · R/Bioconductor

Related work

About

From biomedical questions to careful analysis

My training sits at the intersection of biomedical informatics, epidemiology, and statistical genomics. I earned my PhD in Biomedical Informatics at Stanford University and later conducted research at Johns Hopkins University and St. Jude Children’s Research Hospital.

At USF, I lead and collaborate on studies integrating whole-genome sequencing, RNA sequencing, DNA methylation, electronic health records, and longitudinal clinical phenotypes. I care about methods that are statistically rigorous, biologically interpretable, and reproducible by the next person who works with the data.

EpigenomicsStatistical geneticsMolecular epidemiologyMulti-omic integrationReproducible computing

Selected publications