Human and Molecular Genetics Center

Faculty

Elizabeth Worthey, PhD

 

Assistant Professor
Specialization: Bioinformatics, Genomics, Genetics

 

Liz WortheyWorthey Lab

Research Interests

My major focus is on the clinical and translational use of genomic data (primarily but not exclusively next generation sequencing data). This includes:

  • Use of clinical diagnostic whole genome or exome sequencing to identify causative mutations in pediatric patients with a variety of presumed single gene disorders. I carried out the first next generation sequence analysis used to alter the clinical treatment of a patient, and continue to perform and direct these same types of analysis on additional pediatric patients through our Medical College of Wisconsin (MCW) Whole Genome Sequencing (WGS) clinic (with final interpretation coming from clinical geneticist colleagues).
  • Application of whole genome or exome sequencing in a research setting to identify causative mutations in individuals with a variety of presumed single gene or complex disorders. I have a number of ongoing internal MCW and children’s hospital collaborations as well as external collaborations aimed at analyzing data from individuals, families, or cohorts to uncover the presumed disease associated mutations.
  • Providing useful and actionable pharmacogenomics readouts for both patients and presumed healthy populations. Specifically I am developing systems for reporting reliable and actionable pharmacogenomic data on our patients who have undergone whole genome or exome sequencing.

As part of these projects I am actively engaged in the development of tools and algorithms to support the transition of whole genome sequencing into the clinic. This includes development of:

  • Appropriate methods and tools to display and conceptualize large genomics datasets; a particular focus is on the development of tools for use by clinical colleagues performing WGS interpretation.
  • Pipelines and tools for tertiary sequence analysis in support of clinical diagnostic WGS. This includes development of novel methods, and implementation of existing algorithms for differentiation between disease associated mutations and polymorphisms.
  • Systems for high throughput identification and subsequent exclusion of likely sequencing or mapping errors, which confound WGS analysis.
  • Best practises for clinical WGS.


Click to enlargeIn addition I am interested in, and my group is performing comparative genomics analysis based on whole genome sequencing studies in order to provide more generalisable data relating to sequencing success. Examples include analysis of hard to sequence regions, comparative genomics to identify regions of conservation or divergence, genotype/phenotype correlation analysis, and study of the often neglected repetitive component of the genome. I am also involved in the application of ontologies to the storage and appropriate structuring of WGS derived data.

In addition to my human genetics research I am also involved in architecturing of software and data pipelines designed to search, analyze, visualize, integrate, and store high throughput data including sequence, SNP, CNV, and comparative genomics for basic and biomedical research as a Co-investigator of the Rat Genome Database. Specific areas of focus are genotype to phenotype correlation, and appropriate data visualizations.

I am also the MCW site PI for the InterMine project, which was developed to increase the power and flexibility with which scientists can utilize genomic data. This project applies the InterMine genomic database and platform to five Model Organism datasets: Mouse, Nematode, Budding yeast, Rat (my organism), and Zebrafish for the purpose of data integration and sharing. My goal is to be able to seamlessly extract model organism orthologue data including functional information and phenotype data derived from mutants from each of these species for use in our clinical and translational projects. Model organisms provide a wealth of phenotypic data of great use especially when there is little human phenotype information.

Click to enlargeI also lead the Bioinformatics component of an in house microbiome program. This program aims to characterize the microbial communities found at different sites on the human body, in both healthy and disease individuals. The long term goals of these projects are to advance our understanding of the human - microbe relationships, and to understand the role of these bacterial communities in the pathogenesis of human disease. We are engaged in a number of national programs using this data to uncover findings associated with human health and disease.

I am responsible for IT/vendor collaborations; including working with IT to define the IT infrastructure to support our clinical and research endeavors.

I am very committed to training the next wave of MD and PhD geneticists. I am responsible for training clinical and research staff, students, and Programmers/Bioinformaticians on sequence analysis and other genomics methodologies. I am invested in education of the upcoming wave of “clinical genomicists”, and have developed a laboratory for medical students and physicians to introduce them to this topic; an additional web based interactive WGS lab which will be used for training for continuing medical education is also in progress.

 

Recent Publications