Using computational genomics to investigate human disease

Our Software Our Team


We develop software tools for genomic data analysis using a combination of biological, statistical, and engineering approaches to accurately detect and interpret inherited and somatic genetic variants. We focus on developing easy-to-use, web-based, visually-driven and interactive real-time software tools for intuitive analysis of genomic data. Our overall goal is to develop and apply software to better the care and outcomes of patients.

Clinical Genomics

We collaborate with medical geneticists and clinicians across a broad spectrum of human diseases, investigating the genetic etiology of these diseases and potential therapeutic opporunties.

Precision Oncology

We build and apply methods and visualizations for comprehensive profiling of tumors and their clonal structure across disease progression to directly impact the patient's care.

Variant Discovery

Building on our lab's previous work, we continue to develop computational algorithms for variant discovery, including the accurate detection of germline de novo and somatic cancer variants.

Visually-driven Genomics

Our software development approach prioritizes intuitive and interactive visual presentations of complex genomic data, making our software broadly accessible, regardless of computational expertise.



Realtime genomic data visualization and analysis web tools


K-mer based de novo variant calling

  • a direct comparison of k-mers
  • no reference bias
  • powered to call all variant types and sizes


Graph-based variant adjudication

  • improve germline and somatic variant evidences
  • retain true positives, discard false positives
  • joint calling on n+1 samples


Bayesian haplotype-based variant calling


Computational reconstruction of tumor clones


C++ API & command-line toolkit for working with BAM data


Fast structural variation detection toolbox


Some of our recent and featured publications are shown below, but you can find all of our publications on PubMed and Google Scholar


We are always looking for talented and motivated people to join our team! We are currently looking for post-docs with an emphasis in biostatistics and mathematics, as well as graduate students through the Utah Bioscience PhD and MD/PhD programs. Email us or check out our current job postings!


Gabor Marth

Principle Investigator
Professor of Human Genetics

Matt Velinder

Lab Manager
Clinical Genomics Leader / iobio

Alistair Ward

Director of Research and Science
COO, Co-Founder Frameshift Genomics

Yi Qiao

Director of Research and Science
Precision Oncology Leader / iobio

Andrew Farrell

Research Associate
RUFUS Developer

Tony DiSera

Senior Software Developer
Clinical Genomics / iobio

Dillon Lee

Senior Software Developer
Graphite Developer

Xiaomeng Huang

Assoc. Director of Research and Science
Precision Oncology

Stephanie Georges

Software Developer
Precision Oncology / iobio

Chase Miller

Director of Research and Science
CEO, Co-Founder Frameshift Genomics

Aditya Ekawade

Software Developer

Anders Pitman

Software and Backend Developer

Matt Bailey

Postdoctoral Fellow
Precision Oncology

Will Richards

Software Developer

Preetida Bhetariya

Postdoctoral Research Associate
Precision Oncology

Szabolcs Tarapcsak

Postdoctoral Fellow
Precision Oncology

Corin Thummel

Software Developer
Master's Student - Dept of Economics

Nancy Benson

Administrative Manager
Department of Human Genetics

Lab Alumni

Preetida Bhetariya

Bioinformatics Analyst / RA
Harvard School of Public Health

Erik Garrison

Postdoctoral Research Fellow
University of California, Santa Cruz

Meet Us!

We regularly attend meetings and conferences. In the coming months you can find us at:

American Society of Human Genetics (ASHG) Annual Meeting, October 15-19 2019
- Platform talk #297: The unbiased length spectrum of human de novo mutations in 4,330 children
- Poster #1041W: Oncogene.iobio: a web app for real-time, integrative examination and functional prioritization of tumor mutations
- Poster #1541F: Physician-driven genomic analysis using IOBIO web tools
- Poster #1452W: Context Matters: An Approachable Web Tool for Inspecting Variants in Genetic Disorders

Association for Molecular Pathology (AMP) Annual Meeting, November 7-9 2019

American College of Medical Genetics (ACMG) Annual Clinical Genetics Meeting, March 17-21 2020

Cold Spring Harbor Laboratory (CSHL) Biology of Genomes, May 5-9 2020


Our lab is part of the USTAR Center for Genetic Discovery (UCGD) and the Department of Human Genetics at the University of Utah


15 N 2030 E, Salt Lake City, UT

Phone Number

(801) 581-4422