Using computational genomics to investigate human disease

Our Software Our Team

Research

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, interactive and 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 opportunities.

Precision Oncology

We build and apply methods and visualizations for comprehensive profiling of tumors and their clonal structure across disease progression and therapeutic interventions 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.

Software

iobio

Realtime genomic data visualization and analysis web tools

RUFUS

K-mer based de novo variant calling

  • direct comparison of k-mers in sequencing reads
  • has no reference alignment bias
  • is powered to call all variant types and sizes

Graphite

Graph-based variant adjudication

  • improves germline and somatic variant call evidences
  • retains true positives, discards false positives
  • helps during joint calling on n+1 samples

freebayes

Bayesian haplotype-based variant calling

superseeker

Computational reconstruction of tumor clones

bayescmg

An applied Bayesian framework for the ACMG/AMP criteria

  • automatically applies ACMG criteria to vcf records
  • calculates a simple pathogencity probability
  • filters and prioritizes variants

ped_draw

Pedigree drawing with ease

  • quick and easy pedigree visualization
  • simple one-liner syntax
  • no dependencies

bamtools

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

Tangram

Fast structural variation detection toolbox

Publications

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

Apply!

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 our current job postings!

Members

Gabor Marth

Principle Investigator
Professor of Human Genetics

Matt Velinder

Lab Manager
Clinical Genomics Lead / iobio

Alistair Ward

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

Yi Qiao

Director of Research and Science
Precision Oncology Lead / 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
iobio

Anders Pitman

Software and Backend Developer
iobio

Matt Bailey

Postdoctoral Fellow
Precision Oncology

Will Richards

Software Developer
iobio

Szabolcs Tarapcsak

Postdoctoral Fellow
Precision Oncology

Niki Williams

Graduate Student
Somatic Mosaicism in Haematopoiesis

John Chamberlin

DBMI Graduate Student
Single-Cell Bioinformatics

Gage Black

Graduate Student
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 College of Medical Genetics (ACMG) Annual Clinical Genetics Meeting, March 17-21 2020
- Poster 324/PF: Varbayes: A Computational Tool For Generating Bayesian Probabilities Of Pathogenicity Using The Acmg/amp Guidelines
- Poster 433/PT: Clin.iobio analysis of a complex congenital heart disease and heterotaxy WGS case reveals de novo variation in RNF40

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

Our recent past meetings include:

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

Contact

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

Address

15 N 2030 E, Salt Lake City, UT

Phone Number

(801) 581-4422