The Marth Laboratory at the University of Utah Medical School is developing computational tools for biomedical data analysis in rare-disease genomics, precision oncology, and somatic mosaicism discovery. Our team is part of the Utah Center for Genetic Discovery, a community of doctoral and postdoctoral trainees, data engineers, statisticians, and faculty, all engaged in computational genomics research.
As part of the NIH-funded Undiagnosed Diseases Network (UDN) Data Management and Coordination Center, the Marth Laboratory is building a comprehensive rare-disease patient data management platform and a large set of diagnostic tools for improving diagnostic rates in the UDN patient cohort. We are developing machine learning approaches for phenotype-driven patient-matching that leverage the UDN patients and additional large disease cohorts to identify groups of patients with similar phenotypes to identify shared causative genes within the group.
We are building novel deep-learning algorithms for personalizing treatment for each cancer patient based on the omic and pharmacologic characteristics of the patient’s tumor. In collaboration with cancer biologists, pharmacologists, and oncologists at the University of Utah and Huntsman Cancer Institute, we are implementing and testing these approaches in the clinic, currently for the treatment of advanced/metastatic breast cancers and primary/recurrent brain cancers. We are funded by the National Cancer Institute to utilize our learning approaches for identifying efficacious combination therapies for the treatment of breast cancer.
The Marth Laboratory is a funded participant of the Somatic Mosaicism across Human Tissues (SMaHT) Network, an NIH initiative to transform our understanding of how somatic mosaicism in organs, tissues, and cells influences human biology and disease (more about SMaHT). Our main contribution is the development of reference-free computational algorithms for detecting somatically acquired (rather than inherited) mutations from voluminous, high-throughput DNA sequencing data generated by the SMaHT Consortium for the construction of a comprehensive Healthy Human Somatic Mosaicism Atlas across multiple tissues in hundreds of donors.
We are developing highly visual, intuitive tools for real-time genome data browsing, disease variant prioritization, and metagenomics. Our approach prioritizes intuitive and interactive visual presentations of complex genomic data, making our software broadly accessible, regardless of computational expertise.
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 our current
job postings!
Our lab is part of the Utah Center for Genetic Discovery (UCGD) and the Department of Human Genetics at the University of Utah