A web-based platform to support team-based genome diagnostics

Summary/Abstract
Genomic sequencing is rapidly becoming a standard tool in diagnosing complex diagnostic cases, especially in
critically ill newborns, and patients suffering from rare diseases. Current programs focused on addressing
these cases utilise a team-based approach to identify, interpret and evaluate a patient’s genetic variants.
These diverse teams include bioinformaticians, medical geneticists, genetic counselors, and physicians among
others, and encompass a wide range of expertise, skills, and literacy with computational methods. The
complexity of evaluating a genetic variant’s role in causing a patient’s specific set of phenotypes requires the
expertise and unique knowledge of all members of the team, and efficient methods of communication to
support rapid, asynchronous analysis of all potentially interesting observations. Currently, team members
perform analyses based on their own expertise, and rely on email communication, and regular in-person
meetings to integrate the knowledge of the team. This process is very time-intensive, and inefficient, especially
when previously undiagnosed cases are reviewed, and critical case information is hidden in myriad email
threads, presentations etc. This proposal brings together a highly popular tool for rapid visual analysis of
genetic variants with a commercial data management solution to provide a tool set to support team-based
genomic medicine. Our gene.iobio tool performs real-time analysis of a patient’s genome in an easy-to-use
web-based application, ensuring all team members can efficiently contribute their expertise in the diagnostic
process. This tool will be expanded with critica features, and brought up to a commercial standard of
deployment to ensure it can deliver on its potential in a reliable and repeatable manner. Our Mosaic tool
provides HIPAA-compliant access to distributed data, role-based authentication, as well as comprehensive
visualization, and communication features. This tool will also be expanded with functionality to support
integration with gene.iobio, as well as collaboration features designed to support this community. By improving
the features of both of these tools; providing analysis versioning; developing a deep API based integration
between them; and ensuring the combined package is fast, reliable and robust, we will deliver a software
product that is currently absent in the market; one that will improve collaboration on cases, save significant
amounts of time for all team members, and ultimately use these efficiency gains to ensure that genomic
medicine can be scaled up to serve more patients moving forwards. We will deploy this package in our own
rapid NICU sequencing program, and UDN clinical site to evaluate and refine the product.Narrative
We are developing a software package to support team-based, genomic analysis of challenging diagnostic
cases. This development focuses on significantly improving and integrating existing software tools to offer a
commercially viable product to fill a growing need in the market. We will test the utility and effectiveness of our
software by deploying in two of our own diagnostic analysis programs at the University of Utah.