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.