The reduced cost and increased quality of DNA sequencing technology, coupled with an ever-expanding collection of experimental results, allows for the regular sequencing of individual human genomes, which has the potential to lower healthcare costs and improve outcomes by permitting highly personalized treatment and preventive medicine. This goal can only be reached with deep understanding of normal genetic variation (e.g. the 1000 Genomes project). Organizing such large-scale data in a computationally convenient structure is key. A representation of the human genome with genetic variation serves the same purpose as a picture of a completed jigsaw puzzle – it accelerates the placement of pieces.
Dr. Wyeth Wasserman of the University of British Columbia together with Alice Kaye (graduate student in Wasserman Lab) worked on implementing a novel graph model, the GNOmics Genome Model (GGM), for representing the human genome and other genetic data. GNOmics, an acronym for Graphs ‘N’ Omics, is the brand name used for the research, which is focused around the novel underlying graph model. A USA Patent for the GGM concept was awarded in early 2019. The project team has implemented and tested the initial software framework and demonstrated the capacity of using GGM to create an entire chromosome with other genetic variation information. Work will continue beyond this project with the goal to provide a robust software product with meaningful clinical usage and the patent has laid the foundation for future commercialization opportunities.