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Marc Fiume, Andrew Brook, Eric Smith, and Michael Brudno (Department of Computer Science, University of Toronto, Toronto, Canada)High Throughput Sequencing (HTS) technologies have revolutionized the speed and economy with which genomic information can be obtained, and are providing a means for deep cataloguing of human variation. One of the most challenging problems is in identifying those few genetic variants among millions predicted that are actually causal in disease. For this purpose we introduce MedSavant: a software platform for accelerating the identification of disease-causing genetic variants found in population sequencing studies by enabling complex and dynamic querying of patient data. The platform is comprised of two parts: a graphical interface and a backend database. The database is designed to securely store patient data across three main axes: (1) basic patient data: e.g. age, sex, and pedigree (2) phenotype data: e.g. disease, signs, and symptoms (3) genotype data: e.g. candidate variants, their types, and genomic locations. It is being engineered to handle huge volumes of data that can be updated frequently while still being efficiently searchable. The client-side interface enables users to dynamically visualize global trends in the data, construct complex queries, and analyze the results.