Organization of Variation Based Personal Genetic Data with Relational Database

Abstract

Relational databases arecurrently being used effectively in many hospitals and clinics to store patientrecords and assay results. With the rapid development of sequencingtechnologies, sequencing costs have declined considerably. In addition, thenumber of personalized medicine practices is increasing day by day, andaccordingly the size of the personal genetic data that needs to be stored andquestioned is also increasing. Although relational databases are appropriatefor storing patient records and assay results, additional designs and solutionsare needed to efficiently store personal genetic data. In this study, a novelsolution is proposed for the integration of variation-based personal geneticdata into relational database. Within the scope of this solution, formats forboth non-structural and structural variation types have been developed andcompression algorithms have been used. The proposed method was tested with realdata of 2504 people, published by 1000 Genome Project. As a result of theanalyzes made, it was seen that the proposed method requires much less spacethan the space required to store the raw sequence data.