Genomic Variant Analysis Using Distributed In-Memory Computation Framework

In bioinformatics studies (eg. rare diseases, population genetics, etc.) variation files are used for high volumes of genetic data. A system that allows the transfer of high-volume genomic variation information, the search for variations on this data, filtering, prioritization, complex queries related to genotypes and hereditary properties will enable bioinformatics researchers to work efficiently on high volume data. We have developed a platform called B3SafirBiyo using scalable, distributed, in-memory computation techniques which enables users to do genomic variant analysis operations to be combined with a user-friendly interface to work on large-scale data and shorten the run-time. This framework also forms a infrastructure for machine learning studies on big genomic variation datasets.