Executive Summary : | The proposed project focuses on the rapid analysis and sequencing of genome data using the FPGA framework. The process involves creating an FPGA for dynamic sequencing, pre-loading it with a baseline genome sequence, reading cleaned genome sequences, character/string matching, creating two dictionaries for genome character/string mismatch, string variant, and variation frequency occurrence, and feeding the output to the cloud and GPU workstations. The dictionaries are then post-processed for variant annotation, while cloud data is used for analysis using IoT and EDGE devices. The project's significance lies in the era of personalized medicine, where large volumes of genomic data can improve personal and public health. Disease screening through regular sequencing of multi-omics data will become common practice in the near future, and rapid processing of data will help in faster disease diagnosis and better clinical management. The FPGA-based tools will serve the large community of genomic researchers and medical practitioners working with genomic data in research institutes and clinical settings. |