Distributed gene clinical decision support system based on cloud computing

The clinical decision support system can effectively solve the limitations of doctors' knowledge, reduce misdiagnosis and help enhance health. The traditional genetic data storage and analysis technology based on the stand-alone environment have limited scalability, which has been difficult to meet the computational requirements of rapid genetic data growth. In this paper, we propose a distributed gene clinical decision support system, which is named as GCDSS. We implemented a prototype based on cloud computing. To speed up the data processing of GCDSS, we present a novel distributed read mapping algorithm CloudBWA that leverages batch processing strategy to map reads on Apache Spark. Evaluations show that GCDSS and its component CloudBWA achieve outstanding performance and excellent scalability. Compared with distributed algorithms, CloudBWA achieves up to 2.63 times speedup over SparkBWA.

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