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Updated: Mar 8, 2026

Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies
Published on: April 11, 2016
Next-generation sequencing: big data meets high performance computing
Bertil Schmidt1, Andreas Hildebrandt1
1Institut für Informatik, Johannes Gutenberg University Mainz, Germany.
Abstract:
The progress of next-generation sequencing has a major impact on medical and genomic research. This high-throughput technology can now produce billions of short DNA or RNA fragments in excess of a few terabytes of data in a single run. This leads to massive datasets used by a wide range of applications including personalized cancer treatment and precision medicine. In addition to the hugely increased throughput, the cost of using high-throughput technologies has been dramatically decreasing. A low sequencing cost of around US$1000 per genome has now rendered large population-scale projects feasible. However, to make effective use of the produced data, the design of big data algorithms and their efficient implementation on modern high performance computing systems is required.
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