Scalable and efficient processing of genome sequence data, i.e. for variant
discovery, is key to the mainstream adoption of High Throughput technology for
disease prevention and for clinical use. Achieving scalability, however,
requires a significant effort to enable the parallel execution of the analysis
tools that make up the pipelines. This is facilitated by the new Spark versions
of the well-known GATK toolkit, which offer a black-box approach by
transparently exploiting the underlying Map Reduce architecture. In this paper
we report on our experience implementing a standard variant discovery pipeline
using GATK 4.0 with Docker-based deployment over a cluster. We provide a
preliminary performance analysis, comparing the processing times and cost to
those of the new Microsoft Genomics Services
