5 research outputs found
Design and evaluation of a genomics variant analysis pipeline using GATK Spark tools
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
Design and evaluation of a genomics variant analysis pipeline using GATK Spark tools
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.</p
Design and evaluation of a genomics variant analysis pipeline using GATK Spark tools
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.</p