Interoperable and scalable data analysis with microservices: applications in metabolomics.

ABSTRACT:

Motivation

Developing a robust and performant data analysis workflow that integrates all necessary components whilst still being able to scale over multiple compute nodes is a challenging task. We introduce a generic method based on the microservice architecture, where software tools are encapsulated as Docker containers that can be connected into scientific workflows and executed using the Kubernetes container orchestrator.

Results

We developed a Virtual Research Environment (VRE) which facilitates rapid integration of new tools and developing scalable and interoperable workflows for performing metabolomics data analysis. The environment can be launched on-demand on cloud resources and desktop computers. IT-expertise requirements on the user side are kept to a minimum, and

SUBMITTER: Emami Khoonsari P 

PROVIDER: S-EPMC6761976 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature