Abstract
META-pipe is a complete service for the analysis of marine metagenomic data. It provides assembly of high-throughput sequence data, functional annotation of predicted genes, and taxonomic profiling. The functional annotation is computationally demanding and is therefore currently run on a high-performance computing cluster in Norway. However, additional compute resources are necessary to open the service to all ELIXIR users. We describe our approach for setting up and executing the functional analysis of META-pipe on additional academic and commercial clouds. Our goal is to provide a powerful analysis service that is easy to use and to maintain. Our design therefore uses a distributed architecture where we combine central servers with multiple distributed backends that execute the computationally intensive jobs. We believe our experiences developing and operating META-pipe provides a useful model for others that plan to provide a portal based data analysis service in ELIXIR and other organizations with geographically distributed compute and storage resources.
Highlights
ELIXIR was established to unite European life science resources
An ELIXIR user from Portugal may use a service maintained in Norway run on resources in Finland
We provide META-pipe as an Analysis-asa-Service for Norwegian and Finnish ELIXIR users
Summary
ELIXIR was established to unite European life science resources. It has 21 member states and more than 180 research organizations that each take responsibility for an analysis service, database, software tool, training material, or provide cloud storage and compute resources. One of the deliveries from ELIXIR Norway are marine metagenomics analysis services, whereas ELIXIR Finland provides cloud storage and compute resources. META-pipe[1] is a complete workflow for the analysis of marine metagenomic data. It provides assembly of high-throughput sequence data, functional annotation of predicted genes, and taxonomic profiling. Users log into the META-pipe web application where they can upload data to analyze, select tool parameters, start analyses, and download analysis results. Job execution is handled by the META-pipe backend, such that resource allocation, parallel execution, and fault handling is hidden from the user
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