Arteria: An automation system for a sequencing core facility

Author:

Dahlberg Johan1ORCID,Hermansson Johan1,Sturlaugsson Steinar1,Lysenkova Mariya1,Smeds Patrik2,Ladenvall Claes2ORCID,Guimera Roman Valls3ORCID,Reisinger Florian3,Hofmann Oliver3ORCID,Larsson Pontus1ORCID

Affiliation:

1. Department of Medical Sciences, Molecular Medicine and Science for Life Laboratory, Uppsala University, Box 1432, BMC 751 44, Uppsala, Sweden

2. Department of Immunology, Genetics and Pathology and Science for Life Laboratory, Uppsala University, Rudbecklaboratoriet, 751 84, Uppsala, Sweden

3. University of Melbourne Center for Cancer Research, University of Melbourne, Victorian Comprehensive Cancer Centre, Level 10, UMCCR, 305 Grattan St, Melbourne VIC 3000, Australia

Abstract

AbstractBackgroundIn recent years, nucleotide sequencing has become increasingly instrumental in both research and clinical settings. This has led to an explosive growth in sequencing data produced worldwide. As the amount of data increases, so does the need for automated solutions for data processing and analysis. The concept of workflows has gained favour in the bioinformatics community, but there is little in the scientific literature describing end-to-end automation systems. Arteria is an automation system that aims at providing a solution to the data-related operational challenges that face sequencing core facilities.FindingsArteria is built on existing open source technologies, with a modular design allowing for a community-driven effort to create plug-and-play micro-services. In this article we describe the system, elaborate on the underlying conceptual framework, and present an example implementation. Arteria can be reduced to 3 conceptual levels: orchestration (using an event-based model of automation), process (the steps involved in processing sequencing data, modelled as workflows), and execution (using a series of RESTful micro-services). This creates a system that is both flexible and scalable. Arteria-based systems have been successfully deployed at 3 sequencing core facilities. The Arteria Project code, written largely in Python, is available as open source software, and more information can be found at https://arteria-project.github.io/ .ConclusionsWe describe the Arteria system and the underlying conceptual framework, demonstrating how this model can be used to automate data handling and analysis in the context of a sequencing core facility.

Funder

SNP&SEQ Technology Platform in Uppsala

National Genomics Infrastructure

Science for Life Laboratory

Swedish Research Council

Knut and Alice Wallenberg Foundation

Australian Genomics Health Alliance

National Health and Medical Research Council

Uppsala University Hospital

Publisher

Oxford University Press (OUP)

Subject

Computer Science Applications,Health Informatics

Reference27 articles.

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