Arteria: An automation system for a sequencing core facility

Abstract Background In 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 proces...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Gigascience Ročník 8; číslo 12
Hlavní autoři: Dahlberg, Johan, Hermansson, Johan, Sturlaugsson, Steinar, Lysenkova, Mariya, Smeds, Patrik, Ladenvall, Claes, Guimera, Roman Valls, Reisinger, Florian, Hofmann, Oliver, Larsson, Pontus
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States Oxford University Press 01.12.2019
Témata:
Automation
Bioinformatics
Cancer research
Data analysis
Data processing
Electronic Data Processing - methods
High-Throughput Nucleotide Sequencing - methods
Human error
Humans
Infrastructure
Laboratories
Medical research
Modular design
Nucleotides
Open source software
Public domain
Python
Science
Sequences
Software
Technical Note
Workflow
automation
orchestration
workflows
sequencing
ISSN:2047-217X, 2047-217X
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:Abstract Background In 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. Findings Arteria 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/ . Conclusions We 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.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:2047-217X
2047-217X
DOI:10.1093/gigascience/giz135