Sapporo: A workflow execution service that encourages the reuse of workflows in various languages in bioinformatics.

open science workflow workflow execution service workflow language

Journal

F1000Research
ISSN: 2046-1402
Titre abrégé: F1000Res
Pays: England
ID NLM: 101594320

Informations de publication

Date de publication:
2022
Historique:
accepted: 14 06 2024
medline: 29 7 2024
pubmed: 29 7 2024
entrez: 29 7 2024
Statut: epublish

Résumé

The increased demand for efficient computation in data analysis encourages researchers in biomedical science to use workflow systems. Workflow systems, or so-called workflow languages, are used for the description and execution of a set of data analysis steps. Workflow systems increase the productivity of researchers, specifically in fields that use high-throughput DNA sequencing applications, where scalable computation is required. As systems have improved the portability of data analysis workflows, research communities are able to share workflows to reduce the cost of building ordinary analysis procedures. However, having multiple workflow systems in a research field has resulted in the distribution of efforts across different workflow system communities. As each workflow system has its unique characteristics, it is not feasible to learn every single system in order to use publicly shared workflows. Thus, we developed Sapporo, an application to provide a unified layer of workflow execution upon the differences of various workflow systems. Sapporo has two components: an application programming interface (API) that receives the request of a workflow run and a browser-based client for the API. The API follows the Workflow Execution Service API standard proposed by the Global Alliance for Genomics and Health. The current implementation supports the execution of workflows in four languages: Common Workflow Language, Workflow Description Language, Snakemake, and Nextflow. With its extensible and scalable design, Sapporo can support the research community in utilizing valuable resources for data analysis.

Identifiants

pubmed: 39070189
doi: 10.12688/f1000research.122924.2
pmc: PMC11282396
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

889

Informations de copyright

Copyright: © 2024 Suetake H et al.

Déclaration de conflit d'intérêts

No competing interests were disclosed.

Auteurs

Hirotaka Suetake (H)

Department of Creative Informatics, Graduate School of Information Science and Technology, The University of Tokyo, Bunkyo, Tokyo, Japan.

Tomoya Tanjo (T)

Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka, Japan.

Manabu Ishii (M)

Genome Analytics Japan Inc, Shinjuku, Tokyo, Japan.

Bruno P Kinoshita (B)

Barcelona Supercomputing Center (BSC), Barcelona, Spain.
Curii Corporation, Sommerville, MA, USA.

Takeshi Fujino (T)

Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Bunkyo, Tokyo, Japan.

Tsuyoshi Hachiya (T)

Genome Analytics Japan Inc, Shinjuku, Tokyo, Japan.

Yuichi Kodama (Y)

Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka, Japan.

Takatomo Fujisawa (T)

Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka, Japan.

Osamu Ogasawara (O)

Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka, Japan.

Atsushi Shimizu (A)

Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka, Japan.

Masanori Arita (M)

Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka, Japan.

Tsukasa Fukusato (T)

Department of Computer Science, Graduate School of Information Science and Technology, The University of Tokyo, Bunkyo, Tokyo, Japan.

Takeo Igarashi (T)

Department of Creative Informatics, Graduate School of Information Science and Technology, The University of Tokyo, Bunkyo, Tokyo, Japan.

Tazro Ohta (T)

Institute for Advanced Academic Research, Chiba University, Chiba, Japan.
Database Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Mishima, Shizuoka, Japan.
Department of Artificial Intelligence Medicine, Graduate School of Medicine, Chiba University, Chiba, Chiba, Japan.

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Classifications MeSH