Nature MethodsBioinformaticsPeer-reviewed journal article
Galaxy External Display Applications: Closing a dataflow interoperability loop
Abstract
Interoperability of datasets, tools, and resources is essential to modern scientific investigation and analysis. The necessity to gather disparate datasets together, perform analysis with a collection of discrete tools, and visualize the results remains a standard approach for exploring and making sense across scientific research domains. Here, we describe the Galaxy External Display Application (GEDA) framework which provides researchers with the ability to facilitate the interoperability of Galaxy user data and external resources, while promoting findability, accessibility, and reuse. The only requirement on the external resource for GEDA accessibility is that it is able to accept a parameter value that contains a URL pointing to user data.
- Citations
- 4
- FWCI
- 0.50
- Field percentile
- top 24%
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Go Get Data (GGD): simple, reproducible access to scientific data
Michael J. Cormier, Jonathan R. Belyeu, … Aaron R. Quinlan·Nature CommunicationsPeer-reviewed·Apr 12, 2021
- Laniakea: an open solution to provide Galaxy \"on-demand\" instances over heterogeneous cloud infrastructures.
Marco Antonio Tangaro, Giacinto Donvito, … Federico Zambelli·GigaSciencePeer-reviewed·Apr 1, 2020
- Merging OpenLifeData with SADI services using Galaxy and Docker
Mikel Egañna Aranguren·bioRxiv·Jan 10, 2015
- Increased Interactivity and Improvements to the GigaScience Database, GigaDB.
S. Z. Xiao, C. Armit, … C. Hunter·bioRxiv·Jan 22, 2019
- Galaxy Training: A Powerful Framework for Teaching!
Saskia Hiltemann, Helena Rasche, … the Galaxy Training Network·PLoS Computational BiologyPeer-reviewed·Jan 9, 2023
- Planemo: a command-line toolkit for developing, deploying, and executing scientific data analyses
Simon A. Bray, John M. Chilton, … Anton Nekrutenko·Genome ResearchPeer-reviewed·Feb 1, 2023