{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T11:43:32Z","timestamp":1753875812829,"version":"3.41.2"},"reference-count":11,"publisher":"Oxford University Press (OUP)","issue":"8","license":[{"start":{"date-parts":[[2024,8,6]],"date-time":"2024-08-06T00:00:00Z","timestamp":1722902400000},"content-version":"vor","delay-in-days":5,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"NIH","doi-asserted-by":"publisher","award":["U41 HG006620","U24 HG010263"],"award-info":[{"award-number":["U41 HG006620","U24 HG010263"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"NSF","doi-asserted-by":"publisher","award":["2005506"],"award-info":[{"award-number":["2005506"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,8,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>The Galaxy application is a popular open-source framework for data intensive sciences, counting thousands of monthly users across more than 100 public servers. To support a growing number of users and a greater variety of use cases, the complexity of a production-grade Galaxy installation has also grown, requiring more administration effort. There is a need for a rapid and reproducible Galaxy deployment method that can be maintained at high-availability with minimal maintenance.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We describe the Galaxy Helm chart that codifies all elements of a production-grade Galaxy installation into a single package. Deployable on Kubernetes clusters, the chart encapsulates supporting software services and implements the best-practices model for running Galaxy. It is also the most rapid method available for deploying a scalable, production-grade Galaxy instance on one\u2019s own infrastructure. The chart is highly configurable, allowing systems administrators to swap dependent services if desired. Notable uses of the chart include on-demand, fully-automated deployments on AnVIL, providing training infrastructure for the Bioconductor project, and as the AWS-recommended solution for running Galaxy on the Amazon cloud.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>The source code for Galaxy Helm is available at https:\/\/github.com\/galaxyproject\/galaxy-helm, the corresponding Helm package at https:\/\/github.com\/CloudVE\/helm-charts, and the required Galaxy container image https:\/\/github.com\/galaxyproject\/galaxy-docker-k8s.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btae486","type":"journal-article","created":{"date-parts":[[2024,8,7]],"date-time":"2024-08-07T03:49:02Z","timestamp":1723002542000},"source":"Crossref","is-referenced-by-count":0,"title":["Galaxy Helm chart: a standardized method for deploying production Galaxy servers"],"prefix":"10.1093","volume":"40","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3019-2934","authenticated-orcid":false,"given":"Nuwan","family":"Goonasekera","sequence":"first","affiliation":[{"name":"Australian BioCommons, University of Melbourne , Melbourne, VIC 3052, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alexandru","family":"Mahmoud","sequence":"additional","affiliation":[{"name":"Channing Division of Network Medicine, Harvard Medical School , Boston, MA 02115, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Keith","family":"Suderman","sequence":"additional","affiliation":[{"name":"Department of Biology, Johns Hopkins University , Baltimore, MD 21210, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Enis","family":"Afgan","sequence":"additional","affiliation":[{"name":"Department of Biology, Johns Hopkins University , Baltimore, MD 21210, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2024,8,6]]},"reference":[{"key":"2024082201231468900_btae486-B1","doi-asserted-by":"crossref","first-page":"802","DOI":"10.1016\/j.future.2018.04.037","article-title":"CloudLaunch: discover and deploy cloud applications","volume":"94","author":"Afgan","year":"2019","journal-title":"Future Gener Comput Syst"},{"key":"2024082201231468900_btae486-B2","doi-asserted-by":"crossref","first-page":"972","DOI":"10.1038\/nbt.2028","article-title":"Harnessing cloud computing with galaxy cloud","volume":"29","author":"Afgan","year":"2011","journal-title":"Nat Biotechnol"},{"year":"2008","author":"Aguado Sanchez","key":"2024082201231468900_btae486-B3"},{"key":"2024082201231468900_btae486-B4","doi-asserted-by":"crossref","first-page":"W83","DOI":"10.1093\/nar\/gkae410","article-title":"The galaxy platform for accessible, reproducible, and collaborative data analyses: 2024 update","volume":"52","author":"Galaxy Community","year":"2024","journal-title":"Nucleic Acids Res"},{"year":"2023","author":"Goonasekera","key":"2024082201231468900_btae486-B5"},{"key":"2024082201231468900_btae486-B6","doi-asserted-by":"crossref","first-page":"e1005425","DOI":"10.1371\/journal.pcbi.1005425","article-title":"Jupyter and galaxy: easing entry barriers into complex data analyses for biomedical researchers","volume":"13","author":"Gr\u00fcning","year":"2017","journal-title":"PLoS Comput Biol"},{"key":"2024082201231468900_btae486-B7","doi-asserted-by":"crossref","first-page":"e1010752","DOI":"10.1371\/journal.pcbi.1010752","article-title":"Galaxy training: a powerful framework for teaching!","volume":"19","author":"Hiltemann","year":"2023","journal-title":"PLoS Comput. Biol"},{"key":"2024082201231468900_btae486-B8","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1038\/nmeth.3252","article-title":"Orchestrating high-throughput genomic analysis with bioconductor","volume":"12","author":"Huber","year":"2015","journal-title":"Nat Methods"},{"year":"2018","author":"Moreno","key":"2024082201231468900_btae486-B9"},{"key":"2024082201231468900_btae486-B10","article-title":"Inverting the model of genomics data sharing with the NHGRI genomic data science analysis, visualization, and informatics lab-space","volume":"2","author":"Schatz","year":"2022","journal-title":"Cell Genom"},{"key":"2024082201231468900_btae486-B11","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1109\/MCC.2014.54","article-title":"FedRAMP: history and future direction","volume":"1","author":"Taylor","year":"2014","journal-title":"IEEE Cloud Comput"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btae486\/58749467\/btae486.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/40\/8\/btae486\/58883942\/btae486.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/40\/8\/btae486\/58883942\/btae486.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,22]],"date-time":"2024-08-22T04:24:50Z","timestamp":1724300690000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/doi\/10.1093\/bioinformatics\/btae486\/7728456"}},"subtitle":[],"editor":[{"given":"Pier Luigi","family":"Martelli","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2024,8]]},"references-count":11,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2024,8,2]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btae486","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"type":"print","value":"1367-4803"},{"type":"electronic","value":"1367-4811"}],"subject":[],"published-other":{"date-parts":[[2024,8]]},"published":{"date-parts":[[2024,8]]},"article-number":"btae486"}}