{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,28]],"date-time":"2025-04-28T08:40:03Z","timestamp":1745829603179,"version":"3.40.4"},"reference-count":32,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,4,16]],"date-time":"2025-04-16T00:00:00Z","timestamp":1744761600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,4,16]],"date-time":"2025-04-16T00:00:00Z","timestamp":1744761600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100005774","name":"Universitat de Barcelona","doi-asserted-by":"publisher","award":["2023PMD-UB\/021"],"award-info":[{"award-number":["2023PMD-UB\/021"]}],"id":[{"id":"10.13039\/501100005774","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:sec>\n            <jats:title>Background<\/jats:title>\n            <jats:p>Bioinformatics data analysis faces significant challenges. As data analysis often takes the form of pipelines or workflows, workflow managers (WfMs) have become essential. Data flow programming constitutes the preferred approach in WfMs, enabling parallel processes activated reactively based on input availability. While this paradigm typically follows a linear, acyclic progression, cyclic workflows are sometimes necessary in bioinformatics analyses. These cyclic workflows also present an opportunity to explore workflow interactivity, a feature not widely implemented in existing WfMs.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>We propose DeBasher, a tool that adopts the flow-based programming (FBP) paradigm, in which the workflow components are in control of their life cycle and can store state information, allowing the execution of complex workflows that include cycles. DeBasher also incorporates a powerful model of interactivity, where the user can alter the behavior of a running workflow. Additionally, DeBasher allows the user to define triggers so as to initiate the execution of a complete workflow or a part of it. The ability to execute processes with state and in control of their life cycle also has applications in dynamic scheduling tasks. Furthermore, DeBasher presents a series of extra features, including the combination of multiple workflows at runtime through a feature we have called runtime piping, switching to static scheduling to increase scalability, or implementing processes in multiple languages. DeBasher has been successfully used to process 131.7 TB of genomic data by means of a variant calling pipeline.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusions<\/jats:title>\n            <jats:p>DeBasher is an FBP Bash extension that can be useful in a wide range of situations and in particular when implementing complex workflows, workflows with interactivity or triggers, or when a high scalability is required.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/s12859-025-06108-1","type":"journal-article","created":{"date-parts":[[2025,4,16]],"date-time":"2025-04-16T13:14:52Z","timestamp":1744809292000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["DeBasher: a flow-based programming bash extension for the implementation of complex and interactive workflows with stateful processes"],"prefix":"10.1186","volume":"26","author":[{"given":"Daniel","family":"Ortiz-Mart\u00ednez","sequence":"first","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,4,16]]},"reference":[{"issue":"10","key":"6108_CR1","doi-asserted-by":"publisher","first-page":"1161","DOI":"10.1038\/s41592-021-01254-9","volume":"18","author":"L Wratten","year":"2021","unstructured":"Wratten L, Wilm A, G\u00f6ke J. Reproducible, scalable, and shareable analysis pipelines with bioinformatics workflow managers. Nat Methods. 2021;18(10):1161\u20138. https:\/\/doi.org\/10.1038\/s41592-021-01254-9.","journal-title":"Nat Methods"},{"issue":"4","key":"6108_CR2","doi-asserted-by":"publisher","first-page":"316","DOI":"10.1038\/nbt.3820","volume":"35","author":"P Di Tommaso","year":"2017","unstructured":"Di Tommaso P, Chatzou M, Floden EW, Barja PP, Palumbo E, Notredame C. Nextflow enables reproducible computational workflows. Nat Biotechnol. 2017;35(4):316\u20139. https:\/\/doi.org\/10.1038\/nbt.3820.","journal-title":"Nat Biotechnol."},{"issue":"19","key":"6108_CR3","doi-asserted-by":"publisher","first-page":"2520","DOI":"10.1093\/bioinformatics\/bts480","volume":"28","author":"J K\u00f6ster","year":"2012","unstructured":"K\u00f6ster J, Rahmann S. Snakemake\u2014a scalable bioinformatics workflow engine. Bioinformatics. 2012;28(19):2520\u20132. https:\/\/doi.org\/10.1093\/bioinformatics\/bts480.","journal-title":"Bioinformatics"},{"issue":"W1","key":"6108_CR4","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1093\/nar\/gkae410","volume":"52","author":"TG Community","year":"2024","unstructured":"Community TG. The Galaxy platform for accessible, reproducible, and collaborative data analyses: 2024 update. Nucl Acids Res. 2024;52(W1):83\u201394. https:\/\/doi.org\/10.1093\/nar\/gkae410.","journal-title":"Nucl. Acids Res."},{"key":"6108_CR5","doi-asserted-by":"publisher","unstructured":"Voss K, Auwera GVD, Gentry J. Full-stack genomics pipelining with GATK4 + WDL + Cromwell . F1000Research 2017. https:\/\/doi.org\/10.7490\/f1000research.1114634.1 . https:\/\/f1000research.com\/slides\/6-1381","DOI":"10.7490\/f1000research.1114634.1"},{"issue":"4","key":"6108_CR6","doi-asserted-by":"publisher","first-page":"314","DOI":"10.1038\/nbt.3772","volume":"35","author":"J Vivian","year":"2017","unstructured":"...Vivian J, Rao AA, Nothaft FA, Ketchum C, Armstrong J, Novak A, Pfeil J, Narkizian J, Deran AD, Musselman-Brown A, Schmidt H, Amstutz P, Craft B, Goldman M, Rosenbloom K, Cline M, O\u2019Connor B, Hanna M, Birger C, Kent WJ, Patterson DA, Joseph AD, Zhu J, Zaranek S, Getz G, Haussler D, Paten B. Toil enables reproducible, open source, big biomedical data analyses. Nat Biotechnol. 2017;35(4):314\u20136. https:\/\/doi.org\/10.1038\/nbt.3772.","journal-title":"Nat Biotechnol."},{"issue":"1","key":"6108_CR7","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1022883727209","volume":"14","author":"WMP Aalst","year":"2003","unstructured":"Aalst WMP, Hofstede AHM, Kiepuszewski B, Barros AP. Workflow patterns. Distrib Parallel Databases. 2003;14(1):5\u201351.","journal-title":"Distrib Parallel Databases"},{"key":"6108_CR8","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1186\/s12859-018-2028-2","volume":"19","author":"TCA Hitch","year":"2018","unstructured":"Hitch TCA, Creevey CJ. Spherical: an iterative workflow for assembling metagenomic datasets. BMC Bioinform. 2018;19:20. https:\/\/doi.org\/10.1186\/s12859-018-2028-2.","journal-title":"BMC Bioinform."},{"issue":"1","key":"6108_CR9","doi-asserted-by":"publisher","first-page":"708","DOI":"10.1186\/s12864-016-3030-6","volume":"17","author":"SS Shepard","year":"2016","unstructured":"Shepard SS, Meno S, Bahl J, Wilson MM, Barnes J, Neuhaus E. Viral deep sequencing needs an adaptive approach: Irma, the iterative refinement meta-assembler. BMC Genomics. 2016;17(1):708. https:\/\/doi.org\/10.1186\/s12864-016-3030-6.","journal-title":"BMC Genomics"},{"issue":"27","key":"6108_CR10","doi-asserted-by":"publisher","first-page":"737","DOI":"10.21105\/joss.00737","volume":"3","author":"HJ Oliver","year":"2018","unstructured":"Oliver HJ, Shin M, Sanders O. Cylc: A workflow engine for cycling systems. J Open Sour Softw. 2018;3(27):737. https:\/\/doi.org\/10.21105\/joss.00737.","journal-title":"J Open Sour Softw."},{"key":"6108_CR11","unstructured":"Morrison JP. Flow-based programming: a new approach to application development. 2nd ed. J.P. Morrison Enterprises; 2011"},{"issue":"5","key":"6108_CR12","doi-asserted-by":"publisher","first-page":"044","DOI":"10.1093\/gigascience\/giz044","volume":"8","author":"S Lampa","year":"2019","unstructured":"Lampa S, Dahl\u00f6 M, Alvarsson J, Spjuth O. SciPipe: A workflow library for agile development of complex and dynamic bioinformatics pipelines. GigaScience. 2019;8(5):044. https:\/\/doi.org\/10.1093\/gigascience\/giz044 (https:\/\/academic.oup.com\/gigascience\/article-pdf\/8\/5\/giz044\/28538382\/giz044.pdf).","journal-title":"GigaScience"},{"issue":"1","key":"6108_CR13","doi-asserted-by":"publisher","first-page":"21680","DOI":"10.1038\/s41598-021-99288-8","volume":"11","author":"AE Ahmed","year":"2021","unstructured":"Ahmed AE, Allen JM, Bhat T, Burra P, Fliege CE, Hart SN, Heldenbrand JR, Hudson ME, Istanto DD, Kalmbach MT, Kapraun GD, Kendig KI, Kendzior MC, Klee EW, Mattson N, Ross CA, Sharif SM, Venkatakrishnan R, Fadlelmola FM, Mainzer LS. Design considerations for workflow management systems use in production genomics research and the clinic. Sci Rep. 2021;11(1):21680. https:\/\/doi.org\/10.1038\/s41598-021-99288-8.","journal-title":"Sci Rep."},{"issue":"8","key":"6108_CR14","doi-asserted-by":"publisher","first-page":"1220","DOI":"10.1093\/bioinformatics\/btv710","volume":"32","author":"X Chen","year":"2016","unstructured":"Chen X, Schulz-Trieglaff O, Shaw R, Barnes B, Schlesinger F, K\u00e4llberg M, Cox AJ, Kruglyak S, Saunders CT. Manta: rapid detection of structural variants and indels for germline and cancer sequencing applications. Bioinformatics. 2016;32(8):1220\u20132. https:\/\/doi.org\/10.1093\/bioinformatics\/btv710.","journal-title":"Bioinformatics"},{"key":"6108_CR15","doi-asserted-by":"publisher","first-page":"591","DOI":"10.1038\/s41592-018-0051-x","volume":"15","author":"S Kim","year":"2018","unstructured":"Kim S, Scheffler K, Halpern AL, et al. Strelka2: fast and accurate calling of germline and somatic variants. Nat Methods. 2018;15:591\u20134. https:\/\/doi.org\/10.1038\/s41592-018-0051-x.","journal-title":"Nat Methods"},{"issue":"16","key":"6108_CR16","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1093\/nar\/gkw520","volume":"44","author":"R Shen","year":"2016","unstructured":"Shen R, Seshan VE. FACETS: allele-specific copy number and clonal heterogeneity analysis tool for high-throughput DNA sequencing. Nucl Acids Res. 2016;44(16):131. https:\/\/doi.org\/10.1093\/nar\/gkw520.","journal-title":"Nucl Acids Res."},{"issue":"4","key":"6108_CR17","doi-asserted-by":"publisher","first-page":"1004873","DOI":"10.1371\/journal.pcbi.1004873","volume":"12","author":"E Talevich","year":"2016","unstructured":"Talevich E, Shain AH, Botton T, Bastian BC. CNVkit: Genome-wide copy number detection and visualization from targeted DNA sequencing. PLOS Comput Biol. 2016;12(4):1004873. https:\/\/doi.org\/10.1371\/journal.pcbi.1004873.","journal-title":"PLOS Comput Biol."},{"key":"6108_CR18","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1186\/gb-2014-15-6-r84","volume":"15","author":"RM Layer","year":"2014","unstructured":"Layer RM, Chiang C, Quinlan AR, Hall IM. LUMPY: a probabilistic framework for structural variant discovery. Genome Biol. 2014;15:84. https:\/\/doi.org\/10.1186\/gb-2014-15-6-r84.","journal-title":"Genome Biol."},{"issue":"10","key":"6108_CR19","doi-asserted-by":"publisher","first-page":"966","DOI":"10.1038\/nmeth.3505","volume":"12","author":"C Chiang","year":"2015","unstructured":"Chiang C, Layer RM, Faust GG, Lindberg MR, Rose DB, Garrison EP, Marth GT, Quinlan AR, Hall IM. SpeedSeq: ultra-fast personal genome analysis and interpretation. Nat Methods. 2015;12(10):966\u20138. https:\/\/doi.org\/10.1038\/nmeth.3505.","journal-title":"Nat Methods"},{"issue":"18","key":"6108_CR20","doi-asserted-by":"publisher","first-page":"333","DOI":"10.1093\/bioinformatics\/bts378","volume":"28","author":"T Rausch","year":"2012","unstructured":"Rausch T, Zichner T, Schlattl A, St\u00fctz AM, Benes V, Korbel JO. DELLY: structural variant discovery by integrated paired-end and split-read analysis. Bioinformatics. 2012;28(18):333\u20139. https:\/\/doi.org\/10.1093\/bioinformatics\/bts378.","journal-title":"Bioinformatics"},{"issue":"1","key":"6108_CR21","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1016\/j.gpb.2020.02.001","volume":"18","author":"P Jia","year":"2020","unstructured":"Jia P, Yang X, Guo L, Liu B, Lin J, Liang H, Sun J, Zhang C, Ye K. Msisensor-pro: Fast, accurate, and matched-normal-sample-free detection of microsatellite instability. Genomics, Proteomics Bioinf. 2020;18(1):65\u201371. https:\/\/doi.org\/10.1016\/j.gpb.2020.02.001.","journal-title":"Genomics, Proteomics Bioinf."},{"issue":"1","key":"6108_CR22","doi-asserted-by":"publisher","first-page":"3724","DOI":"10.1038\/s41467-022-31483-1","volume":"13","author":"M Vali-Pour","year":"2022","unstructured":"Vali-Pour M, Park S, Espinosa-Carrasco J, Ortiz-Mart\u00ednez D, Lehner B, Supek F. The impact of rare germline variants on human somatic mutation processes. Nat Commun. 2022;13(1):3724. https:\/\/doi.org\/10.1038\/s41467-022-31483-1.","journal-title":"Nat Commun."},{"key":"6108_CR23","doi-asserted-by":"publisher","first-page":"228","DOI":"10.1016\/j.future.2017.02.026","volume":"75","author":"R Ferreira da Silva","year":"2017","unstructured":"Ferreira da Silva R, Filgueira R, Pietri I, Jiang M, Sakellariou R, Deelman E. A characterization of workflow management systems for extreme-scale applications. Future Gener Comput Syst. 2017;75:228\u201338. https:\/\/doi.org\/10.1016\/j.future.2017.02.026.","journal-title":"Future Gener Comput Syst."},{"issue":"C","key":"6108_CR24","doi-asserted-by":"publisher","first-page":"282","DOI":"10.1016\/j.future.2021.10.007","volume":"128","author":"I Colonnelli","year":"2022","unstructured":"Colonnelli I, Aldinucci M, Cantalupo B, Padovani L, Rabellino S, Spampinato C, Morelli R, Di Carlo R, Magini N, Cavazzoni C. Distributed workflows with jupyter. Future Gener Comput Syst. 2022;128(C):282\u201398. https:\/\/doi.org\/10.1016\/j.future.2021.10.007.","journal-title":"Future Gener Comput Syst."},{"key":"6108_CR25","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1007\/978-3-031-34167-0_39","volume-title":"Mach Learn Astrophys.","author":"I Colonnelli","year":"2023","unstructured":"Colonnelli I, Casella B, Mittone G, Arfat Y, Cantalupo B, Esposito R, Martinelli AR, Medi\u0107 D, Aldinucci M. Federated learning meets HPC and cloud. In: Bufano F, Riggi S, Sciacca E, Schilliro F, editors. Mach Learn Astrophys. Cham: Springer; 2023. p. 193\u20139."},{"key":"6108_CR26","doi-asserted-by":"publisher","unstructured":"Manubens-Gil D, Vegas-Regidor J, Prodhomme C, Mula-Valls O, Doblas-Reyes FJ. Seamless management of ensemble climate prediction experiments on hpc platforms. In: 2016 International conference on high performance computing and simulation (HPCS), 2016. pp. 895\u2013900. https:\/\/doi.org\/10.1109\/HPCSim.2016.7568429","DOI":"10.1109\/HPCSim.2016.7568429"},{"key":"6108_CR27","doi-asserted-by":"publisher","unstructured":"Filgueira R, Krause A, Atkinson M, Klampanos I, Spinuso A, Sanchez-Exposito S. dispel4py: An agile framework for data-intensive escience. In: 2015 IEEE 11th International conference on e-Science, 2015. pp. 454\u2013464. https:\/\/doi.org\/10.1109\/eScience.2015.40","DOI":"10.1109\/eScience.2015.40"},{"key":"6108_CR28","doi-asserted-by":"crossref","unstructured":"Liang L, Zhang H, Yang G, Heinis T, Filgueira R. Optimization towards efficiency and stateful of dispel4py 2023. https:\/\/arxiv.org\/abs\/2309.00595","DOI":"10.1145\/3624062.3624281"},{"key":"6108_CR29","unstructured":"Moritz P, Nishihara R, Wang S, Tumanov A, Liaw R, Liang E, Elibol M, Yang Z, Paul W, Jordan MI, Stoica I. Ray: a distributed framework for emerging ai applications. OSDI\u201918, USENIX Association: USA; 2018. pp. 561\u2013577."},{"key":"6108_CR30","doi-asserted-by":"publisher","unstructured":"Beberg AL, Ensign DL, Jayachandran G, Khaliq S, Pande VS. Folding@home: Lessons from eight years of volunteer distributed computing. In: 2009 IEEE international symposium on parallel and distributed processing, 2009. pp. 1\u20138. https:\/\/doi.org\/10.1109\/IPDPS.2009.5160922","DOI":"10.1109\/IPDPS.2009.5160922"},{"issue":"11","key":"6108_CR31","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1145\/581571.581573","volume":"45","author":"DP Anderson","year":"2002","unstructured":"Anderson DP, Cobb J, Korpela E, Lebofsky M, Werthimer D. Seti@home: an experiment in public-resource computing. Commun ACM. 2002;45(11):56\u201361. https:\/\/doi.org\/10.1145\/581571.581573.","journal-title":"Commun ACM"},{"key":"6108_CR32","doi-asserted-by":"publisher","unstructured":"Rohl CA, Strauss CEM, Misura KMS, Baker D. Protein structure prediction using rosetta. In: numerical computer methods, Part D. methods in enzymology, Academic Press, Cambridge; 2004, 383. 66\u201393 https:\/\/doi.org\/10.1016\/S0076-6879(04)83004-0","DOI":"10.1016\/S0076-6879(04)83004-0"}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-025-06108-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12859-025-06108-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-025-06108-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,28]],"date-time":"2025-04-28T08:10:55Z","timestamp":1745827855000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/s12859-025-06108-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,16]]},"references-count":32,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["6108"],"URL":"https:\/\/doi.org\/10.1186\/s12859-025-06108-1","relation":{},"ISSN":["1471-2105"],"issn-type":[{"type":"electronic","value":"1471-2105"}],"subject":[],"published":{"date-parts":[[2025,4,16]]},"assertion":[{"value":"8 October 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 March 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 April 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 April 2025","order":4,"name":"change_date","label":"Change Date","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Update","order":5,"name":"change_type","label":"Change Type","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The formatting of the supplementary information has been corrected in the original publication. The article has been updated to rectify the error.","order":6,"name":"change_details","label":"Change Details","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not Applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not Applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"106"}}