Open-source analytical pipeline for robust data analysis, visualizations and sharing in crop breeding

cg.authorship.typesCGIAR single centreen
cg.contributor.affiliationInternational Rice Research Instituteen
cg.contributor.crpExcellence in Breeding
cg.contributor.donorBill & Melinda Gates Foundationen
cg.contributor.donorCGIAR Trust Funden
cg.contributor.initiativeAccelerated Breeding
cg.creator.identifierWaseem Hussain: 0000-0002-6861-0193
cg.creator.identifierMahender Anumalla: 0000-0003-4492-4005
cg.creator.identifierMargaret Catolos: 0000-0002-3676-9597
cg.howPublishedFormally Publisheden
cg.identifier.doihttps://doi.org/10.1186/s13007-022-00845-7en
cg.isijournalISI Journalen
cg.issn1746-4811en
cg.issue14en
cg.journalPlant Methodsen
cg.reviewStatusPeer Reviewen
cg.volume18en
dc.contributor.authorHussain, Waseemen
dc.contributor.authorAnumalla, Mahenderen
dc.contributor.authorCatolos, Margareten
dc.contributor.authorKhanna, Apurvaen
dc.contributor.authorSta. Cruz, Ma Teresaen
dc.contributor.authorRamos, Joie M.en
dc.contributor.authorBhosale, Sankalpen
dc.date.accessioned2023-01-16T13:06:26Zen
dc.date.available2023-01-16T13:06:26Zen
dc.identifier.urihttps://hdl.handle.net/10568/127200
dc.titleOpen-source analytical pipeline for robust data analysis, visualizations and sharing in crop breedingen
dcterms.abstractBackground: Developing a systematic phenotypic data analysis pipeline, creating enhanced visualizations, and interpreting the results is crucial to extract meaningful insights from data in making better breeding decisions. Here, we provide an overview of how the Rainfed Rice Breeding (RRB) program at IRRI has leveraged R computational power with open-source resource tools like R Markdown, plotly, LaTeX, and HTML to develop an open-source and end-to-end data analysis workfow and pipeline, and re-designed it to a reproducible document for better interpretations, visualizations and easy sharing with collaborators. Results: We reported the state-of-the-art implementation of the phenotypic data analysis pipeline and workfow embedded into a well-descriptive document. The developed analytical pipeline is open-source, demonstrating how to analyze the phenotypic data in crop breeding programs with step-by-step instructions. The analysis pipeline shows how to pre-process and check the quality of phenotypic data, perform robust data analysis using modern statistical tools and approaches, and convert it into a reproducible document. Explanatory text with R codes, outputs either in text, tables, or graphics, and interpretation of results are integrated into the unified document. The analysis is highly reproducible and can be regenerated at any time. The analytical pipeline source codes and demo data are available at https://github.com/whussain2/Analysis-pipeline. Conclusion: The analysis workfow and document presented are not limited to IRRI’s RRB program but are applicable to any organization or institute with full-fledged breeding programs. We believe this is a great initiative to modernize the data analysis of IRRI’s RRB program. Further, this pipeline can be easily implemented by plant breeders or researchers, helping and guiding them in analyzing the breeding trials data in the best possible way.en
dcterms.accessRightsOpen Access
dcterms.audienceCGIARen
dcterms.audienceDonorsen
dcterms.audienceFarmersen
dcterms.audienceScientistsen
dcterms.available2022-02-05
dcterms.bibliographicCitationHussain, W., Anumalla, M., Catolos, M., Khanna, A., Sta Cruz, M.T., Ramos, J. and Bhosale, S. 2022. Open-source analytical pipeline for robust data analysis, visualizations and sharing in crop breeding. Plant Methods 18, no. 14 (2022): 1-12.en
dcterms.extent12 p.en
dcterms.issued2022-12
dcterms.languageen
dcterms.licenseCC-BY-4.0
dcterms.publisherSpringeren
dcterms.replaceshttps://hdl.handle.net/10568/164112en
dcterms.subjectbreedingen
dcterms.subjectcrop improvementen
dcterms.subjectcrop managementen
dcterms.subjectanalysisen
dcterms.subjectdata analysisen
dcterms.subjectgeneticsen
dcterms.subjectbiotechnologyen
dcterms.subjectplant sciencesen
dcterms.typeJournal Article

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