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

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Title Open-source analytical pipeline for robust data analysis, visualizations and sharing in crop breeding
 
Creator Hussain, Waseem
Anumalla, Mahender
Catolos, Margaret
Khanna, Apurva
Sta. Cruz, Ma Teresa
Ramos, Joie
Bhosale, Sankalp
 
Subject breeding
crop improvement
crop management
analysis
data analysis
genetics
biotechnology
 
Description Background: Developing a systematic phenotypic data analysis pipeline, creating enhanced visualizations, and inter-
preting 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 unifed 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-fedged 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 research-
ers, helping and guiding them in analyzing the breeding trials data in the best possible way.
 
Date 2022-12
2023-01-16T13:06:26Z
2023-01-16T13:06:26Z
 
Type Journal Article
 
Identifier Hussain, 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.
1746-4811
https://hdl.handle.net/10568/127200
https://doi.org/10.1186/s13007-022-00845-7
 
Language en
 
Rights CC-BY-4.0
Open Access
 
Format 12 p.
application/pdf
 
Publisher Springer Science and Business Media LLC
 
Source Plant Methods