Abstract
Phenotypic data analysis is a key component in crop breeding to extract meaningful insights from data in making better breeding decisions. Each year the rainfed rice breeding (RRB) program at IRRI conducts trials in the national agricultural research and extension systems (NARES) network-partner sites across South Asia, Southeast Asia and Africa. Analyzing the data from the network trials and sharing the results with the partners in the best possible format is a daunting task. It is crucial to demystify data analysis to the NARES partners for making better breeding decisions. Here, we provide an overview of how RRB program at IRRI has leveraged R computational power with open-source resource tools like R Markdown, plotly , LaTeX and HTML to develop a unique data analysis workflow and redesigned it to a reproducible document for better interpretation, visualization and seamlessly sharing with partners. The generated report is the state-of-the-art implementation of analysis workflow and outputs either in text, tables or graphics in a unified way as one document. The analysis is highly reproducible and can be regenerated based at any time. The plots are built with enhanced dynamic and interactive visualizations to aid in better understanding and extract information with ease. Tables are highly interactive and manageable rendering liberty to be exported within the document in numerous formats. The source code and demo data set for download and use is available at https://github.com/whussain2/Analysis-pipeline . Conclusively, the analysis workflow and document we presented is not limited to IRRI’s RRB program but is applicable to any organization or institute with full-fledged breeding programs.
Advance of rice breeding in Fukuoka Agricultural Research Center