Mr.Bean: a comprehensive statistical and visualization application for modeling agricultural field trials data - Aparicio, Johan; Gezan, Salvador A.; Ariza-Suarez, Daniel; Raatz, Bodo; Diaz, Santiago; Heilman-Morales, Ana; Lobaton, Juan (Frontiers in Plant Science, 2024)
Crop improvement efforts have exploited new methods for modeling spatial trends using the arrangement of the experimental units in the field. These methods have shown improvement in predicting the genetic potential of evaluated genotypes. However, the use of these tools may be limited by the exposure and accessibility to these products. In addition, these new methodologies often require plant scientists to be familiar with the programming environment used to implement them; constraints that limit data analysis efficiency for decision-making. These challenges have led to the development of Mr.Bean, an accessible and user-friendly tool with a comprehensive graphical visualization interface. The application integrates descriptive analysis, measures of dispersion and centralization, linear mixed model fitting, multi-environment trial analysis, factor analytic models, and genomic analysis. All these capabilities are designed to help plant breeders and scientist working with agricultural field trials make informed decisions more quickly. Mr.Bean is available for download at https://github.com/AparicioJohan/MrBeanApp.Moved (insertion) [1] Deleted: . 121 Moved up [1]: . The application integrates genomic and 122 phenotypic data using the R-package sommer (Covarrubias-Pazaran, 123 2016). It estimates marker effects, variance components with 124 genomic predictions, marker-base heritability, and genomic breeding 125 values (GEBVs). 126 Deleted: Mr.Bean can be installed through the R software console 127 from GitHub (https://github.com/AparicioJohan/MrBeanApp.).It can 128 be also installed and run locally by downloading it directly from 129 dockerhub (https://hub.docker.com/r/johanstevenapa/mrbeanapp).The application can be run in a beta version on the internet using any 131 web browser for users without sufficient processing power, using the 132 link: https://beanteam.shinyapps.io/MrBean_BETA/ (Figure 1). It 133 can be also installed and run locally by downloading it directly from 134 dockerhub (https://hub.docker.com/r/johanstevenapa/mrbeanapp). 135 The Mr.Bean application follows a logical process through data 136 loading, statistical analysis, model development and results 137 generation (Figure 2).138 Moved (insertion) [2] Moved up [2]: It can be also installed and run locally by 139 downloading it directly from dockerhub 140 (https://hub.docker.com/r/johanstevenapa/mrbeanapp).