Owning to advancements in sensor‐based, non‐destructive phenotyping platforms, researchers are increasingly collecting data with higher temporal resolution. These phenotypes collected over several time points are cataloged as longitudinal traits and used for genome‐wide association studies (GWAS). Longitudinal GWAS typically yield a large number of output files, posing a significant challenge to data interpretation and visualization. Efficient, dynamic, and integrative data visualization tools are essential for the interpretation of longitudinal GWAS results for biologists; however, these tools are not widely available to the community. We have developed a flexible and user‐friendly Shiny‐based online application, ShinyAIM, to dynamically view and interpret temporal GWAS results. The main features of the application include (a) interactive Manhattan plots for single time points, (b) a grid plot to view Manhattan plots for all time points simultaneously, (c) dynamic scatter plots for p‐value‐filtered selected markers to investigate co‐localized genomic regions across time points, (d) and interactive phenotypic data visualization to capture variation and trends in phenotypes. The application is written entirely in the R language and can be used with limited programming experience. ShinyAIM is deployed online as a Shiny web server application at https://chikudaisei.shinyapps.io/shinyaim/,enabling easy access for users without installation. The application can also be launched on a local machine in RStudio.
This page provides information abot the application and links to the codes, application and materials available in repo. The application is available online at Shiny Server. All the codes, sample files are available on GitHub repository whussain2/ShinyAIM and Zenodo. The details how to use this application can be found on the first main tab of the application once it is opened. Also, the manuscript along with all the details is published in Plant Direct journal at Shiny Manuscript.
Codes in .rmd and HTML is given below:
Funding for this project was provided by the National Science Foundation through the Plant Genome Reasearch Program grant (Grant No. 1736192) awarded to HW and GM.