Hussain, WaseemCampbell, Malachy T.Walia, HarkamalMorota, Gota2021-10-202021-10-202018-10-012475-4455PLD391 (PII)http://hdl.handle.net/10919/105420Owning 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.4 page(s)application/pdfenCreative Commons Attribution 4.0 InternationalLife Sciences & BiomedicinePlant Sciencesgenome-wide association studiesinteractive visualizationlongitudinal traitsShinyAIMgenome‐wide association studiesArticle - Refereed2021-10-20https://doi.org/10.1002/pld3.91210Morota, Gota [0000-0002-3567-6911]312456912475-4455