ShinyAIM: Shiny Application for Interactive Manhattan Plots

General Information

ShinyAIM allows users to dynamically view and interpret longitudinal GWAS results.

Features of the Application: Interactive Data Visualization

  • Interactive Manhattan Plots.
  • Manhattan Grid Plot.
  • Comparison of Associated Markers.
  • Phenotypic Data Visualization: Interactive Histograms, Density Plots, and Box Plots.


  1. The application has four main tab panels including (a) Interactive Manhattan Plots, (b) Manhattan Grid Plot, (c) Comparison of Associated Markers, and (d) Phenotypic Data Visualization.
  2. The application accepts the text/csv,text/comma-separated-values,text/plain file format. Users can download the sample files by clicking on download button 'Download Sample File' embedded on top of side bar panel in respective main tab panels. All the material including sample files and source code can also be downloaded from the link given below:
  4. The screenshot of the sample files for Interactive Manhattan Plots, Manhattan Grid Plot and Phenotypic Data Visualization is also shown below:

    • Files must have header rows.
    • Column names in the files should match with sample file names. The order of the columns is not important.
    • timepoint: represents the time or day at which data was collected, this column can represent different time points or phenotypes and it can be different traits in users file, but make sure column is named as timepoint.
    • chrom: represents the number of chromosomes.
    • pos: represents the position of markers or SNPs.
    • P: represents the p value for markers or SNPs.
    • NSFTV_ID: is ID for genotypes and can be anything in users file.
    • Value: represents the phenotypic data for each time point and must be numeric.
  5. For each main tab panel separate input files needs to be uploaded. Sample files can be used as examples to get familiar with the application.
  6. In Manhattan Plot panel, once the input file in right format is uploaded, users need to choose the separator value in the file. Once users choose the separator value, the time points will be automatically updated in Choose Time point box. Users can select any time point and Interactive Manhattan plot will be automatically generated in left main panel, and users can interact with it to get more information. Users can choose the significant threshold level by moving slider input bar.
  7. In Interactive Manhattan Plot tab, user's can also see the list of top SNPs in table format by checking Display in Table Significant SNPs box. Once checked, List of SNPs will be displayed with highest p values on top. Users can use slider input to control the number of SNPs displayed in table.
  8. For Manhattan Grid Plot tab, once input file is uploaded and separator value choose, the combined Manhattan plot will be automatically generated in left main panel. Users can choose the significant threshold level and also number of columns in the combined/grid plot. Note: CSV file for Manhattan plot and combined Manhattan plot is same, however, they need to be uploaded separately.
  9. For Comparison of Associated Markers tab, It uses the same data file as uploaded for Manhattan Grid Plot so no need to upload the data for this tab Panel. Once tab Panel is clicked, plot will be automatically displayed in right panel. To modify or change the plot based on top p value, directly enter the value by typing in the box.
  10. For Phenotypic Data Visualization, once the right CVS file is uploaded and file separator value is chosen, the time point will be automatically updated. The users can select the time point, and choose the time point to see the histogram and density plots. Users can also select box plot type to see the trend and variation across all the time points. All the plot types are interactive, and users can interact to get more information .

How to Run the Application

On server

The application is hosted on at:

On Local Machine

The application can be run locally with just one command in R software or RStudio:

shiny::runGitHub("ShinyAIM", "whussain2")

After running the above code the required libraries including shiny, ggplot2, dplyr, grid, plotly, manhattanly, and forcats will be automatically installed. These packages can also be installed within RStudio by running the following code:


Source Code and Sample Files

Source code and sample files are available through GitHub:.

ShinyAIM GitHub Repository

or can be directly downloaded from latest version at:

A demo that shows how to use the application is available at:

How to cite ShinyAIM: Hussain W, Campbell M, Walia H, Morota G. ShinyAIM: Shiny‐based application of interactive Manhattan plots for longitudinal genome‐wide association studies. Plant Direct 2018;2:1–4

Contact Information and Help:

Waseem Hussain -;, Gota Morota

Enjoy, and please give us valuable feedback.



We thank Yan Holtz for the useful R code provided on the webpage (link given below). Some of the codes has been adopted for this project to plot the grid Manhattan plot


Copyright (c) 2018, Waseem Hussain, code licensed under Artistic License 2.0.

Interactive Manhattan Plot

Markers Arranged in Significance Order


Manhattan Grid Plot

Compare Associated Markers Across Timepoints

Shapes and colors represent timepoints or phenotypes