(B)reeding (I)nsight (G)enomics app

Currently, Breeding Insight provides bioinformatic processing support for our external collaborators. This R shiny app will provide a web-based user friendly way for our internal and external collaborators to analyze genomic data without needing to use command-line tools.

Supported Analyses

Initial supported analyses will include the mature genomics/bioinformatics pipelines developed within Breeding Insight, with additional analyses continuing to be added.

Supported:

• Genotype processing
  • Dosage call from read counts
  • SNP filtering
  • Sample filtering
• Summary metrics
  • SNP Allele Frequency
  • SNP Minor Allele Frequency
  • Sample Observed Heterozygosity
• Population Structure
  • PCA
  • DAPC
• GWAS
• GS
  • Estimate Model Prediction Accuracy
  • Predict Trait Values for New Genotypes

Running the BIG app

Tutorial available: https://scribehow.com/page/BIGapp_Tutorials__FdLsY9ZxQsi6kgT9p-U2Zg

Online preview: https://big-demo.shinyapps.io/bigapp/

Local computer

1. Install R
2. Open Terminal (on mac)
3. To install and run development version of package: (in terminal)

install.packages("devtools") #If not already installed
devtools::install_github("Breeding-Insight/BIGapp")
BIGapp::run_app()

4. View shiny app in browser

Online (in progress)

Third-party software

The BIG app relies on both custom scripts and previously developed R packages cited below:

• R: version 4.2.2

R packages

• Shiny tools: shiny, shinyWidgets, shinyalert, shinyjs, shinydisconnect, shinycssloaders, bs4Dash, DT, config

• Genetic analysis: updog, GWASpoly, AGHmatrix, rrBLUP, BIGr, adegenet, vcfR

• Data manipulation optimization: dplyr, tidyr, purrr, stringr, future, tibble

• Statistical analysis: factoextra, MASS, Matrix, matrixcalc

• Generate pretty graphics: ggplot2, scales, RColorBrewer, plotly

Funding Sources

Breeding Insight is funded by USDA through Cornell University.