Introduction to BIGapp for Plant Breeding
A beginner workshop for point-and-click genomic analysis
BIGapp is a free R Shiny application for processing and analyzing low- to mid-density genotype data in diploid and polyploid species. This workshop uses its graphical interface, so no R or command-line experience is required.
Complete required setup Download workshop data
The hands-on exercises run in a local BIGapp installation. The public online BIGapp is a view-only preview for becoming familiar with the interface. Do not use the shared preview to run the workshop data or analyses.
These maintained materials are adapted from the original Introduction to BIGapp for Plant Breeding workshop. Interface labels and checkpoints have been updated for the official BIGapp main release.
Who this is for
This workshop is designed for students, researchers, and breeders who want to use genomic data without first learning a programming language. Familiarity with plant breeding is helpful, but prior experience with R, VCF files, or bioinformatics is not required.
What you will learn
By the end of the guided modules, you will be able to:
- Explain what SNP genotypes and allele dosage represent.
- Filter low-depth genotype cells, markers, and samples with adjustable criteria.
- Use PCA to inspect population structure and possible outliers.
- Run GWASpoly and interpret its BIC, Manhattan, QQ, and LD-window results.
- Describe how cross-validation supports genomic prediction decisions.
Workshop schedule
| Time | Activity |
|---|---|
| Before the session | Install BIGapp and complete the setup check |
| 0:00 to 0:10 | Confirm local BIGapp and workshop files |
| 0:10 to 0:50 | Module 1: Data quality control |
| 0:50 to 1:00 | Break |
| 1:00 to 1:25 | Module 2: Population structure and PCA |
| 1:25 to 1:55 | Module 3: GWASpoly |
| 1:55 to 2:00 | Review and next steps |
The genomic selection module is optional self-study material or an extension when time allows.
What you need
- R 4.4.0 or later and a local BIGapp installation
- A current web browser with JavaScript enabled
- Internet access during setup to install R packages
- The three local files described in the dataset guide
- Enough free disk space for BIGapp, its R-package dependencies, the workshop files, and saved results
The workflow
The guided analysis follows one continuous sequence:
- Install BIGapp, start it locally, and check the example files.
- Filter the VCF with dataset-specific example thresholds.
- Inspect genetic structure with PCA.
- Test the simulated fruit-weight trait with GWASpoly.
- Optionally estimate predictive ability and generate genomic predictions.
Each module includes written steps and a collapsible answer. The animations are supplementary, so you can complete every exercise without relying on them.
Help and reporting problems
For software problems, unexpected results, or feature requests, open an issue in the BIGapp repository. Include the BIGapp version or public-demo URL, the browser and operating system, the step that failed, and the complete error message. Do not attach private genotype or phenotype files to a public issue.