These open source software solutions offer users a way to make various genomic, bioinformatic and phenomic workflows easier.
Breeding Insight’s open source software solutions
Any questions regarding any of our tools? Email breedinginsight@cornell.edu.

BIGr is a RPackage for a-to-z genomic analyses.
Applications: Genomics, GWAS, GS
Language: R
GitHub link: https://github.com/Breeding-Insight/BIGr
RRID: SCR_o26677
For citations, please include both of the following for the package and the methods:
- Sandercock, Alexander M., Cristiane H. Taniguti, Josue Chinchilla-Vargas, Dongyan Zhao, Shufen Chen, Meng Lin, Manoj Sapkota, and Breeding Insight Team. 2025. “Breeding Insight Genomics Functions for Polypoid and Diploid Species.”
- Sandercock A.M., Peel M.D., Tanigut C.H., Chinchilla-Vargas J., Chen S., Sapkota M., Lin M., Zhao D., Ackerman A.J., Basnet B.R., Beil C.T., Sheehan M.J. (2025). BIGapp: A User-Friendly Genomic Tool Kit Identified Quantitative Trait Loci for Creeping Rootedness in Alfalfa (Medicago sativa L.)., The Plant Genome. doi:https://doi.org/10.1002/tpg2.70067

Qploidy is a RPackage tools for ploidy estimation with array and target markers.
Applications: Genomics
Language: R
GitHub link: https://github.com/Cristianetaniguti/qploidy
RRID: SCR_o26724
For citations, please reference the following: Taniguti, C.H; Lau, J.; Hochhaus, T.; Arias Lopez, D. C.; Hokanson, S.C.; Zlesak, D. C.; Byrne, D. H.; Klein, P.E. and Riera-Lizarazu, O. Exploring Chromosomal Variations in Garden Roses: Insights from High-density SNP Array Data and a New Tool, Qploidy. The Plant Genome, e70044. https://doi.org/10.1002/tpg2.70044
BerryPortraits is a Python pipeline for image analysis.
Applications: Image analysis
Language: Python
GitHub link: https://github.com/Breeding-Insight/berryportraits
RRID: SCR_026628
For citations, please reference the following: Loarca, J., Wiesner-Hanks, T., Lopez-Moreno, H. et al. BerryPortraits: Phenotyping Of Ripening Traits in cranberry (Vaccinium macrocarpon Ait.) with YOLOv8. Plant Methods 20, 172 (2024). https://doi.org/10.1186/s13007-024-01285-1