Pangenomics

This project works on developing novel representations and analyses for multiomic pangenomic data to aid in the interrogation and manipulation of plant genetic diversity. The exponential growth of complete, high-quality genomes and functional sequencing datasets has created opportunity for algorithmic innovation. We are developing new techniques for representing and analyzing multi-omic pangenomic data, including connecting genomic regions to phenotypes such as expression levels and climate adaptation.

Funding

• NSF-1759522 Collaborative Research: Innovation: Pioneering New Approaches to Explore Pangenomic Space at Scale. Joint with Joann Mudge (National Center for Genomics Research), Alan Cleary (National Center for Genomics Research), Thiru Ramaraj (DePaul University), Indika Kahanda (University of North Florida)

Select Publications

• I. Kahanda, B. Manuweera, B. Mumey, T. Ramaraj, A. Cleary, J. Mudge. Genotype-to-Phenotype Associations with Frequented Region Variants. 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). 114-119. doi.org/10.1109/BIBM58861.2023.10385551

• A. Cleary, T. Ramaraj, I. Kahanda, J. Mudge and B. Mumey, Exploring Frequented Regions in Pan-Genomic Graphs. IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 16, no. 05. 1424-1435. 2019. doi.org/10.1109/TCBB.2018.2864564