Constructed an unbiased pangenome graph of 38 reference-quality soybean genomes for the enhanced capture and representation of global genetic diversity within agronomically relevant cultivars. Developed workflows to remove alignment artifacts and complex regions in pangenome graphs using the ODGI toolkit and to validate small and large scale variants using a Soy HapMap and known gene PAVs. Demonstrated the pangenome model's utility by exploring the genetic variation across cultivars within target regions of the gene-editing platform.

Consultant for graduate research projects involving bioinformatics tools and NGS data. Organized and co-led graduate student workshops on bioinformatics fundamentals, working on a compute cluster, and phylogenomics workflows. Collaborated with Ph. D candidate to develop strategies to identify optimal reference sequences for extracting variants from NGS data. Independently designed a script to extract unique alleles in amplicon sequencing data for Ph. D candidates performing parentage analyses.

Collaborated with lab members to construct a coalescent phylogeny containing 200+ Lobelioid taxa using target enrichment NGS data. Frequently communicated with a post-doctoral student and the principal investigator to discuss observed results and methods to improve tree support. Bioinformatics workflows involved (1) turning raw reads into multi-sequence alignments, (2) constructing gene trees, and (3) inferring a species tree by coalescing gene trees.

Compared novel approaches and methodologies in accurately detecting and extracting paralogous genes from NGS data of a dozen Rosaceae species. Uncovered trends in phylogenomic depth and sampling that inform optimal approaches to use for identifying paralogous genes. Discovered that including versus excluding paralogous genes during phylogenomic tree reconstructions had little to no impact on tree topology of the Rosaceae species.

Determined the mechanism for self-incompatibility in three Castilleja species via fluorescence microscopy.