The human reference genome has been a cornerstone of biological research, yet its limited diversity restricts its applicability across different populations. Pangenomes, which incorporate genetic variations from diverse individuals, offer a more inclusive alternative, but their complexity poses significant computational challenges. In my research, I will develop innovative computational tools to address these challenges. First, I will create a haplotype sampling technique to generate personalized pangenome references, enhancing accuracy in mapping and variant calling. Next, I will design a novel graph indexing structure to efficiently store and retrieve data from pangenomes, reducing computational overhead. Finally, I will improve Moni-align, an advanced pangenome aligner. Integrating these advancements can optimize its performance for large-scale genomic analyses. These contributions aim to make pangenome-based analyses more reliable and accessible, advancing the field of genomics.

Event Host: Parsa Eskander, Ph.D. Student, Biomolecular Engineering & Bioinformatics 

Advisor: Benedict Paten