Understanding others is a deeply human urge basic in our existential quest. It requires knowing where someone has come from and where they sit amongst peers. Phylogenetic analysis and genome wide association studies seek to tell us where we’ve come from and where we are relative to one another through evolutionary history and genetic makeup. Current methods do not address the computational complexity caused by new forms of genomic data, namely long-read DNA sequencing and increased abundances of assembled genomes, that are becoming evermore abundant. To address this, we explore specialized data structures for storing and comparing genomic information. This work resulted in the creation of novel data structures for storing multiple genomes that can be used for identifying structural variations and other types of polymorphisms. Using these methods we illuminate the genetic history of organisms in our efforts to understand the world around us.
College and Department
Physical and Mathematical Sciences; Computer Science
BYU ScholarsArchive Citation
Fujimoto, Masaki Stanley, "Graph-Based Whole Genome Phylogenomics" (2020). Theses and Dissertations. 8461.
Genomics, Next-Gen Sequencing, Parallel Programming, Data Structures, Phylogenetics, Phylogenomics, de Bruijn Graph, NGS Read Mapping, Whole Genome Alignment, Whole Genome Analysis