- Statistical Inference of Mutations in Clonal Genomic Data
- Project Year:
2019
- REU Student (s):
Theodora Katsarou | Stony Brook University NY
- Student 1 Institution:
Stony Brook University
- Project Mentor:
Hossein Khiabanian
- Project Mentor Area:
Rutgers Cancer Institute of New Jersey
- Project Abstract:
Phylogenetic trees have been used in biology to graphically represent hierarchical relationships between genes. Many methods used to construct these phylogenetic trees often produce trees that are too large for easy visualization, or statistical analysis. Hence, reducing the dimensionality of large phylogenetic trees is a key to better understanding large data sets. We study what methods are best suited for tree dimensionality reduction and how we can use those methods to reconstruct trees that suit our data set of influenza from 1993-2017. Through analyzing the topology of reduced trees, we concluded that mutations rate and reassortment reduces the effectiveness of vaccines, resulting in individuals being unprotected against the new strains in circulation. Thus, as vaccine effectiveness increases, branched evolution in influenza decreases. Most importantly, the methods we used are beneficial in visualizing and analyzing any type of clonal genomic data.
