Within bioinformatics, phylogenetics is the study of the evolutionary relationships between different species and organisms. The genetic revolution has caused an explosion in the amount of raw genomic information that is available to scientists for study. While there has been an explosion in available data, analysis methods have lagged behind. A key task in phylogenetics is identifying homology clusters. Current methods rely on using heuristics based on pairwise sequence comparison to identify homology clusters. We propose the Orthology Group Cleaner (the OGCleaner) as a method to evaluate cluster level verification of putative homology clusters in order to create higher quality phylogenetic tree reconstruction.
College and Department
Physical and Mathematical Sciences; Computer Science
BYU ScholarsArchive Citation
Fujimoto, Masaki Stanley, "The OGCleaner: Detecting False-Positive Sequence Homology" (2017). All Theses and Dissertations. 6410.
machine learning, orthology clusters, phylogenetics