Publication Date


Document Type


First Advisor

Hou, Minmei

Degree Name

M.S. (Master of Science)

Legacy Department

Department of Computer Science


Computer science; Genomics; Computer science


Pico-inversions are very small inversions that cannot be detected by local alignments directly. The study of these inversions has been very limited in the past due to the limitations of computational techniques. I performed a study to improve the accuracy of detecting small inversions among the genomes of human individuals, pico-inversions. My hypothesis is that inversion is rare, and the chance of multiple inversions occurring on the same genome site among multiple individuals is small. Therefore, the sequences of an inversion site can be divided into two clusters: one with the inversion and the other without the inversion. The sequences of chromosome 20 of twenty human individuals were used for this study. I first detected pico-inversions and created 1775 Multi-Inversion-Blocks using existing tools. I then realigned sequences in these blocks to create better alignment. To cluster the sequences in each block, I counted the number of substitutions between each pair of sequences and created distance matrices. Based on the distance matrices, I implemented a hierarchical clustering tool to create two clusters for each block of sequences. I then calculated the internal and external distances of these clusters to quantify the quality of clusters. This study builds a framework to further validate pico-inversions among human individuals.


Advisors: Minmei Hou.||Committee members: Reva Freedman; Jie Zhou.


57 pages




Northern Illinois University

Rights Statement

In Copyright

Rights Statement 2

NIU theses are protected by copyright. They may be viewed from Huskie Commons for any purpose, but reproduction or distribution in any format is prohibited without the written permission of the authors.

Media Type