Committee Chair
Yang, Li
Committee Member
Winters, Katherine; Kandah, Farah
College
College of Engineering and Computer Science
Publisher
University of Tennessee at Chattanooga
Place of Publication
Chattanooga (Tenn.)
Abstract
Substantial health disparities exist between African Americans and Caucasians in the United States. Copy number variations (CNVs) are one form of human genetic variations that have been linked with complex diseases and often occur at different frequencies among African Americans and Caucasian populations. In this study, we aimed to investigate whether CNVs with differential population frequencies can contribute to health disparities from the perspective of gene networks. We inferred network clusters from two different human gene/protein networks. We then evaluated each network cluster for the occurrences of known pathogenic genes and genes located in CNVs with different population frequencies, and used false discovery rates (FDRs) to rank network clusters. This approach let us identify five clusters enriched with known pathogenic genes and with genes located in CNVs with different frequencies between African Americans and Caucasians. These clustering patterns predict four candidate causal population-specific CNVs that play potential roles in health disparities.
Acknowledgments
I would like to express my deepest gratitude to my advisor, Dr. Li Yang, for her thoughtful guidance, warm encouragement, great patience, and financial support during the whole period of my research. I appreciate her vast knowledge and skills, and her assistance in writing this thesis. I would like to thank my thesis committee members, Prof. Farah Kandah and Ms. Katherine Winters for their excellent advises and detailed review during the preparation of this thesis. I would also like to thank Prof. Hong Qin at Spelman College, Atlanta, GA, for thoughtful guidance, insightful discussion, correction of my writing, and the help to develop my background in computational biology and genetics.
Degree
M. S.; A thesis submitted to the faculty of the University of Tennessee at Chattanooga in partial fulfillment of the requirements of the degree of Master of Science.
Date
12-2014
Subject
Bioinformatics; Variation (Biology); Human genetics; Genetic disorders
Document Type
Masters theses
DCMI Type
Text
Extent
ix, 47 leaves
Language
English
Rights
https://rightsstatements.org/page/InC/1.0/?language=en
License
http://creativecommons.org/licenses/by-nc-nd/3.0/
Recommended Citation
Jiang, Yi, "Using network clustering to predict copy number variations associated with health disparities" (2014). Masters Theses and Doctoral Dissertations.
https://scholar.utc.edu/theses/144
Department
Dept. of Computer Science and Engineering