Discovery And Visual Analysis of Tracts of Homozygosity In The Human Genome

I propose a new visual analytics system designed for genetic researchers to study genome-wide homozygosity regions. Finding significant tracts of homozygosity (TOH) using single nucleotide polymorphisms (SNPs) from a large-scale genome data set can contribute to the discovery of genetic factors related to human diseases. The proposed system helps users to visually examine TOH clusters computed from the underlying patient data, lending itself a convenient and powerful tool for knowledge discovery. I've designed and implement the TOH clustering algorithm based on repeated binary spectral clustering. A hierarchy of clusters is created and represented by a TOH cluster (TOHC) tree. Researchers can investigate the clusters with a special interactive widget, namely navigation rings, which is integrated with a visual cluster explorer. Statistical association study and NCBI genome map viewer are also incorporated into the system. The usability and performance of the system is illustrated with a clinical data set of human cancers.

Name thesis:degree_name

MS

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

College of Arts and Sciences / Department of Computer Science

Grantor dc:publisher

Kent State University

Year dc:date

2013

Author dc:creator

• Reber, Sean Cameron

Contributors dc:contributor

• Zhao, Ye

• Computer Science
• Bioinformatics
• Genome
• Tracts of Homozygosity
• Single Nucleotide Polymorphism
• Genomic Risk
• Association Study
• Visual Analytics
• Data Mining

Statement dc:rights

• unrestricted
• This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.

Language dc:language

English

Repository record dc:identifier

http://rave.ohiolink.edu/etdc/view?acc_num=kent1365617689

OAI identifier oai:identifier

oai:etd.ohiolink.edu:kent1365617689