Statistical Analysis of DNA Methylation Data in a Cervical Cancer Study
Department
Mathematics and Statistics
Major
Applied Mathematics with an emphasis in Statistics
Research Advisor
Olbricht, Gayla R.
Advisor's Department
Mathematics and Statistics
Funding Source
Center for Undergraduate Research in Mathematics via the National Science Foundation (NSF) grant #DMS-0636648 / #DMS-1148695 awarded to Brigham Young University (BYU).
Abstract
DNA methylation occurs when methyl groups attach to cytosine bases on DNA segments. Previous studies have established links between specific methylation patterns and many diseases. In this research, statistical methods are employed to test for significant differences in methylation levels between HIV patients with different stages of cervical cancer. DNA methylation levels are measured at cytosines across the genome with Illumina 450K methylation microarrays. After initial pre-processing to eliminate low-quality data, testing was performed at each cytosine site using t-tests and empirical Bayes tests to identify any statistically significant site level methylation differences between the cervical cancer stages. Two region level statistical methods (Bumphunter and DMRcate) were also applied to identify statistically significant regions of interest in the genome. Significant sites or regions that overlap with genes, CpG Islands, or other genomic annotations can help researchers better understand the molecular impact of DNA methylation and its connection to cervical cancer.
Biography
Elizabeth Hollen is a senior in applied mathematics with an emphasis in statistics. Active on campus, she is a Student Ambassador and a board member of the undergraduate student leadership council. Jason Viehman is a sophomore in applied mathematics. He is the historian and community service chair of S&T's chapter of Kappa Mu Epsilon. He is also starting to get involved in the local MAA chapter, in addition to being a peer learning assistant.
Research Category
Sciences
Presentation Type
Poster Presentation
Document Type
Poster
Location
Upper Atrium/Hall
Presentation Date
11 Apr 2017, 9:00 am - 11:45 am
Statistical Analysis of DNA Methylation Data in a Cervical Cancer Study
Upper Atrium/Hall
DNA methylation occurs when methyl groups attach to cytosine bases on DNA segments. Previous studies have established links between specific methylation patterns and many diseases. In this research, statistical methods are employed to test for significant differences in methylation levels between HIV patients with different stages of cervical cancer. DNA methylation levels are measured at cytosines across the genome with Illumina 450K methylation microarrays. After initial pre-processing to eliminate low-quality data, testing was performed at each cytosine site using t-tests and empirical Bayes tests to identify any statistically significant site level methylation differences between the cervical cancer stages. Two region level statistical methods (Bumphunter and DMRcate) were also applied to identify statistically significant regions of interest in the genome. Significant sites or regions that overlap with genes, CpG Islands, or other genomic annotations can help researchers better understand the molecular impact of DNA methylation and its connection to cervical cancer.
Comments
Alternate title: Investigating Statistical Issues in DNA Methylation and their Relation to Cervical Cancer (Jason Vieman)