Title

Statistical Analysis of DNA Methylation Data in a Cervical Cancer Study

Presenter Information

Elizabeth Hollen
Jason Viehman

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

Start Date

4-11-2017 9:00 AM

End Date

4-11-2017 11:45 AM

Comments

Alternate title: Investigating Statistical Issues in DNA Methylation and their Relation to Cervical Cancer (Jason Vieman)

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Apr 11th, 9:00 AM Apr 11th, 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.