A Statistical Analysis of DNA Methylation In a Shift Work Study
Department
Mathematics and Statistics
Major
Applied Mathematics
Research Advisor
Olbricht, Gayla R.
Advisor's Department
Mathematics and Statistics
Funding Source
OURE
Abstract
DNA methylation occurs when methyl groups attach to cytosine nucleotides on DNA segments. Previous studies have established links between specific methylation patterns and certain lifestyles. In this research, statistical methods are employed to test for significant differences in methylation levels between females who work the night shift and females who work the day shift. 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 different shifts. A region level statistical method known as Bumphunter was 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 shift work.
Biography
Jason Viehman is a senior in applied mathematics. He is also getting a second bachelors in economics, and an emphasis area in actuarial science. He has been the historian, community service chair, and president of S&T's chapter of Kappa Mu Epsilon.
Research Category
Sciences
Presentation Type
Poster Presentation
Document Type
Poster
Location
Upper Atrium
Presentation Date
17 Apr 2018, 9:00 am - 12:00 pm
A Statistical Analysis of DNA Methylation In a Shift Work Study
Upper Atrium
DNA methylation occurs when methyl groups attach to cytosine nucleotides on DNA segments. Previous studies have established links between specific methylation patterns and certain lifestyles. In this research, statistical methods are employed to test for significant differences in methylation levels between females who work the night shift and females who work the day shift. 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 different shifts. A region level statistical method known as Bumphunter was 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 shift work.
