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dc.contributor.authorClaussen, Henry
dc.date.accessioned2021-07-16T19:03:13Z
dc.date.available2021-07-16T19:03:13Z
dc.date.issued2021-07
dc.identifier.urihttp://hdl.handle.net/10675.2/624128
dc.description.abstractThe collection and order of nucleobases in a strand of DNA, called the primary sequence, is one of the most important pieces of information in the study of the human body. The proteins which regulate all biological functions in the body are synthesized based on the structure of the DNA molecule. The next generation sequencing (NGS) process of sequencing RNA transcripts, known as RNA-seq, has become a powerful alternative to traditional microarray technology. NGS is used to measure the levels of gene expression, detect structural DNA variations from the human reference genome, and uncover the epigenetic modifications of methylation. Despite its prevalence in genetic research, RNA-seq data suffers from the statistical complication known as ”large p small n” where the predictor variables greatly outnumber the subjects in a study. In this research we propose combining all three types of data into a multivariate linear model. With the implementation of a variable selection process for preliminary dimension reduction and the application of a Group LASSOapproach, we hope to reduce the complexity and dimension of NGS data to a manageable and, most importantly, interpretable level. Changes in gene expression levels have been linked with the development of harmful diseases such as cancer. A successful model will provide insight on the simultaneous effects that methylation and structural variation have on gene expression in the body.
dc.publisherAugusta University
dc.subjectBiostatistics
dc.titleMODELING THE SIMULTANEOUS EFFECTS OF COPY NUMBER VARIATION AND METHYLATION ON GENE EXPRESSION USING NEXT GENERATION SEQUENCING DATA
dc.typedissertationen_US
dc.contributor.departmentDepartment of Physiology
dc.language.rfc3066en
dc.date.updated2021-07-16T19:03:14Z
dc.description.advisorChen, Jie
dc.description.advisorGhosh, Santu
dc.description.committeeLinder, Daniel
dc.description.committeeShi, Huidong
dc.description.committeeShi, Yang
dc.description.committeeXu, Nathan
dc.description.degreePh.D.
refterms.dateFOA2021-12-06T21:10:14Z
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