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dc.contributor.advisor Leal, Suzanne
dc.contributor.advisor Kimmel, Marek
dc.creatorLiu, Dajiang
dc.date.accessioned 2013-03-08T00:36:01Z
dc.date.available 2013-03-08T00:36:01Z
dc.date.issued 2012
dc.identifier.urihttps://hdl.handle.net/1911/70324
dc.description.abstract There is solid evidence that complex human diseases can be caused by rare variants. Next generation sequencing technology has revolutionized the study of complex human diseases, and made possible detecting associations with rare variants. Traditional statistical methods can be inefficient for analyzing sequence data and underpowered. In addition, due to high cost of sequencing, it is also necessary to explore novel cost effective studies in order to maximize power and reduce sequencing cost. In this thesis, three important problems for analyzing sequence data and detecting associations with rare variants are presented. In the first chapter, we presented a new method for detecting rare variants/binary trait associations in the presence of gene interactions. In the second chapter, we explored cost effective study designs for replicating sequence based association studies, combining both sequencing and customized genotyping. In the third chapter, we present a method for analyzing multiple phenotypes in selected samples, such that phenotypes that are commonly measured in different studies can be jointly analyzed to improve power. The methods and study designs presented are important for dissecting complex trait etiologies using sequence data.
dc.format.extent 128 p.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.subjectPure sciences
Biological sciences
Rare variants
Complex traits
Sequencing data
Genetics
Statistics
dc.title Statistical Methods for Analyzing Rare Variant Complex Trait Associations via Sequence Data
dc.identifier.digital LiuD
dc.type.genre Thesis
dc.type.material Text
thesis.degree.department Statistics
thesis.degree.discipline Engineering
thesis.degree.grantor Rice University
thesis.degree.level Doctoral
thesis.degree.name Doctor of Philosophy
dc.identifier.citation Liu, Dajiang. "Statistical Methods for Analyzing Rare Variant Complex Trait Associations via Sequence Data." (2012) Diss., Rice University. https://hdl.handle.net/1911/70324.


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