Integrative statistical approaches to gain biological insights from genome-wide association studies

dc.contributor.advisor	Li, Bingshan
dc.creator	Ji, Ying
dc.date.accessioned	2021-07-09T03:51:25Z
dc.date.created	2021-06
dc.date.issued	2021-06-11
dc.date.submitted	June 2021
dc.identifier.uri	http://hdl.handle.net/1803/16730
dc.description.abstract	This paper
dc.format.mimetype	application/pdf
dc.language.iso	en
dc.subject	Genome wide association studies (GWAS)
dc.subject	gene-level association test
dc.subject	splicing
dc.subject	false discovery rate
dc.subject	hypothesis weighting
dc.subject	polygenic risk score
dc.title	Integrative statistical approaches to gain biological insights from genome-wide association studies
dc.type	Thesis
dc.date.updated	2021-07-09T03:51:25Z
dc.type.material	text
thesis.degree.name	PhD
thesis.degree.level	Doctoral
thesis.degree.discipline	Human Genetics
thesis.degree.grantor	Vanderbilt University Graduate School
local.embargo.terms	2021-12-01
local.embargo.lift	2021-12-01
dc.creator.orcid	0000-0001-5691-1303
dc.contributor.committeeChair	Sutcliffe, James S

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