Director of Research (if dissertation) or Advisor (if thesis)
Zhao, Sihai D
Doctoral Committee Chair(s)
Zhao, Sihai D
Committee Member(s)
Foss, Alexander H
Li, Bo
Simpson, Douglas G
Department of Study
Statistics
Discipline
Statistics
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Dimension Reduction
Contrastive
Methylation
Bioinformatics
Statistics
Methodology
Abstract
Data integration challenges in bioinformatics are multifaceted. This paper aims to motivate methods and techniques to handle multiple data types and data sources. We integrate multiple sources of data to explore the usefulness of proxy blood methylation as a substitute for brain tissue. We then propose a likelihood based dimension reduction method to handle non-quantitative data. Lastly, we propose a tuning-free method that identifies low-dimensional representations of a target dataset relative to one or more comparison datasets which also is computationally efficient even with large numbers of features.
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