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THESIS DEFENSE ABSTRACT

Combining High-Throughput Genomic Data: Methods and Utility

 Rob Scharpf, PhD Candidate, Johns Hopkins Department of Biostatistics

High-throughput technologies that measure an underlying biological process by quantifying levels of RNA or DNA in a cell can be combined. This integration has many useful applications. My thesis proposes methods for  combining gene expression data from multiple studies with applications to real data.  For SNP chips that measure chromosomal copy number and genotype, we propose combining these components into a single probabilistic model. Particular emphasis is  placed on visualization, open source R packages, and reproducible research.