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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp014j03d246x
Title: ReannotatoR: A Tool for Comparative Analysis of RNA-Seq and its Application in Highlighting Differences Between HCMV and Oncoviruses
Authors: Schoenberg, Yoni
Advisors: Shenk, Thomas
Department: Molecular Biology
Certificate Program: Applications of Computing Program
Class Year: 2019
Abstract: RNA-sequencing technology (RNA-seq) allows for measurement of mRNA in cells, providing gene expression levels. RNA-seq data from published studies are available in a public repository maintained by the National Center for Biotechnology Information (NCBI), but the metadata is difficult to access, making cross-study analyses challenging. Here we describe a tool that we developed, which we have named ReannotatoR, that organizes RNA-seq metadata into an editable spreadsheet format. Metadata can be viewed and experimental conditions annotated into specific columns, allowing for downstream analysis of the RNA-seq data for differential gene expression levels between experimental conditions. To show the utility of our tool, we use it to analyze RNA-seq data from cells infected with different viruses. We explore expression levels of p53 target genes in cells infected with different known oncoviruses and Human cytomegalovirus (HCMV), which all inhibit activity of the p53 tumor suppressor, to better understand why HCMV has not been shown to be an oncovirus. Our results identify three genes or family of genes that are upregulated in HCMV-infected cells and downregulated in cells infected with oncoviruses. These findings highlight potential novel gene functions that can be tested in the lab, which ultimately could lead to understanding how to mitigate the effects of p53 mutations in cancer. Additionally, they highlight our tool’s ability to help answer many questions in biology using publicly available RNA-seq data.
URI: http://arks.princeton.edu/ark:/88435/dsp014j03d246x
Type of Material: Princeton University Senior Theses
Language: en
Appears in Collections:Molecular Biology, 1954-2020

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