Using the R package Shiny to create web applications that facilitate quantitative gene expression analysis

Thesis (Master's)--University of Washington, 2016-06

Kaposi’s Sarcoma-associated Herpesvirus (KSHV), the etiologic agent of Kaposi’s Sarcoma (KS) infects host cells and predominantly enters a latent state. Tumorigenesis, however, likely requires lytic replication. The signals that cause the virus to transition from latency to active viral replication are not understood completely. RNA-sequencing provides investigators with a way to study the viral transcriptome to determine patterns of gene expression. However, processing and analyzing the very large data sets obtained via high-throughput sequencing can be challenging. Numerous software packages have been written using the R programming language to assist investigators in working with large biological data sets. However, the steep learning curve required to use R effectively makes these packages potentially difficult to use. The new R package Shiny is a web application framework for R. For this project, two applications were developed using Shiny – 1) an application to generate figures with side-by-side box plots for selected genes, demonstrating the variance in the expression of these genes across samples; and 2) an application to perform principal components analysis on a dataset. Both applications provide the user with a graphical user interface, thus bypassing the need for any coding skills on the part of the investigator.