Kaya, Tuğberk2018-10-042018-10-042018-092018-092018-09-03http://hdl.handle.net/11693/48074Cataloged from PDF version of article.Thesis (M.S.): Bilkent University, Department of Neuroscience, İhsan Doğramacı Bilkent University, 2018.Includes bibliographical references (leaves 86-89).Gene expression signatures have been proved to be effective biomarkers of tumorigenesis and metastasis especially when alternative methods are inconvenient or ineffective. Nevertheless, handling very large datasets obtained via high-throughput protocols to extract gene expression signatures may prove challenging. A great number of software packages that facilitate such analyses have been written in R programming language are publicly available and free. However, the relatively steep learning curve that is required to use R proficiently prevents the utilization of these packages. I have developed the Shiny application Co-expression Modules and Pairs (CoEX-PM) using R programming language and the R package shiny. The CoEX-PM application handles human Affymetrix microarray data and enables users to generate pairwise correlation plots, conduct meta-correlation analysis with user-selected GEO datasets along with co-expression module generation by WGCNA program for genes of interest. The CoEX-PM application provides the user with a GUI, therefore, does not require any coding knowledge to perform the analyses. Pheochromocytoma (PCC) and neuroblastoma (NB) are neural-crest derived tumors, common in adults and children, respectively and are both associated with high-rate of morbidity and mortality. In addition, both tumor types display neuroendocrine tumor (NET) characteristics. Chromogranin A (CgA) has been linked with NETs as a moderately sensitive and non-specific tumor marker. The chromogranin family consists of up to seven members, three of which are chromogranin (CgA), chromogranin B (CgB) and secretogranin II (SgII) or occasionally named as chromogranin C (CgC). However, it is not known whether chromogranin/secretogranin family members are differentially co-expressed in PCC and NB. Here, I investigate the degree of co-expression in gene networks by analyzing gene expression signatures of the chromogranin/secretogranin paralogous gene family using CoEX-PM application on neuroendocrine tumor datasets. The findings indicate presence of concise and highly co-expressed functional components in PCC and NB driven by chromogranin expression signatures.xiii, 89 leaves : illustrations, tables, charts (some color) ; 30 cm.Englishinfo:eu-repo/semantics/openAccessMicroarrayR Programming LanguageGene Co-ExpressionNeuroendocrine TumorsThesisB158380