Browsing by Subject "Gene Co-Expression"

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    Co-expression pairs and modules (CoEX-PM): a shiny application and an example case study on chromogranins
    (2018-09) Kaya, Tuğberk
    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.