Understanding the role of deregulated biological pathways in cancer samples has the potential to improve cancer treatment, making it more effective by selecting treatments that reverse the biological cause of the cancer. One of the challenges with pathway analysis is identifying a deregulated pathway in a given sample. This project develops the Universal Probability of Expression Code (UPC), a profile of a single deregulated biological path- way, and projects it into a cancer cell to determine if it is present. One of the benefits of this method is that rather than use information from a single over-expressed gene, it pro- vides a profile of multiple genes, which has been shown by Sjoblom et al. (2006) and Wood et al. (2007) to be more effective. The UPC uses a novel normalization and summarization approach to characterize a deregulated pathway using only data from the array (Mixture model-based analysis of expression arrays, MMAX), making it applicable to all microarray platforms, unlike other methods. When compared to both Affymetrix's PMA calls (Hubbell, Liu, and Mei 2002) and Barcoding (Zilliox and Irizarry 2007), it performs comparably.
College and Department
Physical and Mathematical Sciences; Statistics
BYU ScholarsArchive Citation
Withers, Michelle Rachel, "Utilizing Universal Probability of Expression Code (UPC) to Identify Disrupted Pathways in Cancer Samples" (2011). Theses and Dissertations. 2505.
oncogenic pathways, microarray normalization