Application of singular value decomposition and functional clustering to analyzing gene expression profiles of renal cell carcinoma

Abstract

Microarray gene expression profiles of both renal cell carcinoma (RCC) tissues and a RCC cell line were analyzed using singular value decomposition (SVD) and functional clustering. The SVD projections of the expression profiles revealed significant differences between the profiles of RCC tissues and a RCC cell line. Based on the biological processes, selected genes were annotated and clustered into functional groups. The analysis of each functional group revealed remarkable gene expression alterations in the biological pathways in RCC and provided insights into understanding the molecular mechanism of renal cell carcinogenesis.