Cross-SAGE: SAGE Data Mining Tool Based on Set Theory
SAGE (Serial Analysis of Gene Expression) is a technique for analyzing gene expression of a series of tags obtained from cDNA. This technology lets biologists analyze and observe the relative gene expressions of many samples in silico. To date, some visible analyzing platforms for SAGE were not provided in a biologically significance way for cross-analysis and -comparison, thus limiting its application. Therefore, the author retrieved various SAGE databases of Homo sapiens from NCBI SAGEmap and proposed a powerful tool for cross-analyzing gene expression among different SAGE libraries of tissue sources. This paper combines the mathematical set theory with a unique multi-group method to analyze SAGE data, and provide the function for gaining the corresponding information between tags and genes.