Integrated analysis of microarray data and gene function information.
Microarray data should be interpreted in the context of existing biological knowledge. Here we present integrated analysis of microarray data and gene function classification data using homogeneity analysis. Homogeneity analysis is a graphical multivariate statistical method for analyzing categorical data. It converts categorical data into graphical display. By simultaneously quantifying the microarray-derived gene groups and gene function categories, it captures the complex relations between biological information derived from microarray data and the existing knowledge about the gene function. Thus, homogeneity analysis provides a mathematical framework for integrating the analysis of microarray data and the existing biological knowledge.
Department of Molecular Sciences, University of Tennessee Health Science Center, Memphis, 38103, USA. ycui2@utmem.edu
Yan
Y
Cui
Mi
M
Zhou
Wing Hung
WH
Wong
D000465:Algorithms; D019295:Computational Biology; D020869:Gene Expression Profiling; D008962:Models, Theoretical; D020411:Oligonucleotide Array Sequence Analysis; D013223:Statistics as Topic; D015003:Yeasts / Q000235:genetics