CLIC: clustering analysis of large microarray datasets with individual dimension-based clustering

摘要: Large microarray data sets have recently become common. However, most available clustering methods do not easily handle large due to their very computational complexity and memory requirements. Furthermore, typical construct oversimplified clusters that ignore subtle but meaningful changes in the expression patterns present sets. It is necessary develop an efficient method identifies both absolute differences profile different levels for This study presents CLIC, which meets requirements of analysis particularly limited CLIC based on a novel concept genes are clustered individual dimensions first ordinal labels each dimension then used further full dimension-wide clustering. enables iterative sub-clustering into more homogeneous groups identification common among separated difference levels. In addition, computation parallelized, number automatically detected, functional enrichment cluster pattern provided. freely at http://gexp2.kaist.ac.kr/clic.