A statistical integrative analysis method for microRNA and gene expression

MicroRNA (miRNA), a type of non-coding RNA, is known to suppress the expression of target genes and there is an increasing number of studies analyzing various miRNAs in cancer. In an integrated analysis of miRNA and gene expressions, it is often difficult to obtain a significant result with a small amount of data. In this study, we proposed a method that allows integrated analysis even with a small amount of miRNA and gene expression data, and examined its validity. The method is based on a group comparison between target genes having specific functions controlled by a specific miRNA and a background group of randomly selected genes. We conducted a simulation to verify the validity of the proposed method. The simulation results indicated that the method can detect significant differences in expression of target genes controlled by a miRNA showing significant expression change. We then applied the proposed method to real data derived from multiple myeloma cells. As a result, some functions were detected as significantly changed due to a significant change of miRNA.