1. Comparison of normalization methods with microRNA microarray
- Author
-
Kang Tu, You-Jia Hua, Zhong-Yi Tang, Hua-Sheng Xiao, and Yixue Li
- Subjects
Normalization (statistics) ,Male ,Microarray ,Computational biology ,Biology ,Print-tip loess ,Rats, Sprague-Dawley ,RNA interference ,Ganglia, Spinal ,microRNA ,Gene expression ,Genetics ,Gene silencing ,Animals ,Cluster Analysis ,Radiculopathy ,Oligonucleotide Array Sequence Analysis ,Microarray analysis techniques ,Reverse Transcriptase Polymerase Chain Reaction ,Molecular biology ,Rats ,Normalization ,MicroRNAs ,microRNA microarray ,Real-time polymerase chain reaction ,Data Interpretation, Statistical - Abstract
MicroRNAs (miRNAs) are a group of RNAs that play important roles in regulating gene expression and protein translation. In a previous study, we established an oligonucleotide microarray platform to detect miRNA expression. Because it contained only hundreds of probes, data normalization was difficult. In this study, the microarray data for eight miRNAs extracted from inflamed rat dorsal root ganglion (DRG) tissue were normalized using 15 methods and compared with the results of real-time polymerase chain reaction. It was found that the miRNA microarray data normalized by the print-tip loess method were the most consistent with results from real-time polymerase chain reaction. Moreover, the same pattern was also observed in 14 different types of rat tissue. This study compares a variety of normalization methods and will be helpful in the preprocessing of miRNA microarray data.
- Published
- 2007