Abstract: Objective RNA sequencing is a common technique for gene expression profiling. The goal was to examine the effects of different methods upon data homogenization of glomerular RNA sequencing and seek an optimal mode of data processing.Methods The adjacent tissues of kidney cancer were harvested and glomeruli extracted by screen technology. Trizol method was employed for extracting glomerular RNA. Then RNA data were acquired by Ion Xpress deep sequencing. PCA analysis was performed with the PCA data in R package. And rlog and median/ratio of DESEQ2 were utilized for data homogenization. Pheatmap and GGPLOT2 in R package were used for drawing a heat map.Results The conventional rlog method recommended by Ion Xpress could not well homogenize the data while the median/ratio of Deseq2 software offered better data homogenization. Cluster analysis was performed by selecting eight housekeeping genes. Housekeeping genes showed no significant differences among three classifications of kmeans. Thus it proved the reliability of the data homogenization results.Conclusion The median/ratio method of Deseq2 software may be employed for processing the data of glomerular RNA sequencing. And it has a better effect of data homogenization.