Large Scale Comparison of Gene Expression Levels by Microarrays and RNAseq Using TCGA Data

Yan Guo, Quanhu Sheng, Jiang Li, Fei Ye, David C. Samuels, Yu Shyr

研究成果: Article同行評審

147 引文 斯高帕斯(Scopus)

摘要

RNAseq and microarray methods are frequently used to measure gene expression level. While similar in purpose, there are fundamental differences between the two technologies. Here, we present the largest comparative study between microarray and RNAseq methods to date using The Cancer Genome Atlas (TCGA) data. We found high correlations between expression data obtained from the Affymetrix one-channel microarray and RNAseq (Spearman correlations coefficients of ∼0.8). We also observed that the low abundance genes had poorer correlations between microarray and RNAseq data than high abundance genes. As expected, due to measurement and normalization differences, Agilent two-channel microarray and RNAseq data were poorly correlated (Spearman correlations coefficients of only ∼0.2). By examining the differentially expressed genes between tumor and normal samples we observed reasonable concordance in directionality between Agilent two-channel microarray and RNAseq data, although a small group of genes were found to have expression changes reported in opposite directions using these two technologies. Overall, RNAseq produces comparable results to microarray technologies in term of expression profiling. The RNAseq normalization methods RPKM and RSEM produce similar results on the gene level and reasonably concordant results on the exon level. Longer exons tended to have better concordance between the two normalization methods than shorter exons.

原文English
文章編號e71462
期刊PloS one
8
發行號8
DOIs
出版狀態Published - 2013 八月 20

All Science Journal Classification (ASJC) codes

  • 生物化學、遺傳與分子生物學 (全部)
  • 農業與生物科學 (全部)
  • 多學科

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