Assessing technical performance in differential gene expression experiments with external spike-in RNA control ratio mixtures

• Published in: Nature communications 2014-09, Vol.5 (1), p.5125, Article 5125
• Main Authors: Munro, Sarah A., Lund, Steven P., Pine, P. Scott, Binder, Hans, Clevert, Djork-Arné, Conesa, Ana, Dopazo, Joaquin, Fasold, Mario, Hochreiter, Sepp, Hong, Huixiao, Jafari, Nadereh, Kreil, David P., Łabaj, Paweł P., Li, Sheng, Liao, Yang, Lin, Simon M., Meehan, Joseph, Mason, Christopher E., Santoyo-Lopez, Javier, Setterquist, Robert A., Shi, Leming, Shi, Wei, Smyth, Gordon K., Stralis-Pavese, Nancy, Su, Zhenqiang, Tong, Weida, Wang, Charles, Wang, Jian, Xu, Joshua, Ye, Zhan, Yang, Yong, Yu, Ying, Salit, Marc
• Format: Article
• Language: English
• Subjects: 38; 38/61; 38/91; 631/114; 631/1647/2017; Gene Expression Profiling - methods; Gene Expression Profiling - standards; Humanities and Social Sciences; Humans; multidisciplinary; Reference Standards; Reproducibility of Results; RNA, Messenger - genetics; Science; Science (multidisciplinary)
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/ncomms6125

There is a critical need for standard approaches to assess, report and compare the technical performance of genome-scale differential gene expression experiments. Here we assess technical performance with a proposed standard ‘dashboard’ of metrics derived from analysis of external spike-in RNA control ratio mixtures. These control ratio mixtures with defined abundance ratios enable assessment of diagnostic performance of differentially expressed transcript lists, limit of detection of ratio (LODR) estimates and expression ratio variability and measurement bias. The performance metrics suite is applicable to analysis of a typical experiment, and here we also apply these metrics to evaluate technical performance among laboratories. An interlaboratory study using identical samples shared among 12 laboratories with three different measurement processes demonstrates generally consistent diagnostic power across 11 laboratories. Ratio measurement variability and bias are also comparable among laboratories for the same measurement process. We observe different biases for measurement processes using different mRNA-enrichment protocols. Differential gene expression experiments yield quantitative insight into biological activity and may be important in disease classification and treatment. Here, the authors analyse external spike-in RNA controls to provide a standard method to assess and compare experiment performance.