External RNA controls (ERCs), although important for microarray assay performance assessment, have yet to be fully implemented in the research community. As part of the MicroArray Quality Control (MAQC) study, two types of ERCs were implemented and evaluated; one was added to the total RNA in the samples before amplification and labeling; the other was added to the copyRNAs (cRNAs) before hybridization. ERC concentration-response curves were used across multiple commercial microarray platforms to identify problematic assays and potential sources of variation in the analytical process. In addition, the behavior of different ERC types was investigated, resulting in several important observations, such as the sample-dependent attributes of performance and the potential of using these control RNAs in a combinatorial fashion. This multiplatform investigation of the behavior and utility of ERCs provides a basis for articulating specific recommendations for their future use in evaluating assay performance across multiple platforms.
Subscribe to Journal
Get full journal access for 1 year
only $4.92 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
ERCC. Proposed methods for testing and selecting the ERCC external RNA controls. BMC Genomics 6, 150 (2005).
ERCC. The External RNA Controls Consortium: a progress report. Nat. Methods 2, 731–734 (2005).
Hill, A.A. et al. Evaluation of normalization procedures for oligonucleotide array data based on spiked cRNA controls. Genome Biol 2, RESEARCH0055 (2001).
Rajagopalan, D. A comparison of statistical methods for analysis of high density oligonucleotide array data. Bioinformatics 19, 1469–1476 (2003).
Irizarry, R.A. et al. Summaries of Affymetrix GeneChip probe level data. Nucleic Acids Res. 31, e15 (2003).
Irizarry, R.A. et al. Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics 4, 249–264 (2003).
Freudenberg, J., Boriss, H. & Hasenclever, D. Comparison of preprocessing procedures for oligo-nucleotide micro-arrays by parametric bootstrap simulation of spike-in experiments. Methods Inf. Med. 43, 434–438 (2004).
Choe, S.E., Boutros, M., Michelson, A.M., Church, G.M. & Halfon, M.S. Preferred analysis methods for Affymetrix GeneChips revealed by a wholly defined control dataset. Genome Biol. 6, R16 (2005).
Dabney, A.R. & Storey, J.D. A reanalysis of a published Affymetrix GeneChip control dataset. Genome Biol. 7, 401 (2006).
MAQC Consortium. The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements. Nat. Biotechnol. 24, 1151–1161 (2006).
Guo, L. et al. Rat toxicogenomic study reveals analytical consistency across microarray platforms. Nat. Biotechnol. 24, 1162–1169 (2006).
Shippy, R. et al. Using RNA sample titrations to assess microarray platform performance and normalization techniques. Nat. Biotechnol. 24, 1123–1131 (2006).
“Guide to Probe Logarithmic Intensity Error (PLIER) Estimation”, Affymetrix Technical Note, http://www.affymetrix.com/support/technical/technotes/plier_technote.pdf
Microarray Suite User's Guide, Version 5.0, http://www.affymetrix.com/support/technical/manuals.affx
Wu, Z., Irizarry, R.A., Gentleman, R., Murillo, F.M. & Spencer, F. A model based background adjustment for oligonucleotide expression arrays. J. Am. Stat. Assoc. 99, 909–917 (2004).
Li, C. & Wong, W. Model-based analysis of oligonucleotide arrays: expression index computation and outlier detection. Proc. Natl. Acad. Sci. USA 98, 31–36 (2001).
Fang, H., Xie, Q., Boneva, R., Fostel, J., Perkins, R. & Tong, W. Gene expression profile exploration of a large dataset on chronic fatigue syndrome. Pharmacogenomics, 7, 429–440, (2006).
Tong, W. et al. ArrayTrack–supporting toxicogenomic research at the US Food and Drug Administration National Center for Toxicological Research. Environ. Health Perspect. 111, 1819–1826 (2003).
Tong, W. et al. Development of public toxicogenomics software for microarray data management and analysis. Mutat. Res. 549, 241–253 (2004).
Comparison of the correlation coefficients for each assay from the lines fit through the expected versus observed log10 ratios in Figure 4. (DOC 99 kb)
The tERC signal intensity across different RNA samples. (DOC 89 kb)
The effect of normalization methods on the tERC performance behavior across the same RNA samples illustrated in Supplementary Figure 2. (DOC 141 kb)
Observed log10 ratios for the AGL tERCs that are spiked in at intended 1:1 ratios in the Two-Color hybridization samples. (DOC 34 kb)
Correlation Assuming Percent Brain is Changed to mRNA Differences Between in the Samples. (DOC 110 kb)
The cERC signal intensity (y-axis) was compared across the four different RNA samples (A, B, C and D) for the ABI (top graph) and AFX (bottom graph) platforms. (DOC 34 kb)
The effect of normalization method on the sample independency of the cERC signal intensity (y-axis) for the AFX microarray platform. (DOC 66 kb)
Hierarchical cluster analysis for the One-Color AG1 platform based on either the tERC probes (A) or the biological probes (B). (DOC 157 kb)
Full Concentration-Response Curves for tERCs on the Agilent microarray platform. (DOC 267 kb)
Summary of cERC Concentration and tERC Molar Ratio Used for Plotting Concentration-Response Curves in Figure 1. (DOC 52 kb)
Summary of statistical results presented in Figure 3. (DOC 1945 kb)
Summary of statistical results presented in Figure 5. (DOC 39 kb)
Summary of tERC Concentration and Expected Two-Color Ratios for the AGL Platform. (DOC 39 kb)
About this article
Cite this article
Tong, W., Lucas, A., Shippy, R. et al. Evaluation of external RNA controls for the assessment of microarray performance. Nat Biotechnol 24, 1132–1139 (2006). https://doi.org/10.1038/nbt1237
Nature Communications (2019)
Practical determination of LODP (limit of detection for microarray platform) for the evaluation of microarray platforms
Analytical Biochemistry (2019)
Polish Journal of Microbiology (2018)
The challenge of the application of 'omics technologies in chemicals risk assessment: Background and outlook
Regulatory Toxicology and Pharmacology (2017)
Standardising RNA profiling based biomarker application in cancer—The need for robust control of technical variables
Biochimica et Biophysica Acta (BBA) - Reviews on Cancer (2017)