Performance comparison of one-color and two-color platforms within the Microarray Quality Control (MAQC) project

Abstract

Microarray-based expression profiling experiments typically use either a one-color or a two-color design to measure mRNA abundance. The validity of each approach has been amply demonstrated. Here we provide a simultaneous comparison of results from one- and two-color labeling designs, using two independent RNA samples from the Microarray Quality Control (MAQC) project, tested on each of three different microarray platforms. The data were evaluated in terms of reproducibility, specificity, sensitivity and accuracy to determine if the two approaches provide comparable results. For each of the three microarray platforms tested, the results show good agreement with high correlation coefficients and high concordance of differentially expressed gene lists within each platform. Cumulatively, these comparisons indicate that data quality is essentially equivalent between the one- and two-color approaches and strongly suggest that this variable need not be a primary factor in decisions regarding experimental microarray design.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Figure 1: Volcano plots depicting estimated fold change (log2, x-axis) and statistical significance (−log10 P value, y-axis).
Figure 2: Comparison of log2 fold-change estimate results from three different modeling approaches for the three different platforms.
Figure 3: Comparison of negative log10 P-value estimate results from three different modeling approaches for the three different platforms.
Figure 4: Comparison of Agilent one-color and two-color data with TaqMan assay data.

References

  1. 1

    Fodor, S.P. et al. Light-directed, spatially addressable parallel chemical synthesis. Science 251, 767–773 (1991).

  2. 2

    Fodor, S.P. et al. Multiplexed biochemical assays with biological chips. Nature 364, 555–556 (1993).

  3. 3

    Schena, M. et al. Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science 270, 467–470 (1995).

  4. 4

    Churchill, G.A. Fundamentals of experimental design for cDNA microarrays. Nat. Genet. 32, Suppl. 490–494 (2002).

  5. 5

    Li, J., Pankratz, M. & Johnson, J. Differential gene expression patterns revealed by oligonucleotide versus long cDNA arrays. Toxicol. Sci. 69, 383–390 (2002).

  6. 6

    Tan, P. et al. Evaluation of gene expression measurements from commercial platforms. Nucleic Acids Res. 31, 5676–5684 (2003).

  7. 7

    Dobbin, K.K. et al. Interlaboratory comparability study of cancer gene expression analysis using oligonucleotide microarrays. Clin. Cancer Res. 11, 565–572 (2005).

  8. 8

    Irizarry, R.A. et al. Multiple-laboratory comparison of microarray platforms. Nat. Methods 2, 345–349 (2005).

  9. 9

    Larkin, J.E., Frank, B.C., Gavras, H., Sultana, R. & Quackenbush, J. Independence and reproducibility across microarray platforms. Nat. Methods 2, 337–343 (2005).

  10. 10

    Kuo, W.P. et al. A sequence-oriented comparison of gene expression measurements across different hybridization-based technologies. Nat. Biotechnol. 24, 832–840 (2006).

  11. 11

    Järvinen, A-K. et al. Are data from different gene expression microarray platforms comparable? Genomics 83, 1164–1168 (2004).

  12. 12

    de Reynies, A. et al. Comparison of the latest commercial short and long oligonucleotide microarray technologies. BMC Genomics 7, 51 (2006).

  13. 13

    Wang, Y. et al. Large scale real-time PCR validation on gene expression measurements from two commercial long-oligonucleotide microarrays. BMC Genomics 7, 59 (2006).

  14. 14

    Bammler, T. et al. Standardizing global gene expression analysis between laboratories and across platforms. Nat. Methods 2, 351–356 (2005).

  15. 15

    MAQC Consortium. The MicroArray Quality Control (MAQC) project shows inter- and intramolecular reproducibility of gene expression measurements. Nat. Biotechnol. 24, 1151–1161 (2006).

  16. 16

    Canales, R.D. et al. Evaluation of DNA microarray results with quantitative gene expression platforms. Nat. Biotechnol. 24, 1115–1122 (2006).

  17. 17

    Guo, Y. et al. Genomic analysis of anti-hepatitis B virus (HBV) activity by small interfering RNA and lamivudine in stable HBV-producing cells. J. Virol. 79, 14392–14403 (2005).

  18. 18

    Barczak, A. Spotted long oligonucleotide arrays for human gene expression analysis. Genome Res. 13, 1175–1785 (2003).

  19. 19

    Shi, L. et al. Cross-platform comparability of microarray technology: intra-platform consistency and appropriate data analysis procedures are essential. BMC Bioinformatics 6 Suppl. 2, S12 (2005).

  20. 20

    Tong, W. et al. Development of public toxicogenomics software for microarray data management and analysis. Mutat. Res. 549, 241–253 (2004).

  21. 21

    Wolfinger, R.D. et al. Assessing gene significance from cDNA microarray data via mixed models. J. Comput. Biol. 8, 625–637 (2001).

  22. 22

    Jin, W., Riley, R., Wolfinger, R.D., White, K.P, Passador-Gurgel, G. & Gibson G. Contributions of sex, genotype and age to transcriptional variance in Drosophila melanogaster. Nat. Genet. 29, 389–395 (2001).

  23. 23

    Chu, T-M., Deng, S., Wolfinger, R.D., Paules, R.S. & Hamadeh, H.K. Cross-site comparison of gene expression data reveals high similarity. Environ. Health Perspect. 112, 449–455 (2004).

  24. 24

    Chu, T-M., Deng, S. & Wolfinger, R.D. Modeling Affymetrix data at the probe level. in DNA microarray and statistical genomics techniques: Design, analysis, and interpretation of experiment. (eds. Edwards, J.W., Beasley, T.M., Page, G.P. and Allison, D.B.) 197–222 (Chapman & Hall/CRC, Taylor & Francis Group, Boca Raton, FL, 2006).

Download references

Acknowledgements

The authors thank the MicroArray Quality Control (MAQC) consortium for generating the large data sets used in this study. E.K.L. and P.H. acknowledge the Advanced Technology Program of the National Institute of Standards and Technology, whose generous support provided partial funding of this research (70NANB2H3009).

Author information

Correspondence to Tucker A Patterson.

Ethics declarations

Competing interests

S.B.F.-S., P.J.C. and L.Z. declare competing financial interests. While engaged in this research project, they were employed by two separate companies that manufacture microarrays. These two companies provided two of the three platforms used in this study.

Supplementary information

Supplementary Fig. 1

Example scatter plot matrices from each platform (PDF 114 kb)

Supplementary Fig. 2

Comparison of B/A ratios for Agilent one-color and two-color designs (Site 1) (PDF 115 kb)

Supplementary Fig. 3

Comparison of the normalization procedures on two-color TeleChem data: Lowess_Medium Scaling (LO_MS) versus Medium Scaling_Lowess (MS_LO) (PDF 19 kb)

Rights and permissions

Reprints and Permissions

About this article

Further reading