What is the best reference RNA? And other questions regarding the design and analysis of two-color microarray experiments.

The reference design is a practical and popular choice for microarray studies using two-color platforms. In the reference design, the reference RNA uses half of all array resources, leading investigators to ask: What is the best reference RNA? We propose a novel method for evaluating reference RNAs and present the results of an experiment that was specially designed to evaluate three common choices of reference RNA. We found no compelling evidence in favor of any particular reference. In particular, a commercial reference showed no advantage in our data. Our experimental design also enabled a new way to test the effectiveness of pre-processing methods for two-color arrays. Our results favor using intensity normalization and foregoing background subtraction. Finally, we evaluate the sensitivity and specificity of data quality filters, and we propose a new filter that can be applied to any experimental design and does not rely on replicate hybridizations.

[1]  The External Rna Controls Consortium.  The External RNA Controls Consortium: a progress report , 2005 .

[2]  M. Kathleen Kerr,et al.  Linear Models for Microarray Data Analysis: Hidden Similarities and Differences , 2003, J. Comput. Biol..

[3]  M Kathleen Kerr,et al.  Design considerations for efficient and effective microarray studies. , 2003, Biometrics.

[4]  G. Churchill,et al.  Experimental design for gene expression microarrays. , 2001, Biostatistics.

[5]  Weida Tong,et al.  Evaluation of external RNA controls for the assessment of microarray performance , 2006, Nature Biotechnology.

[6]  S. Dudoit,et al.  Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation. , 2002, Nucleic acids research.

[7]  David Botstein,et al.  BMC Genomics BioMed Central Methodology article Universal Reference RNA as a standard for microarray experiments , 2004 .

[8]  Jerry Li,et al.  Within the fold: assessing differential expression measures and reproducibility in microarray assays , 2002, Genome Biology.

[9]  T. Speed,et al.  Design issues for cDNA microarray experiments , 2002, Nature Reviews Genetics.

[10]  John Quackenbush.  Microarray data normalization and transformation , 2002, Nature Genetics.

[11]  Chunlian Zhang,et al.  Universal mouse reference RNA derived from neonatal mice. , 2004, BioTechniques.

[12]  Tao Han,et al.  Microarray scanner calibration curves: characteristics and implications , 2005, BMC Bioinformatics.

[13]  D. Allison,et al.  Towards sound epistemological foundations of statistical methods for high-dimensional biology , 2004, Nature Genetics.

[14]  S. Sealfon,et al.  Accuracy and calibration of commercial oligonucleotide and custom cDNA microarrays. , 2002, Nucleic acids research.

[15]  John Aach,et al.  Measuring absolute expression with microarrays with a calibrated reference sample and an extended signal intensity range , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[16]  External Rna Controls Consortium,et al.  Proposed methods for testing and selecting the ERCC external RNA controls , 2005 .

[17]  Roland Eils,et al.  Reliability of gene expression ratios for cDNA microarrays in multiconditional experiments with a reference design. , 2004, Nucleic acids research.

[18]  X. Cui,et al.  Transformations for cDNA Microarray Data , 2003, Statistical applications in genetics and molecular biology.

[19]  Members of the Complex Trait Consortium,et al.  Standardizing global gene expression analysis between laboratories and across platforms , 2005 .

[20]  A. Vanmeter,et al.  Development of a new reference standard for microarray experiments. , 2004, BioTechniques.

[21]  L. Qin,et al.  Empirical evaluation of data transformations and ranking statistics for microarray analysis. , 2004, Nucleic acids research.

[22]  L. Lin,et al.  A concordance correlation coefficient to evaluate reproducibility. , 1989, Biometrics.