Fundamentals of experimental design for cdna microarrays

Nature Genetics

Volumn 32, Issue 4S, 2002, Pages 490-495

  Churchill, Gary A ^a  

^a JACKSON LABORATORY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPLEMENTARY DNA;

ACCURACY; COMPARATIVE STUDY; DNA MICROARRAY; EXPERIMENTAL DESIGN; GENE EXPRESSION; GENE TECHNOLOGY; HUMAN; HYBRIDIZATION; PRIORITY JOURNAL; REVIEW; STATISTICAL ANALYSIS; VALIDATION PROCESS;

ANIMALS; DNA, COMPLEMENTARY; GENE EXPRESSION; GENE EXPRESSION PROFILING; MICE; MODELS, BIOLOGICAL; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; REFERENCE STANDARDS; REPRODUCIBILITY OF RESULTS; RESEARCH DESIGN; STATISTICS;

EID: 0036900895     PISSN: 10614036     EISSN: 15461718     Source Type: Journal    
DOI: 10.1038/ng1031     Document Type: Review

References (22)

1. Oleksiak, M.F., Churchill, G.A. and Crawford, D.L. Variation in gene expression within and among natural populations. Nature Genet. 32, 261-266 (2002).
2. Lee, M.T., Kuo, F.C., Whitmore, G.A. and Sklar, J. Importance of replication in microarray gene expression studies: Statistical methods and evidence from repetitive cDNA hybridizations. Proc. Natl Acad. Sci. USA 97, 9834-9839 (2000).
3. Rosenbaum, P.R. Replicating effects and biases. Am. Stat. 55, 223-227 (2001).
4. Cox, D.R. The Design of Experiments (Wiley, NY, 1958).
5. Kerr, M.K. and Churchill, G.A. Biostatistics 2, 183-201 (2001).
6. Yang, Y.H. and Speed, T.P. Nature Rev. Genet. 3, 579-588 (2002).
7. Kerr, M.K. and Churchill, G.A. Statistical design and the analysis of gene expression microarray data. Genet. Res. 77, 123-128 (2001).
8. Brem, R.B., Yvert, G., Clinton, R. and Kruglyak, L. Genetic dissection of transcriptional regulation in budding yeast. Science 296, 752-755 (2002).
9. Jin, W. et al. The contributions of sex, genotype and age to transcriptional variance in Drosophila melanogaster. Nature Genet. 29, 389-395 (2001).
10. Simon, R., Radmacher, M.D. and Dobbin, K. Design of studies using DNA microarrays. Genet. Epidemiol. 23, 21-36 (2002).
11. Quackenbush, J. Microarray data normalization and transformation. Nature Genet. 32, 496-501 (2002).
12. Yang, Y.H. et al. Normalization for cDNA microarray data: A robust composite method addressing single and multiple slide systematic variation. Nucleic Acids Res. 30, e15 (2002).
13. Tanner, J. Fallacy of per-weight and per-surface area standards, and their relation to spurious correlation. Appl. Physiol. 2, 1-15 (1949).
14. Pearson, K. Spurious correlation between indices. Proc. R. Soc. Lond. 60, 489 (1897).
15. Fisher, R.A. The Design of Experiments6th edn (Oliver and Boyd, London, 1951).
16. Slonim, D.K. From patterns to pathways: Gene expression data analysis comes of age. Nature Genet. 32, 502-508 (2002).
17. Kerr, M.K., Martin, M. and Churchill, G.A. Analysis of variance for gene expression microarray data. J. Comput. Biol. 7, 819-837 (2000).
18. Wolfinger, R.D. et al. Assessing gene significance from cDNA microarray expression data via mixed models. J. Comput. Biol. 8, 625-637 (2001).
19. Pritchard, C.C., Hsu, L., Delrow, J. and Nelson, P.S. Project normal: Defining normal variance in mouse gene expression. Proc. Natl Acad. Sci.USA 98, 13266-13271 (2001).
20. Callow, M.J. et al. Microarray expression profiling identifies genes with altered expression in HDL-deficient mice. Genome Res. 10, 2022-2029 (2000).
21. Kerr, M.K. et al. Statistical analysis of a gene expression microarray experiment with replication. Stat. Sinica12, 203-218 (2002).
22. Churchill, G.A. and Oliver, B. Sex, flies and microarrays. Nature Genet. 29, 355-356 (2001).