Experimental design for gene expression microarrays
- PMID: 12933549
- DOI: 10.1093/biostatistics/2.2.183
Experimental design for gene expression microarrays
Abstract
We examine experimental design issues arising with gene expression microarray technology. Microarray experiments have multiple sources of variation, and experimental plans should ensure that effects of interest are not confounded with ancillary effects. A commonly used design is shown to violate this principle and to be generally inefficient. We explore the connection between microarray designs and classical block design and use a family of ANOVA models as a guide to choosing a design. We combine principles of good design and A-optimality to give a general set of recommendations for design with microarrays. These recommendations are illustrated in detail for one kind of experimental objective, where we also give the results of a computer search for good designs.
Similar articles
-
Factorial and time course designs for cDNA microarray experiments.Biostatistics. 2004 Jan;5(1):89-111. doi: 10.1093/biostatistics/5.1.89. Biostatistics. 2004. PMID: 14744830
-
Optimal designs for 2-color microarray experiments.Biostatistics. 2009 Jul;10(3):561-74. doi: 10.1093/biostatistics/kxp012. Epub 2009 Apr 28. Biostatistics. 2009. PMID: 19401503
-
Technology Insight: tuning into the genetic orchestra using microarrays--limitations of DNA microarrays in clinical practice.Nat Clin Pract Oncol. 2006 Sep;3(9):501-16. doi: 10.1038/ncponc0587. Nat Clin Pract Oncol. 2006. PMID: 16955089 Review.
-
Assessing statistical precision, power, and robustness of alternative experimental designs for two color microarray platforms based on mixed effects models.Vet Immunol Immunopathol. 2005 May 15;105(3-4):175-86. doi: 10.1016/j.vetimm.2005.02.002. Vet Immunol Immunopathol. 2005. PMID: 15808299
-
Review of microarray experimental design strategies for genetical genomics studies.Physiol Genomics. 2006 Dec 13;28(1):15-23. doi: 10.1152/physiolgenomics.00106.2006. Epub 2006 Sep 19. Physiol Genomics. 2006. PMID: 16985008 Review.
Cited by
-
Different gene expression profiles in normo- and dyslipidemic men after fish oil supplementation: results from a randomized controlled trial.Lipids Health Dis. 2012 Aug 29;11:105. doi: 10.1186/1476-511X-11-105. Lipids Health Dis. 2012. PMID: 22929118 Free PMC article. Clinical Trial.
-
Methods for genome-wide analysis of gene expression changes in polyploids.Methods Enzymol. 2005;395:570-96. doi: 10.1016/S0076-6879(05)95030-1. Methods Enzymol. 2005. PMID: 15865985 Free PMC article.
-
The simple classification of multiple cancer types using a small number of significant genes.Mol Diagn Ther. 2007;11(4):265-75. doi: 10.1007/BF03256248. Mol Diagn Ther. 2007. PMID: 17705581
-
The Thermotoga maritima phenotype is impacted by syntrophic interaction with Methanococcus jannaschii in hyperthermophilic coculture.Appl Environ Microbiol. 2006 Jan;72(1):811-8. doi: 10.1128/AEM.72.1.811-818.2006. Appl Environ Microbiol. 2006. PMID: 16391122 Free PMC article.
-
RNA-seq: technical variability and sampling.BMC Genomics. 2011 Jun 6;12:293. doi: 10.1186/1471-2164-12-293. BMC Genomics. 2011. PMID: 21645359 Free PMC article.
LinkOut - more resources
Full Text Sources
Other Literature Sources