Fundamentals of experimental design for cDNA microarrays
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- 1 December 2002
- journal article
- review article
- Published by Springer Nature in Nature Genetics
- Vol. 32 (S4), 490-495
- https://doi.org/10.1038/ng1031
Abstract
Microarray technology is now widely available and is being applied to address increasingly complex scientific questions. Consequently, there is a greater demand for statistical assessment of the conclusions drawn from microarray experiments. This review discusses fundamental issues of how to design an experiment to ensure that the resulting data are amenable to statistical analysis. The discussion focuses on two-color spotted cDNA microarrays, but many of the same issues apply to single-color gene-expression assays as well.Keywords
This publication has 20 references indexed in Scilit:
- From patterns to pathways: gene expression data analysis comes of ageNature Genetics, 2002
- Microarray data normalization and transformationNature Genetics, 2002
- Variation in gene expression within and among natural populationsNature Genetics, 2002
- Design of studies using DNA microarraysGenetic Epidemiology, 2002
- Genetic Dissection of Transcriptional Regulation in Budding YeastScience, 2002
- Assessing Gene Significance from cDNA Microarray Expression Data via Mixed ModelsJournal of Computational Biology, 2001
- Replicating Effects and BiasesThe American Statistician, 2001
- Experimental design for gene expression microarraysBiostatistics, 2001
- Analysis of Variance for Gene Expression Microarray DataJournal of Computational Biology, 2000
- Mathematical contributions to the theory of evolution.—On a form of spurious correlation which may arise when indices are used in the measurement of organsProceedings of the Royal Society of London, 1897