The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Analysis of Variance for Gene Expression Microarray Data
Abstract
Spotted cDNA microarrays are emerging as a powerful and cost-effective tool for large-scale analysis of gene expression. Microarrays can be used to measure the relative quantities of specific mRNAs in two or more tissue samples for thousands of genes simultaneously. While the power of this technology has been recognized, many open questions remain about appropriate analysis of microarray data. One question is how to make valid estimates of the relative expression for genes that are not biased by ancillary sources of variation. Recognizing that there is inherent "noise" in microarray data, how does one estimate the error variation associated with an estimated change in expression, i.e., how does one construct the error bars? We demonstrate that ANOVA methods can be used to normalize microarray data and provide estimates of changes in gene expression that are corrected for potential confounding effects. This approach establishes a framework for the general analysis and interpretation of microarray data.
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Cites
Cluster analysis and display of genome-wide expression patterns
Eisen, M. B., Spellman, P. T., Brown, P. O., & Botstein, D. (1998) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.95.25.14863 · Cited by 16,184
Efron, B., & Tibshirani, R. (1986) · Statistical Science · doi:10.1214/ss/1177013815 · Cited by 6,033
Cited by
Smyth, G. K. (2004) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1027 · Cited by 11,829
Huber, W., von Heydebreck, A., Sültmann, H., Poustka, A., & Vingron, M. (2002) · Bioinformatics · doi:10.1093/bioinformatics/18.suppl_1.s96 · Cited by 2,440
Capturing Heterogeneity in Gene Expression Studies by Surrogate Variable Analysis
Leek, J. T., & Storey, J. D. (2007) · PLoS Genetics · doi:10.1371/journal.pgen.0030161 · Cited by 1,930
Vaske, C. J., Benz, S. C., Sanborn, J. Z., Earl, D., Szeto, C., Zhu, J., Haussler, D., & Stuart, J. M. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq182 · Cited by 786
Variation in gene expression within and among natural populations
Oleksiak, M. F., Churchill, G. A., & Crawford, D. L. (2002) · Nature Genetics · doi:10.1038/ng983 · Cited by 736
Metadata
- Authors
- Kerr, M. K., Martin, M., & Churchill, G. A.
- Venue
- Journal of Computational Biology
- Publisher
- SAGE Publications
- Published
- 2000-12
- Volume
- 7
- Issue
- 6
- Pages
- 819-837
- ISSN
- 1066-5277 (ISSN-L)
- 1557-8666
- OpenAlex
- W2093017030
- Cited by
- 1,310
- References
- 2
- FWCI
- 26.25
- Type
- journal article
- Language
- en
- Open access
- closed
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