Functional Genomic Dose-Response Experiments
In the first part of the book, we discussed different aspects of the analysis of dose-response data such as estimation, inference, and modeling. In the second part of the book, we focus on dose-response microarray experiments. Within the microarray setting, a dose-response experiment has the same structure as described in Part I of the book. The response is the gene expression at a certain dose level. The role of functional genomics, particularly in this setting, is to find indications of both safety and efficacy before the drug is administrated to patients. In Chap. 5, we give an overview about dose-response microarray experiments and their data structure.
KeywordsDose Level Isotonic Regression Gene Selection Method Order Alternative Squamous Carcinoma Cell Line
- Affymetrix GeneChip. (2004). Expression analysis technical manual, Rev.4. Santa Clara: Affymetrix.Google Scholar
- Amaratunga, D. & Cabrera, J. (2004). Exploration and Analysis of DNA Microarray and Protein Array Data, Hoboken, NJ, Wiley-Interscience-John Wiley and Sons, Inc.Google Scholar
- Bolstad, B. M., Irizarry, R. A., Astrand, M., & Speed, T. P. (2002). A comparison of normalization methods for high density oligonucleotide array data based on bias and variance. Bioinformatics, 19, 185–193.Google Scholar
- Chuang-Stein, C., & Agresti, A. (1997). Tutorial in biostatistics: A review of tests for detecting a monotone dose-response relationship with ordinal response data. Statistics in Medicine, 16, 2599–2618.Google Scholar
- Dunnett, C. W. (1955). A multiple comparison procedure for comparing several treatments with a control. JASA, 50, 1096–1121.Google Scholar
- Goehlmann, H., & Talloen, W. (2009). Gene expression studies using Affymetrix microarrays. Boca Raton: Chapman & Hall/CRC.Google Scholar
- Hubbell, E., Liu, W. M., & Mei. R. (2002) Robust estimators for expression analysis. Bioinformatics, 18(12), 1585–1592.Google Scholar
- Liu, T., Lin, N., Shi, N., & Zhang, B. (2009a). Order-restricted information criterion-based clustering algorithm. Reference manual. http://cran.r-project.org/web/ packages/ORIClust/.
- Peddada, S., Lobenhofer, E. K., Li, L., Afshari, C. A., Weinberg, C. R., & Umbach, D. M. (2003). Gene selection and clustering for time-course and dose-response microarray experimants using order-restricted inference. Bioinformatics, 19(7), 834–841.Google Scholar
- Simmons, S. J., & Peddada, S. (2007). Order-restricted inference for ordered gene expresion (ORIOGEN) data under heteroscedastic variances. Bioinformation, 1(10), 414–419.Google Scholar
- Robertson, T., Wright, F. T., & Dykstra, R. L. (1988). Order restricted statistical inference. New York: Wiley.Google Scholar
- Ruberg, S. J. (1995a). Dose response studies. I. Some design considerations. Journal of Biopharmaceutical Statistics, 5(1), 1–14.Google Scholar
- Ruberg, S. J. (1995b) Dose response studies. II. Analysis and interpretation. Journal of Biopharmaceutical Statistics, 5(1), 15–42.Google Scholar