Integrating statistical approaches in experimental design and data analysis
Part 4. Bioinformatics
4.5. Computational Methods for High-throughput Genetic Analysis: Expression Profiling
Published Online: 15 NOV 2005
Copyright © 2005 John Wiley & Sons, Ltd
Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics
How to Cite
Wit, E. and Khanin, R. 2005. Integrating statistical approaches in experimental design and data analysis. Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics. 4:4.5:50.
- Published Online: 15 NOV 2005
In complex experiments such as microarray studies, the quantity of interest is measured via a long path of intermediate technologies. It is not surprising that the final signal is partially corrupted by the measurement process itself. Statistical design is aimed at assigning the replicates in an optimal way to the conditions of interest. It should be seamlessly integrated with the statistical methods to recover the signal, so that it is possible to evaluate the scientific question of interest most efficiently.
- statistical design;
- optimal design;
- interwoven loop design