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Open AccessJournal ArticleDOI

Optimal factorial designs for cDNA microarray experiments

TLDR
In this paper, the authors consider cDNA microarray experiments when the cell populations have a factorial structure, and investigate the problem of their optimal designing under a baseline parametrization where the objects of interest differ from those under the more common orthogonal parameter.
Abstract
We consider cDNA microarray experiments when the cell populations have a factorial structure, and investigate the problem of their optimal designing under a baseline parametrization where the objects of interest differ from those under the more common orthogonal parametrization. First, analytical results are given for the $2\times 2$ factorial. Since practical applications often involve a more complex factorial structure, we next explore general factorials and obtain a collection of optimal designs in the saturated, that is, most economic, case. This, in turn, is seen to yield an approach for finding optimal or efficient designs in the practically more important nearly saturated cases. Thereafter, the findings are extended to the more intricate situation where the underlying model incorporates dye-coloring effects, and the role of dye-swapping is critically examined.

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Citations
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Journal ArticleDOI

Experiments: Planning, Analysis, and Parameter Design Optimization

TL;DR: This work discusses the practice of problem solving, testing hypotheses about statistical parameters, calculating and interpreting confidence limits, tolerance limits and prediction limits, and setting up and interpreting control charts.
Journal ArticleDOI

Best practices for hybridization design in two-colour microarray analysis

TL;DR: An overview of the different classes of hybridization designs is provided, discussing their advantages and limitations, and the current trends in the use of different hybridization design types in contemporary research are illustrated.
Journal ArticleDOI

Optimal fractions of two-level factorials under a baseline parameterization

TL;DR: In this paper, two-level fractional factorial designs are considered under a baseline parameterization and the criterion of minimum aberration is formulated in this context and optimal designs under this criterion are investigated.
Journal ArticleDOI

General weighted optimality of designed experiments

TL;DR: In this article, a general theory for weighted optimality, allowing precise design selection according to expressed relative interest in different functions in the estimation space, is developed, and the results are applied to solve the $A$-optimal design problem for baseline factorial effects in unblocked experiments.
Journal ArticleDOI

Optimal Biased Weighing Designs and Two-Level Main-Effect Plans

TL;DR: In this paper, the authors considered the problem of optimal biased chemical and spring balance weights for the case N ≡ 0 (mod 4), where N is the run size, and showed that for all p ≥ 0, there is a Φ p -optimal estimator for this problem.
References
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Journal Article

Designing two-level fractional factorial experiments in blocks of size two

P. C. Wang
- 01 Jan 2004 - 
TL;DR: Several assignment rules are suggested for designing good experiments to deal with the trade-off between run-size reduction and the possibly negligible effects in two-level factorial experiments.
Journal ArticleDOI

Balanced Factorial Designs for cDNA Microarray Experiments

TL;DR: The paper provides a systematic method of deriving designs for microarray experiments as opposed to algorithmic and ad-hoc methods and generalizes several of the microarray designs given recently in the literature.

The relationship between optimal designs for microarray and paired comparison experiments

TL;DR: In this article, a multi-factor paired comparison model for two-color microarray experiments is presented, which is structurally similar to linear models for paired comparisons so that essentially the same designs are optimal in both settings.
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