Optimal factorial designs for CDNA microarray experiments

DOI10.1214/07-AOAS144SUPPzbMath1137.62074arXiv0803.3911MaRDI QIDQ2482985

Rahul Mukerjee, Tathagata Banerjee

Publication date: 30 April 2008

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0803.3911

zbMATH Keywords

interactionadmissibilityweighted optimalitysaturated designmain effectaugmented designorthogonal parametrizationbaseline parametrizationdye-swapping

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Optimal statistical designs (62K05) Biochemistry, molecular biology (92C40) Factorial statistical designs (62K15)

Related Items (10)

Selecting baseline designs using a minimum aberration criterion when some two-factor interactions are important ⋮ A systematic construction of compromise designs under baseline parameterization ⋮ Relationship between orthogonal and baseline parameterizations and its applications to design constructions ⋮ Approximate theory-aided robust efficient factorial fractions under baseline parametrization ⋮ Robust multistratum baseline designs ⋮ Compromise designs under baseline parameterization ⋮ Algorithmic search for baseline minimum aberration designs ⋮ Optimal factorial designs for CDNA microarray experiments ⋮ Optimal biased weighing designs and two-level main-effect plans ⋮ Highly efficient factorial designs for cDNA microarray experiments: use of approximate theory together with a step-up step-down procedure

Uses Software

• daMA

Cites Work

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• Optimal factorial designs for CDNA microarray experiments
• DNA Microarray Experiments: Biological and Technological Aspects
• Balanced Factorial Designs for cDNA Microarray Experiments
• Design Considerations for Efficient and Effective Microarray Studies
• Experimental design for gene expression microarrays
• Factorial and time course designs for cDNA microarray experiments
• Near-Optimal Designs for Dual Channel Microarray Studies

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