Array comparative genomic hybridization (aCGH) technology is commonly used to estimate genome-wide copy-number variation and to evaluate associations between copy number and disease. Although aCGH technology is well developed and there are numerous algorithms available for estimating copy number, little attention has been paid to the important issue of the statistical experimental design. Herein, we review classical statistical experimental designs and discuss their relevance to aCGH technology as well as their importance for downstream statistical analyses. Furthermore, we provide experimental design guidance for various study objectives.
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