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Semilinear high-dimensional model for normalization of microarray data: a theoretical analysis and partial consistency; Comment.

Article Excerpt
I congratulate the authors for this excellent and timely work. Publications in microarray data analysis to date have concentrated on methodological issues, including the critical step of normalization as the authors have addressed in this article, among many others. There are few articles that deal with the theoretical aspect of the statistical approaches, making the present article a welcome and novel contribution to the field. Similar models to the authors' model (1),

[Y.sub.gi] = [[alpha].sub.g] + [[beta].sub.r.sub.gi] + [[gamma].sub.c.sub.gi] + m([X.sub.gi]) + [[epsilon].sub.gi],

have been proposed and used in the microarray data analysis. Here [[alpha].sub.g] is the treatment effect associated with the gth gene, [r.sub.gi] and [c.sub.gi] are the row and column of print-tip block where the gth gene of the ith replication resides, [beta]...

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