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Preferred analysis methods for Affymetrix GeneChips. II. An expanded, balanced, wholly-defined spike-in dataset
Qianqian Zhu1, Jeffrey C Miecznikowski, Marc S Halfon
1Department of Biochemistry, State University of New York at Buffalo, Buffalo, NY 14214, USA.
Background:
Concomitant with the rise in the popularity of DNA microarrays has been a surge of proposed methods for the analysis of microarray data. Fully controlled "spike-in" datasets are an invaluable but rare tool for assessing the performance of various methods.
Results:
We generated a new wholly defined Affymetrix spike-in dataset consisting of 18 microarrays. Over 5700 RNAs are spiked in at relative concentrations ranging from 1- to 4-fold, and the arrays from each condition are balanced with respect to both total RNA amount and degree of positive versus negative fold change. We use this new "Platinum Spike" dataset to evaluate microarray analysis routes and contrast the results to those achieved using our earlier Golden Spike dataset.
Conclusions:
We present updated best-route methods for Affymetrix GeneChip analysis and demonstrate that the degree of "imbalance" in gene expression has a significant effect on the performance of these methods.
