Preferred analysis methods for Affymetrix GeneChips. II. An expanded, balanced, wholly-defined spike-in dataset.
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.
Zhu
Qianqian
Q
Department of Biochemistry, State University of New York at Buffalo, Buffalo, NY 14214, USA.
Miecznikowski
Jeffrey C
JC
Halfon
Marc S
MS
D030541:Databases, Genetic; D020869:Gene Expression Profiling; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D012313:RNA / Q000235:genetics; D013223:Statistics as Topic / Q000379:methods*
D012313:RNA