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Background  Normalization is an important step for microarray data analysis to minimize biological and technical variations. Choosing a suitable approach can be critical. The default method in GeneChip expression microarray uses a constant factor, the scaling factor ( SF ), for every gene on an array. The  SF  is obtained from a trimmed average signal of the array after excluding the 2% of the probe sets with the highest and the lowest values.    Results  Among the 76 U34A GeneChip experiments, the total signals on each array showed 25.8% variations in terms of the coefficient of variation, although all microarrays were hybridized with the same amount of biotin-labeled cRNA. The 2% of the probe sets with the highest signals that were normally excluded from  SF  calculation accounted for 34% to 54% of the total signals (40.7% ± 4.4%, mean ± sd). In comparison with normalization factors obtained from the median signal or from the mean of the log transformed signal,  SF  showed the greatest variation. The normalization factors obtained from log transformed signals showed least variation.    Conclusions  Eliminating 40% of the signal data during  SF  calculation failed to show any benefit. Normalization factors obtained with log transformed signals performed the best. Thus, it is suggested to use the mean of the logarithm transformed data for normalization, rather than the arithmetic mean of signals in GeneChip gene expression microarrays.

Improving the scaling normalization for high-density oligonucleotide GeneChip expression microarrays.