Normalization for triple-target microarray experiments.
BACKGROUND
Most microarray studies are made using labelling with one or two dyes which allows the hybridization of one or two samples on the same slide. In such experiments, the most frequently used dyes are Cy3 and Cy5. Recent improvements in the technology (dye-labelling, scanner and, image analysis) allow hybridization up to four samples simultaneously. The two additional dyes are Alexa488 and Alexa494. The triple-target or four-target technology is very promising, since it allows more flexibility in the design of experiments, an increase in the statistical power when comparing gene expressions induced by different conditions and a scaled down number of slides. However, there have been few methods proposed for statistical analysis of such data. Moreover the lowess correction of the global dye effect is available for only two-color experiments, and even if its application can be derived, it does not allow simultaneous correction of the raw data.


RESULTS
We propose a two-step normalization procedure for triple-target experiments. First the dye bleeding is evaluated and corrected if necessary. Then the signal in each channel is normalized using a generalized lowess procedure to correct a global dye bias. The normalization procedure is validated using triple-self experiments and by comparing the results of triple-target and two-color experiments. Although the focus is on triple-target microarrays, the proposed method can be used to normalize p differently labelled targets co-hybridized on a same array, for any value of p greater than 2.


CONCLUSIONS
The proposed normalization procedure is effective: the technical biases are reduced, the number of false positives is under control in the analysis of differentially expressed genes, and the triple-target experiments are more powerful than the corresponding two-color experiments. There is room for improving the microarray experiments by simultaneously hybridizing more than two samples.
Martin-Magniette
Marie-Laure
ML
UMR AgroParisTech-INRA MIA 518, 75231 Paris Cedex05, France. marie_laure.martin@agroparistech.fr
Aubert
Julie
J
Bar-Hen
Avner
A
Elftieh
Samira
S
Magniette
Frederic
F
Renou
Jean-Pierre
JP
Daudin
Jean-Jacques
JJ
D017360:Arabidopsis / Q000235:genetics; D016477:Artifacts; D002138:Calibration; D002232:Carbocyanines / Q000032:analysis; D005456:Fluorescent Dyes / Q000032:analysis; D020869:Gene Expression Profiling / Q000379:methods / Q000592:standards*; D017343:Genes, Plant; D016247:Information Storage and Retrieval; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D009930:Organic Chemicals / Q000032:analysis; D012015:Reference Standards; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D017422:Sequence Analysis, DNA
C417664:Alexa594; D002232:Carbocyanines; D005456:Fluorescent Dyes; D009930:Organic Chemicals; C089187:cyanine dye 3; C085321:cyanine dye 5