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We also investigated the results when these data are normalized with the two unsupervised normalization procedures considered above, ISN and QN.
Normalization procedures were performed using R statistical software using Spike-in control intensities to normalize each dataset.
An invariant set normalization procedure performed to normalize the different arrays using DNA-chip analyzer.
Chips were normalized with the quantile normalization procedure.
Hybridization signals were normalized using the scale normalization procedure previously described [ 25].
Data was normalized using a quantile normalization procedure using R (http://www.rproject.org/).org/
Probe intensities were normalized using the quantile normalization procedure (Wu et al. 2004).
Hybridization success was evaluated using flag values, excluding those intensities not equal to 1. Data was normalized using a quantile normalization procedure using R (http://www.r-project.org).org
After the adjustment of background signal using the Plier method, probe intensities were normalized using the quantile normalization procedure with Affymetrix Expression Console software [ 66].
Other than that, thereafter, each subject's image was segmented and normalized using VBM2's normal procedure (segmentation: cross-sectional data, 1 time point per subject).
The microarray data were normalized by a quantile normalization procedure by using the bioconductor package affy, and batch effect was corrected by using the ComBat algorithm [ 28].
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