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For consistency, all files were normalized to 26 dBov using the ITU-T P.56 voltmeter [52].
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All CEL files were normalized by gcRMA (Robust Multichip Average) methods (Wu and Irizarry, 2004) and we selected genes with expression levels changed more than 2 times that passed the two-way ANOVA test.
The CEL-files from all three tissues (18 files) were normalized together to allow for comparison of all expression values.
The input files were normalized with full quantile normalization [95].
Raw CEL files were normalized with RMA, and the normalized expression values were extracted.
For clustering analyses, results files were normalized with DNMAD (Diagnosis and Normalization for MicroArray Data) [ 43] using print-tip loess.
The twenty-seven microarray data files were normalized against each other using quantile normalization [ 41].
Gene expression values from the CEL files were normalized by use of the standard quantile normalization method in RMA [ 20].
The raw CEL files were normalized using the RMA background correction with quantile normalization, log base 2 transformation and mean probe-set summarization with adjustment for GC content.
Cell files were normalized using the Partek Genomics Suite (RMA background correction, quantile normalization, median polishing).
For Bioinformatics analysis, Affymetrix CEL files were normalized using the Robust Multi-array Average (RMA) algorithm with quantile normalization, background correction, and median scaling.
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