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Specifically, key established pathways in lung cancer exhibit higher statistical significance using a dataset normalized with our reference genes relative to normalization without using our reference genes.
where the corrected image intensity is derived from the measured raw image, by subtracting, the average image over the full large dataset, normalized by the standard deviation image of that dataset.
where the corrected image intensity is derived from the measured raw image by subtracting, the average image over the full large dataset, normalized by the standard deviation image of that dataset (dimensionless units are used throughout).
The downloaded SOHO/SEM daily EUV flux is the dataset normalized to 1 AU.
The structural (T1 – MPRAGE) and functional data were coregistered for each participant dataset, normalized into the standard Montreal Neurological Institute space, and then transformed into a common stereotactic space based on Talairach and Tournoux [28].
Results from SAM were compared using the dataset normalized by MAS 5.0 alone, versus the same dataset normalized by MAS 5.0 with scale normalization using the lung- NEPS reference genes represented on the microarray.
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Mean ratios and standard deviations (SDs) for all array elements spotted in triplicate were calculated and the datasets normalized to the median ratio per hybridization.
Processing of the TIFF images from hybridized arrays was performed using TIGR-Spotfinder http://www.tigr.org/software, and the datasets normalized by applying the LOWESS algorithm, using block mode and a smooth parameter of 0.33, available in the TIGR-MIDAS package http://www.tigr.org/software.
For the calculation of each gene's final p-value, an approach described before in [ 20] was used: as the dataset was normalized with two independent normalization methods, two different datasets having different value sets for each gene were produced.
For the 36 cancer datasets generated from Affymetrix microarray platforms, the log2 intensities in each gene expression dataset were normalized using the GC-RMA normalization method (15).
Subsequently, the generated dataset was normalized with two widely used microarray data normalization methods, as there exists no gold standard normalization method, with the scope to decrease the number of possible false positives during the statistical selection step.
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