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The processing comprises background subtraction and quality refining; in this way structures or scratches on the sample are considered.
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Concerning the background correction methods, most of them (such as those implemented in the lumi package) involve a simple background subtraction and do not significantly improve data quality.
Data sets were highly consistent both after background subtraction and after quantile normalisation of the background subtracted data.
Initial quality control (positive and negative controls), exclusion of manufacturing defects (MSR spots), background subtraction, and intra-array normalization was then performed and the results exported to GeneSpring GX 7.3 (Agilent Technologies).
The second column shows background subtraction: d the image used as the background model, e the frame of interest prior to background subtraction, and f the foreground image.
Image processing, background subtraction, and the construction of an unbiased ratio image are discussed.
The signal values were derived by background subtraction and normalization.
Background subtraction and Gaussian filtering was performed before signal identification.
All spot intensity values were subjected to local background subtraction, secondary antibody alone background subtraction, and normalization relative to total protein intensities.
CT values were determined using the same background subtraction and threshold values for all reactions.
RMA background subtraction and Quantile normalization was used on sample data.
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