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Clustering of the quality scores assigned reveals two major tendencies based on background normalization.
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We thresholded images based on background fluorescence and measured total length of objects above background.
People form their opinions based on backgrounds and experiences.
The signal intensity was background corrected based on the quantile normalization process [ 35, 36] for all microarrays from the entire experiment (under uniform conditions) using data from only perfectly matched oligos.
There were only two studies based on Asian background and one based on African background.
The quantification of individual constituents is based on internal normalization.
In [18] Lambrix and Larocchia proposed a simple concept learning algorithm based on concept normalization.
All results described below are based on RMA normalization of data from each center separately.
The results also varied based on the normalization methods.
There were only five studies based on Caucasian background and no studies on African background.
To process the signals from the array, quantile normalization (WT vs DKO) and PM-GCBG (signal adjustment based on the background with similar GC content) were applied.
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