Exact(1)
Accurate microarray quantification is best realized when there is a linear relationship between fluorescence and RNA concentration.
Similar(59)
The initial fundamental concept and limitation to be grasped is that with current microarray technology, quantification is relative not absolute.
For example, the relative ranking based on the magnitude of fold differences, as predicted by microarray and qPCR quantification, is in general agreement within and between the two groups of candidate genes.
Nevertheless, absolute qPCR has the potential to extend gene expression analysis beyond what is possible with microarray analysis, based upon the innate capability to overcome two of the greatest limitations of microarray quantification, which are limited sensitivity and lack of absolute scale [ 4].
From our experience in analyzing microarray data, we believe the key to more accurate and effective expression quantification is to establish an appropriate statistical model.
Quantification is shown in.
Objective quantification is optimal.
Corresponding quantification is shown.
A possible source of higher variation relative to the reconstitution experiments was that microarrays and FACS based quantification were run on the same individual, but on different preparations of the bulk tissue such that variation in the cellular composition of the sectioned tissue per individual may have added to the experimental noise.
Spot detection, mean signals, mean local background intensities, image segmentation, and signal quantification were determined for the microarray images using the Array-Pro Analyzer 4.0 software (Media Cybernetics, L.P).
Image acquisition and initial array quantification were performed using the Affymetrix Microarray Suite Version 5.0.
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