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Fold changes observed through microarrays are small.
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The high manufacturability of semiconductors and their adaptability to inexpensive electrochemical microarray readers, which are small and field deployable, make these assays much more powerful than simple Real Time-PCR systems.
Though the magnitudes of microarray data are smaller, it can sensitively discriminate the direction of transcriptional changes (up-regulation or down-regulation) for a large number of genes simultaneously.
We show that even when gene expression differences between groups are small, several microarray platforms are able to consistently detect them.
In addition, the targets on these microarrays are much smaller in size as compared to BAC clones with an average insert size of 170 kb, thereby theoretically allowing the detection of aberrations below 100 kb.
Third, the sample size used in the microarray experiment is small.
YbgF was stained strongly in immunoblot assay while the RASIgG in microarray assay was small.
However, often the sample size for each individual microarray experiment is small.
First, the sample size in microarray analysis was small in each group.
In particular, the number of samples used in the microarray experiment is small.
The moderated t-test is based on empirical Bayes analysis, and is equivalent to shrinkage (or expansion) of the estimated sample variances towards a pooled estimate, resulting in more stable inference when the number of microarray experiments is small.
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