Biomedical Engineering Reference
In-Depth Information
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Data does not seem comparable to non-amplified data of the same cell type
:One
issue that is critical to the success of any amplification procedure is that all samples
must be treated the same [20, 44]. In order to ensure success, researchers should look
to determine which samples that will be included in the study are the smallest. The
appropriate amplification strategy for that sample should be determined and that method
should be used to treat all samples regardless of whether some samples could be used
without amplification or with fewer rounds of amplification. Sample input amounts should
also be normalized. Most of the amplification procedures have an optimal range of input
material, and will change slightly with the amount of RNA input into the reactions.
When using a two-color array system, it is critical that both samples be treated the
same as well. Thus, if using a reference RNA (such as those available from Stratagene,
Clontech, ArrayIt), this reference RNA must also be amplified. This is a critical step.
Each amplification procedure introduces some inherent bias; however, for good methods
this bias is reproducible. As such, by amplifying both the reference and the experimental
sample, the bias is equally applied to each sample, and when looking at ratiometric data,
it is largely canceled out, greatly improving the reliability and usefulness of the technique.
References
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et al
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7. Eberwine, J., Yeh, H., Miyashiro, K.
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3010-3014. This is the first time that the ability to measure transcript levels from a single cell was
presented. The T7-amplification method is often referred to as Eberwine amplification because of
this paper.
8. Kamme, F., Salunga, R., Yu, J.
et al
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