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Furthermore, although URSA is trained on data from the single most popular microarray platform, it is able to make tissue/cell-type predictions (without re-training) for samples measured by other microarray platforms and even by next-generation RNA sequencing.
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Finally, similar analyses could be performed on other microarray platforms in the future to allow a cross-platform comparison.
This is likely caused by the increased variance caused by the large linear dynamic range (>10,000-fold in our experiments) and increased sensitivity of the ABI1700 chemiluminescent system compared to other microarray platforms.
The same approach can also be applied to other microarray platforms to allow better evaluation of the potential impact of these polymorphisms on microarray expression data.
This may have caused a disagreement with other microarray platforms.
The currently proposed method to predict 3' UTR extensions may be easily adapted to other microarray platforms.
Additional RNA aliquots could be stored for later processing using other microarray platforms.
Similar to other microarray platforms, different probes on an Affymetrix tiling array usually behave differently.
We also repeated this double-blind study for other microarray platforms: hgu133a, hgu95v2 and hugene1.0st.
Filtering for the other microarray platforms are described in Kuo et al. [ 6].
Provided that large enough datasets of different tissues are available, this method can easily be applied to other microarray platforms.
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