Additionally, many different platforms exist for both microarray and qPCR analyses that have led to debate over which methods produce the most accurate measurements of gene expression (6- 12).
It is generally understood that differences between platforms exist.
This bias does not exist for microarray platforms, which uses a single or set of diagnostic probes to assess expression levels.
Several reports and reviews have pointed out the differences that exist between different microarray platforms that are in use for miRNA profiling, RT-PCR techniques, and different miRNA isolation kits in today's market from different vendors that can interfere with our ability in comparing our results with other reports[67].
Generally, consistent model performance exists across different microarray platforms for multiple-class prediction, both for the complete set of samples and for those with different RHI scores, regardless of the ACs, probe-mapping methods, and classification algorithms.
Currently, there exist three major DNA microarray platforms: spotted cDNA array [4], spotted oligo array (e.g., Agilent microarray [5]), and in situ synthesized oligo array (e.g., Affymetrix gene chip [6] and Nimblegen array [7]).
Sequences that appear to be present in several probe designs of microarray platforms (table 1) indicate that no design rules exist today to preclude them.
Although good reproducibility exist within RT-qPCR profiling platforms, the correlation with microarray platforms is often not high, as reported by Chen et al. [ 26].
Since the tomato genome sequence is currently incomplete and the microarray platforms for this species do not feature most of the loci predicted to exist [ 5- 7], genetic studies have focused on the analysis of particular loci and segregating populations.
This indicates that 95% of the transcripts in the 44 K microarray platform could be validated by mRNA-Seq.
