Moreover, studies comparing data originating from different microarray platforms have reported poor inter-platform correlations (Kuo et al, 2002; Tan et al, 2003).
For each stage, gene expression values were collected for three or four individuals on the Agilent Bovine microarray platform, as reported previously [ 59].
For these analyses, we took advantage of two published datasets that used the same Illumina HumanMethylation27 microarray platform and reported a number of methylation quantitative trait loci (mQTL) in lymphoblastoid cell lines (LCLs) [ 33, 34].
However, no comparative and quality control study of microRNA microarray platforms has been reported yet.
Recently, different microarray platforms have been reported to have a good agreement [ 79, 80].
The overlaps of differentially expressed genes across commercially microarray platforms are recently reported to be~80 90 % [ 10, 32, 33].
To further validate our prediction system, we tested our PCT-TC-derived predictors on two other groups of breast cancer patients whose survival and microarray expression data have been published but which utilized different microarray platforms [a Duke University report, using Affymetrix arrays [4], and a University of North Carolina (UNC) report, using cDNA spotted arrays [5]].
Similar estimates of correspondence between RNA-seq and microarrays platforms have been reported in studies of the rat and Candida parapsilosis transcriptomes [ 28, 66].
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].
Reports using different microarray platforms and analysing specific cancer subgroups are finding consensus on subclasses and signatures of the disease with predictive utility.
