GSE66592
Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology (RNA-seq_ClonTech)
We present a more extensive and yet precise assessment to elucidate differences and similarities in performance at numerous aspects including signal range, sensitivity to fold-change, and fidelity with TaqMan qRT-PCR. There were three levels of data examined: entire data sets, data derived from gene name annotation oriented subset of 15442 RefSeq genes, and data derived from transcript pattern defined subset of 7034 RefSeq genes.  Our results showed a fair degree of overall correlation between all 6 platforms evaluated; but, to varying degrees, two RNA-seq protocols outperformed three of the microarray platforms in most categories.  Notably, a fourth microarray platform, Agilent, was comparable, or marginally superior, to the RNA-seq protocols within these same assessments.  Furthermore, 3 platforms (Agilent and two RNA-seq methods) demonstrated over 80% concordance with the gold standard TaqMan assay in terms of fold-change accuracy.  Our study suggests that the use of transcript patterns can enhance a number of the observed cross-platform correlations, indicating a potential usefulness for similar evaluations. Overall design: The study assessed differences and similarities in performance at numerous aspects including signal range, sensitivity to fold-change, and fidelity with TaqMan qRT-PCR. There were three levels of data examined: entire data sets, data derived from gene name annotation oriented subset of 15442 RefSeq genes, and data derived from transcript pattern defined subset of 7034 RefSeq genes.