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Pearson's correlation analysis showed a high level of similarity (coefficient = 0.85) in expression patterns of genes between these two platforms.
As Flurry's Peter Farago rightly argues, though, "the shift in time spent between these two platforms appears to be a signal of disruption".
Between these two platforms, the data indicates that the inkjet system would perform better for the transcriptional profiling of 100 ng total RNA samples for neuroscience studies.
A circular impression lies between these two platforms, which is all that remains of another platform, of a different type, that must have stood there.
Even though our comparison with arrays from Agilent was based on entirely different elutriations, we obtained a high degree of correlation between these two platforms (r = 0.92).
A difference of 1.8 – 91.4% was seen in samples between these two platforms (Additional file 4).
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The difficult task of matching probes from the Affymetrix gene chips with cDNA arrays was illustrative of the disparities between the probe sets within these two platforms.
Further, results were collated to determine the level of shared detection and abundance of specific miRNAs between these three platforms.
The volcano plots (plotting estimate of treatment effects against the negative log of the p-value) demonstrate that the number of significant differentially expressed genes identified varies greatly between these three platforms.
We then examined the concordance of DNA methylation at each of these loci between the two platforms, and found a high correlation coefficient in all cases (CALCA: 0.94, EPHA3: 0.95, KIT: 0.95, SLC5A8: 0.86), lending further support to our initial GoldenGate-based DNA methylation screen.
The comparison results of these five platforms between SNPTracker and LiftRsNumber are shown in Table S3, Table S4, Table S5, Table S6, and Table S7.
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