Several methods were developed for correlation analysis between the datasets of different type, such as mRNA and proteomics [ 18, 43- 46].
The Bradley-Blackwood F test also revealed a highly significant difference (p < 0.0001) between the datasets of the same amplification method.
The Bradley-Blackwood F test revealed highly significant differences (p < 0.0001) between the datasets of one and two rounds of amplification.
The concordance correlation revealed a very low average correlation coefficient between the datasets of one and two rounds of amplification (0.09 ± 0.09) indicating a very low agreement between the two amplification methods.
The differences between the datasets of clinical studies by implant developers and pooled data were statistically significant, which was not, however, the case for the difference between inventor studies and independent studies.
The values of PSR were compared between the datasets of mRNAs either including or skipping the cassette exons from the array, as well as for all mRNAs detected by RNA-seq belonging to genes with multiple isoforms.
The biggest variation was observed between the datasets of study 1 (GSE3141 (Bild et al., 2006)) and study 5 (GSE29013 (Xie et al., 2011)), which showed more than a 32 fold-difference in expression levels.
To partly cope with the resulting artifacts in the tomographic reconstruction, a statistical iterative reconstruction technique, described in detail by Hahn et al. (Hahn et al., 2015), was applied with parameters optimized for each modality individually but consistent between the datasets of the three mice.
Principal component analysis shows a statistical relation between the datasets of RHs and PTs which is suggestive of a common transcriptional profile pattern for the apical growing cells in a plant, with overlapping profiles and clear similarities at the level of small GTPases, vesicle-mediated transport and various specific metabolic responses.
