While spatial auto-correlation is comparable in magnitude to temporal auto-correlation in a small copy number regime (Fig. 11 top panels), we observe much greater spatial auto-correlation than temporal auto-correlation for various lag k values in a large copy number regime (Fig. 11 right panels).
The variance was much greater in the correlations to the xenograft volumes (SUVmean (Fig. 6e, exponential regression, r 2 = 0.27 (the largest tumor was here treated as an outlier and excluded from the plot)) and SUVmax (r 2 = 0.38, data not shown)), indicating the correlation to be quite poor.
In the course of our analyses, we calculated simple uncorrected (Hamming) distances with PAUP* (DSET DIST = P) because in preliminary analyses (not shown), we observed that with the current data, the type of recoding has a much greater effect on the correlation with reference distances and on the Delta values than the nucleotide distance function applied.
Interestingly, although the average CP of opposite cells was approximately 0.5 for both models in the combined condition (pure-correlation model: 0.486 ± 0.13 SD; selective decoding model: 0.491 ± 0.06 SD), the SD of CP across the population of opposite cells was much greater for the pure-correlation model than for the selective decoding model.
Although original and updated BLUPs were highly correlated as input values (r =0.99), their small differences resulted in QTL model residuals with much greater differences, reflected in correlations of 0.80 to 0.91 between residual outcomes differing only for original vs. updated BLUPs (Model comparisons 1 vs 3, 2 vs. 4, and 5 vs. 6; Table 3).
Although in both sexes higher average recombination frequencies were observed for regions exhibiting a higher GC content, this correlation was much greater in females than in males.
Since microarray measures are inherently corrupted by noise, we hypothesized that the true underlying biological correlations between gene expression and H3K9 acetylation were much greater than captured through a simple correlation of high SNR genes.
The strength of the correlation between plantarflexion moment arm and 6MIN velocity found for slower subjects is much greater than those previously reported for correlations between ankle strength or power and walking velocity.
Thus, the degree of correlation between the two variables is much greater but not perfect; there are other climatic variables influencing the correlation between the two.
In comparison, the square root of AVE was much greater than the absolute value of the correlation coefficient between latent variables, thus indicating good discriminate validity of such variables.
