In contrast, CD274 and PDCD1LG2 showed significantly weaker correlations with each focus gene, but nonetheless remained well correlated in comparison with all genes tested (rank <1000 out of 20,121 tested).
A non-spatial Markov process model provides excellent agreement with this broader histogram indicating that cells in the primitive streak may have significantly weaker spatial correlations.
Significantly weak negative correlation was established for IgM with the received dose (r = −0.112) and a positive one for immunoglobulin A (r =.259).
Although both models also show a similar dependency of CP on neuronal sensitivity in the combined condition (p<<0.001, linear regression, Figure 5F,G), the strength of the correlation is significantly weaker for the pure correlation model (R = −0.41, 95% CI: [−0.32 to −0.48]) than for the selective readout model (R = −0.67, 95% CI: [−0.61 to −0.72], Figure 5H).
However, a significantly positive weak correlation was found (R = 0.3561; P < 0.0001) between the two raters and Bland-Altman analysis revealed that there was a slight bias between the raters for the number of voids counted in slices with many voids (Supplementary Fig. S1).
At other locations where seasonal changes in the relative humidity tend to be less significant (Copiapó, La Serena and Iquique), the correlations in Fig. 5b were significantly weaker.
Similarly, we connected HDF proteins that significantly share indirectly interacting viral proteins (P<0.01) and found a similar, yet weaker correlation between pathway involvement and indirectly targeting viral proteins (inset, Fig. 3D; r = 0.26, P<0.1).
Our results demonstrate a significantly positive and linear correlation of serum ferritin levels with SLEDAI, serum creatinine levels and urine RBC counts, and a weaker correlation with serum complement.
Correlations between neurite/synapse-enriched miRNAs from one family with the optimal normalizer of another family are significantly weaker (Fig. S5).
The activation was significantly weaker.
