“highly significant”

The correlation between the number of PPI domains and the number of TF–TF interactions was highly significant and negative (Spearman r = −0.455, P -value = 1e-51; fig. 1B ; table 1 ).

This observation was held for trial-by-trial analysis of firing rate on FI12 trials, which revealed a highly significant interaction between time-related ramping, temporal context, and brain area (three-way ANOVA of GLMMs; F (4 045 080) = 226.8, P = 3e-51; Table 2 ).

Discrimination capacity was high (AUC > 0.8) and highly significant ( p = 6.516 × 10 –51 ).

Furthermore, COWAS discovered a highly significant effect of the interaction between APOE and LDLR on AD risk ( P < 1e−50).

To assess the statistical significance of the enrichment of cLD in 3D contact regions, we conducted Mantel-Haenszel and Fisher exact tests ( Section 3.4 in S1 Text ), both of which are highly significant (P-value < 1.0E-50; Tables J and R and Section 3.4.1 in S1 Text ).

Likelihood ratio tests indicated that the differences in model fit were highly significant (both P < 10 −50 ).

7 There is a highly significant correlation between absolute ASM scores across all probes informative in both data sets (n = 129,559, r = 0.21, P < 1.0 × 10 −50 , Fig.

The RNA-seq based estimates of the change in transcript abundance showed a highly significant positive correlation with the change in the long/short-ratio ( Fig 2B ; correlation coefficient 0.32; p-value <1.0E-50), which was even stronger for the 97 genes with significant tail-length change after multiple-testing correction ( Fig 2B ; correlation coefficient 0.4; p-value = 4.4E−05), suggesting that changing the poly(A)-tail length due to reduced PAPS1 activity alters transcript abundance.

The Spearman correlation coefficients (ρ) were 0.83 for both the nonstimulated and EGF-stimulated conditions, with highly significant p -values <1 × 10 –50 .

We found the correlation of similarity within days and across days to be high (ρ = 0.75) and highly significant (P<10 −50 ).

A minority of SNPs > 500 kb away from their associated eGenes were highly significant (0.5%, P < 1 × 10 -50 , 13.4% with P < 5e-8) (Figure 4 A).

However, even though the overlap between the two target sets was modest (46%), it was statistically highly significant ( p <10 −50 ).

All CpGs that were highly significant [−log( P- value) > 50] were negatively correlated with the expression of their corresponding gene, and many of them were recurrent in several tumor types, namely CpGs in TDRD1 ( n = 16 tumor types), RNF17 ( n = 13 tumor types), SP140L ( n = 5 tumor types), and STK31 ( n = 3 tumor types) ( Fig. 3 D).

Ten other regions with smaller but still highly significant effects (20 ≤ − log 10 (P) < 50) were located on BTA 5 (~ 119.0 Mbp), 6 (~ 43.3, 48.1, and 85.6 Mbp), 11 (~ 103.2 Mbp), 17 (~ 50.8 Mbp), 19 (~ 60.6 Mbp), 20 (~ 55.9 and 60.8 Mbp), and 22 (~ 32.8 Mbp); these also generally affected multiple milk components.

This analysis revealed amongst the biotin-oAβ1-42 binding candidates a highly significant overrepresentation (p<1.0 E-50) of ‘Cellular component’ GO classifiers that indicate an association with the ‘extracellular vesicular exosome’, ‘cytosol’, ‘vesicle’ and ‘extracellular region part’ ( Figure 1C ).

Relationship of citation source to citation validity Pearson’s chi-square tests revealed a highly significant association between citation source type (article vs. book) and citation validity across all three models (χ2 ≥ 236, df = 3, Bonferroni-adjusted p < 1 × 10 − 50).

In contrast, NLR showed a moderate correlation (r = 0.6299) with a highly significant difference between the pre- and post-deployment values ( p = 1.43 × 10 −50 ) ( Table 3 ).

Recent large-scale meta-analyses of PD GWAS have described a highly significant peak at chromosome 4 (latest PD GWAS, chr4:951947 (hg19)/rs34311866, P = 1.47 E − 50, odds ratio [OR] = 1.232, standard error [SE] = 0.014) ( 3 , 4 ).

These differences in the percentage of cells with naive phenotype between day 0 and nadir, and between nadir and plateau, were highly significant (p = 1.99 × 10 −50 and p = 2.69 × 10 −38 , respectively, by paired t test).

As a group, haplotype-specific FIRE scores for these 124 peaks carried highly significant differences between their corresponding haplotypes (paired t test, p < 2 × 10 −50 , Figure 4 D).

This result was also reflected in our highly significant Pearson's correlation analysis of the cumulative deletion read % between Splice-Break and MitoDel (Pearson's r : 0.950; P = 2.98e −50 ) ( Supplemental Figure S14J ).

Overall, population differentiation between basins along the first eigenvector was highly significant ( p ‐value = 5.4 × 10 −50 : summed across AMOVA comparisons). 3.4 Isolation and migration analysis reveals gene flow between divergent populations The unconstrained model, M‐mode in IMa2p, estimated a population splitting time parameter t of 0.29 (HiPt = 0.299, HPD95Lo‐Hi: 0.253–0.351).

This overlap is highly significant ( P = 6 × 10 -50 ) and substantially greater than with any other signatures we tested (Table 1 ).

Using 14–19 months of cumulative 24/7 home-cage activity recorded with a non-intrusive technique, evidence is here provided for a highly significant circannual oscillation in spontaneous activity (1–2 SD of the mean, on average 65% higher during peak of highs than lows; P = 7E−50) of male and female C57BL/6 mice held under constant conditions.

Comparing the inferred “age/maturity” of the individual B-cell cluster showed highly significant differences between the three nonmature B-cell subpopulations (Kruskal-Wallis test, p =9.84e-50).