“highly significant”

The results indicated highly significant Pearson correlation coefficients of −0.82, −0.68, −0.78, and − 0.71, respectively, with P -values < 2.2e-16 ( Fig. 3B-E ).

Results Phenotypic variance decomposition and heritability of partial resistance to bacterial canker Considering differences between all controls and inoculated shoots regardless of the genotype effect, a highly significant effect of bacterial inoculation was observed (Wilcoxon unilateral t.test p < 2.2E-16) for lgc whatever the year and for bs in 2013 and 2015 (lesser extent in 2014 p < 9.77E-12 and 2016 p < 9.06E-06).

We found that both up- and downregulated genes showed highly significant enrichment for association signals ( Z = 9.41, P < 2.2 × 10 −16 for genes downregulated by SUMO-1 depletion and Z = 3.43, P = 4.19 × 10 −4 for genes upregulated by SUMO-1 depletion; Figure 5 D).

A Fisher’s exact test confirmed that this difference is highly significant ( P < 2.2 × 10 –16 ), with an odds ratio of 2.76.

Of these orthologs, 5,292 genes were located on the autosomes and 942 on the X chromosome, resulting in a highly significant difference in their chromosomal distribution (chi-squared test, p < 2.2 × 10−16).

These differences, while modest in strength, were highly significant (p < 2.2e-16).

Moreover, not only do we find differences in predictive performance between populations from different continents, we also find highly significant differences in prediction accuracy among the four European ancestry populations considered ( F -test p -value < 2.2 × 10 −16 ).

In addition, CREB1 is the top upstream regulator of the 465 overlapping differentially expressed genes (see previous texts) and there is a highly significant, negative correlation ( r = − 0.91, p value = 2.2E−16) between the fold changes for these genes—including the 58 direct CREB1 target genes—in the two comparisons (Supplementary Fig. 3 ).

5 a and b) and gene expression was highly significant for both root and leaf (root: R = 0.364, P < 2.2e-16; leaf: R = 0.334, P < 2.2e-16).

Likelihood ratio tests reveal a large, highly significant effect of third chromosome line on phenotypic variation in bacterial load against all four bacteria ( S. marcescens : χ 2 = 128.42, d.f. = 1, P <2.2×10 -16 ; P. rettgeri : χ 2 = 263.88, d.f. = 1, P <2.2×10 −16 ; E. faecalis : χ 2 = 51.533, d.f. = 1, P = 7.04×10 −13 ; L. lactis : χ 2 = 35.391, d.f. = 1, P = 2.70×10 −9 ).

The observed overlap was highly significant ( P value < 2.2 × 10 −16 ), indicating strong concordance between the 2 datasets.

Further, the concordance of miRNA expression (log normalized) of the common miRNAs was also explored by Spearman correlation and showed a highly significant correlation with rho of 0.81, p<2.2x10 -16 ( Fig 4b ).

A highly significant statistical difference (X-squared = 1715.4, df = 180, p -value < 2.2 × 10 −16 ) was found between the frequency combinations of the two haplotype sequences. 3.5.

The difference between the nuclear area of cells from infected and uninfected plants was highly significant (based on the Brown–Mood median test, p = 2.2e-16), and the nuclear area of cells from P. brassicae -infected plants was 2.8 times bigger based on the median size.

Out of 387 proteins associated with gestational age in human amniotic fluid, 225 (58%) were also associated with gestational age in rhesus and the correlation of effect sizes between the two species in the 225 overlapping false discovery rate (FDR) significant proteins was highly significant (R = 0.75; p < 2.2e–16; Fig. 4 ).

The difference in half‐life distribution is highly significant with a p ‐value = 2.2 × 10 −16 (Kolmogorov–Smirnov test).

The correlation of the concentrations determined by 1 H-NMR and by quantitative methods were highly significant for both the samples of ccDMEM (Pearson: r = 0.99, p = 2.20 * 10 −16 ) and of vcDMEM (Pearson: r = 0.91, p = 2.84 * 10 −6 ).

The difference was highly significant ( p < 2.2 × 10 −16 ), indicating robust epigenetic dysregulation of the SYTL4 locus in breast cancer ( Figure 2 A).

Overall, we observed a modest but highly significant correlation of predictions with both these regulatory prediction scores reported by DeepSEA (multi-tissue: r = 0.227, p<2.2e-16; PanIslets: r = 0.223, p<2.2e-16) ( Figure 3—figure supplement 1 - AB ).

The mean values of the non-invasively measured community-wide parameters obtained by DWCP seem to give a valid representation of the actual plant community as indicated by the highly significant positive relationship between the weighted plant biomass removed from sods and the digital biomass extracted from scans (quadratic polynomial regression, p < 2.2e-16, adjusted R 2 = 0.59, see Additional Figure 3 ), supporting results from scans of plant individuals ( Laxman et al., 2018 ).

Despite these differences, δ age and δ PD showed a highly significant positive correlation (r = 0.71, p < 2.2 × 10 −16 , Pearson) ( Figure 4 C), suggesting that the process of decoupling is qualitatively similar and has a comparable genome-wide distribution in HA and PD, although it is more pronounced in the latter.

Additionally, a Kruskal-Wallis test revealed a highly significant difference in ANI across the three comparison types (χ2 = 6,332.9, df = 2, P < 2.2e – 16).

There was a highly significant effect of orchard on epiphyte species richness per tree ( F 4,607 = 358.17, p < 2.2 × 10 −16 ) and a highly significant effect of cultivar nested within orchard ( F 5,607 = 20.92, p < 2.2 × 10 −16 ; Appendix S2).

The Chi-squared test among the 6 groups of fishers defined above and the catches of the 14 main taxa (each representing > 2% of the total number of caught individuals and 83% of the overall catches in total) was highly significant (Chi-squared = 914.8, df = 65, p value < 2.2e-16), allowing to conclude that the groups of fishers did not have the same target species.

Note that likelihood ratio tests comparing the model results without and with the T1WP correction were all highly significant ( p < 2.2 × 10 − 16 ), probably due to the high number of observations and relatively small number of terms in the model.