“highly significant”

At the provincial level, the analysis reveals a highly significant difference in case distribution across months ( χ 2 = 169.82, df = 11, p -value < 2.2e-16).

We first assessed the variation in gene expression among the three biological replicate samples for each sex and tissue; the correlation values were highly significant between them all (Spearman's rank correlation coefficients of at least 0.95, p-value<2.2×10 −16 ; Figure S1 ).

We found a highly significant positive correlation of number of hits per target site with motif score (Spearman's correlation, ρ = 0.154; P < 2.2 × 10 −16 ) and weak positive correlation with palindrome score (Spearman's correlation, ρ = 0.029; P = 0.003).

Wilcoxon rank sum test with continuity correction revealed highly significant changes for old versus young cortex and hippocampus circRNA TPM values ( P < 2.2 E-16) ( Fig. 2d ).

All fitted models were highly significant ( F 5,122 = 26.1, p -value < 2.2 × 10 -16 with ‖ Δ ^ ̄ − Δ ‖ as response; F 5,122 = 47.7, p -value < 2.2 × 10 -16 with λ ^ ̄ as response; and F 5,122 = 12.1, p -value = 1.6 × 10 -9 with | ε ^ g e n − ε ̃ g e n | ̄ as response); residual plots showed no large deviations from the assumptions of normality of error distribution (an asymptotic normal distribution of the response variables is warranted by the central limit theorem), homoscedasticity, and independent errors (data not shown).

This comparison also revealed highly significant, albeit slightly weaker correlations (Pearson correlation 0.73; P <2.2e-16; Figure S11 ) – similar to the results we obtained for chromosome 1 CNVs.

One notes highly significant terms for time (β-est. = 0.21, (95%C.I. 0.17, 0.25), p < 2.2 × 10 −16 ), monthly cannabis use (β-est. = 2.97, (1.91, 4.03), p = 8.2 × 10 −8 ), cannabis use quintiles (β-est. = 3.86, (2.45, 5.27), p = 1.2 × 10 −7 ), dichotomized cannabis use quintiles (β-est. = 3.54, (2.19, 4.89), p = 4.4 × 10 −7 ) and time: quintile interactions. 3.4.

ponticus worker (average of 0.00186, range from 0.0002 to 0.0024) versus all other individuals which have very close to zero γ values (average of 1.86 × 10 −6 , range from 6.598 × 10 −7 to 6.461 × 10 −6 ), with a highly significant difference (two-sided Wilcoxon rank-sum test, P < 2.2 × 10 −16 ).

Visually, H3K4me2 also seemed to be lost at this region, but the major site of enrichment, at the spacer promoter, was unaffected, and the locus-wide correlation remained robust and highly significant (mESC vs. mNPC: R 2 = 0.87, P <2.2 × 10 −16 ).

Gene set analysis using the signatures in the Molecular Signatures Database (MSigDB) revealed a highly significant positive correlation of the KIT-signature with the hallmark EMT signature ( r = 0.81 and p < 2.2e−16) (Fig. 1C, D ).

To test this prediction, we performed DRIP-seq in ovaries dissected from adult females and found strong, highly significant correlations between the female whole fly samples and ovary samples for both nonDE and FE peaksets from the adult data (Spearman’s rho > = 0.72 and P < 2.2e-16 in all comparisons, S2D Fig ).

A binomial test confirmed that this enrichment was highly significant ( p < 2.2 × 10 − 16).

However, it is interesting to note the highly significant co-directionality (binomial test: p < 2.2e−16) of the expression changes observed for nitrogen-limited cultures and in hospite symbionts, with 92.67% of the 12,295 (11,394) DEGs changing expression in the same direction (Fig. 2 e).

The Kruskal–Wallis test revealed highly significant differences between conditions at 0–24 h (H = 147.38, df = 2, p = 2.2 × 10 −16 ) and 24–48 h (H = 121.46, df = 2, p = 2.2 × 10 −16 ).

The overlap was highly significant, with 30% (1095/3647) of SEM CpGs found to be among NRBC-associated CpGs ( p < 2.2E−16).

This shift was highly significant as determined by the Mann-Whitney-Wilcoxon Test ( P <2.2*10 −16 ).

Regression analyses indicate a highly significant relationship between PSC accuracy ( cf . empirical species richness) versus wia ( F 1,8190 = 5615, adjusted R 2 = 0.4067, p < 2.2e−16; Figure 4a ), whilst the relationship weakens when positive (WIA) and uninfected (uWIA) predictions are combined ( F 1,8190 = 1933, adjusted R 2 = 0.1909, p < 2.2e−16; Figure 4b ).

When miRNA expression levels were averaged for tissue type across animals within the groups, Spearman’s rank correlations between PBMCs and the brain regions are all highly significant ( r s = 0.47–0.57; P < 2.2 × 10 –16 ), although pairwise correlations among the brain regions are markedly stronger ( r s = 0.86–0.99).

Fisher's exact test confirms that this difference in numbers is highly significant ( p < 2.2 × 10 −16 ).

A comparison of activation strength in both assays revealed an intermediate (Pearson's correlation coefficient of 0.58) but highly significant correlation ( P < 2.2e−16) of activation values ( Figure 1B ).

Results There was large variation in cross-correlations among MD scores, from nil (t=0.0, p=0.54) to highly significant (t=0.97, p<2.2e-16).

Subsequent statistical analysis revealed a highly significant ( p < 2.2 × 10 −16 ) cell cluster composition between the baseline sample NI Day + 0 ( n = 217 cells) compared to differentiated samples S Day + 15 ( n = 577 cells) and SON Day + 15 ( n = 400 cells) as well as between the differentiated samples ( Figure 3 C, Table S5 ).

On the other hand, when we considered each individual base count independently, we observed that the count of G nucleotides specifically shows a stronger negative correlation (R = −0.22) than the C nucleotide count (R = −0.074) alone ( Figure S5 A), although both correlations are highly significant (P < 2.2 × 10 −16 ).

The final model was highly significant ( p = 2.2e−16), and for all three cancer types IRF1 was identified as a significant explanatory variable for CD274 expression (Table 1 , left 3 columns).

A chi-squared test revealed a highly significant difference in the distribution of genes across score ranges among the three categories (χ2 = 519.5, df = 18, p < 2.2 × 10−16), indicating that gene distributions differed substantially between them.