“highly significant”

The slope coefficients were highly significant ( p -values < 2.2 × 10 −16 ), confirming a strong linear relationship between er and the IM-MS responses.

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 ).

All reported correlations were highly significant ( p < 2.2 × 10 −16 ).

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 ).

Analysis of variance showed that the genotypic (G) and the year (Y) effects for fruit weight were highly significant for each population ( P values < 2.2e-16).

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

Remarkably, we observed a highly significant negative correlation between B cell levels and HEUScore among all immune cell subtypes ( r = -0.8857, P < 2.2e-16) ( Figure 5G ).

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 ).

Remarkably, we found a highly significant increase in entropy in the converging sites of 0.005 increase in entropy per decade of age ( p value < 2.2e −16 ), and a stark contrast with the diverging sites, which significantly decrease entropy with age, and could be considered “anti-entropic” since they become more predictable with age (Fig. 5 B).

The excess of GC to AT substitutions is highly significant, indicating non-equilibrium ( p < 2.2 × 1 0 − 16 ).

Distribution profiles of wtTrop-2 /∆cytoTrop-2 cells indicated a highly significant reduction in aggregates with respect to control cells (χ2 test P-value <2.2e−16).

Using a pairwise comparison of 5286 genes with adjP ≤ 0.1 for log fold change of WT MR versus WT Con and NRF2 KO MR versus NRF2 KO Con, the correlation of the effect of MR in the two genotypes was highly significant (R 2 = 0.64, p < 2.2 × 10 −16 , Supplementary Figure S2 ).

Spearman’s correlation of the methylation levels obtained for the fully methylated and unmethylated HBV controls with Nanopolish and Guppy+Medaka indicated a highly significant correlation ( R =0.83, P <2.2 −16 ) ( Fig. 2e ).

Analysis of variance based on the reparametrized polynomial-interaction model with MPR effects showed a highly significant impact of partial yields on test-day yields ( P <2.2e-16).

A linear statistical model for the rate constant of photoinhibition ( k PI ) was highly significant ( F (8,95) = 50.3, P < 2.2 × 10 −16 ) and showed that k PI was significantly affected by light color (coefficient 0.70 ± 0.0095, P = 6.75 × 10 −11 ) and leaf group (coefficient 0.016 ± 0.0069, P = 0.0256) but not by the other variables (see Summary of statistics available as Supplementary data at Tree Physiology Online).

Statistical analysis using an independent two-sample t -test (Welch’s correction) revealed a highly significant difference in mean PC1 values between the two groups ( P < 2.2 × 10 −16 ).

Additionally, the P-value for accuracy being greater than the No Information Rate (NIR) was highly significant (P < 2.2e-16), indicating that the model’s performance was far superior to random chance.

Despite major differences in experimental design, including the developmental stage of the worms, the overlap with the single-cell cis eQTLs was highly significant, with 335 cis eQTLs shared between the studies (OR = 7.2, p < 2.2×10 −16 , Fisher’s exact test) ( Figure 3C ).

The Welch 2 Sample t-test indicated a statistically highly significant difference in PRS between the 2 dietary categories ( t = −32.758; P = 2.2 × 10 −16 ).

For example, the Fisher exact test for association between the markers rs3856806 and rs41516544 for both males and females was highly significant (P-values <2.2×10 -16 and 1.102×10 -12 , respectively).

Transcripts that lose m6A during differentiation show highly significant increase in TE in glioblastoma samples irrespective of subtype (GSC1: p<2.2e-16, GSC2: p<3.4e-11, GSC3: p<2.2e-16) (Fig B in S1 Text ).

The polarity score analysis of all expressed ORFs revealed a small but highly significant shift of ribosomes toward the 5′ end of ORFs when RPLP1/2 were depleted (mean of the differences = 0.013, P = 2.2 × 10 −16 ) ( Supplementary Figure S12A ).

This correlation was highly significant ( p < 2.2 × 10 −16 ), indicating that the observed similarity is unlikely to occur by chance. 2.4 Expression of PAMPs and DAMPs in Human and Murine pDCs Quantitative proteomic comparison of human and murine plasmacytoid dendritic cells (pDCs) revealed selective, pathway‐specific differences rather than global proteome shifts.