Excerpts

In the case-control dataset with PM1 method, RL0-855 was highly significant at each phenocopy level until 45%, displayed a −log10(p) = 62.54 at 0%PE and a −log10(p) = 25.84 at 45%.

This resulted in highly significant (p < 3.1 × 10 −63 ) separations of positive and negative correlations between functional readouts and lipid abundance ( Figures 4 E–4H and S4 J).

Genes involved in the Fgf/Mapk pathway are up-regulated by Fgf4 overexpression and Cic knockdown Using the stated selection criteria, 122 genes are significantly up-regulated by Fgf4 overexpression and 457 by Cic knockdown ( S1 Table ; Fig 3A , 3B , 3D and 3E ), with a highly significant (p<3.9e-63) overlap of 65 genes up-regulated in both conditions ( Fig 3B , S4 Table ).

There was a strong highly significant correlation between the expression levels extracted from the microarray data and those obtained using EST (Pearson CC = 0.39, P < 10 −62 ) ( supplementary figure S5 , Supplementary Material online).

Despite this potential for background noise in the overall associations, a number of individual genes stood out as highly significant, most notably a P450 gene (Zt09_7_00450, P = 2.49e − 62) and several major facilitator superfamily (MFS) transporter genes (Zt09_10_00549, P -values (Wald) = 5.57e − 19; Zt09_7_00012, P = 9.97e − 13; Zt09_7_00453, p-values (Wald) = 1.69e − 18).

Additionally, we have observed a highly significant difference in the expression levels of the conserved duplicates compared to the neofunctionalized (Wilcoxon test, P < 2.5E-61) and specialized genes (Wilcoxon test, P < 2.3E-42) (Fig. 5 B).

Additionally, a highly significant correlation was observed in the scatter plot of gene significance (GS) and module membership (MM) within the MEblue modules (cor = 0.92, p = 2.9e − 61) (Fig. 3 D).

We observed a highly significant association between rs7538876 and the methylation status of a CpG island within RCC2 (probe ID cg07965774; p = 10 -60 ), which was the strongest meQTL observed for this SNP (Figure 4 B).

Panel C presents the frequency of genes in each of the 36 possible 6 × 6 matrix of sets and shows that there is highly significant overlap (p<10 -60 likelihood ratio test of clustering of categories).

Our algorithm identified 35 highly significant clusters ( P <10 −60 ), merging factors from different levels of the transcriptional architecture.

Despite moderate discrimination (C-index ∼0.67), the model achieved a 3-year Brier score of 0.21, reflecting excellent calibration, and demonstrated highly significant survival separation across predicted risk quartiles (log-rank χ 2 = 304; P < 10 -60 ).

Forward perturbation direction theta dynamics model The forward perturbation direction GLME model was overall a highly significant fit to the data ( R 2 = 0.147, F (3703) = 29.70, P = 1.27e −60 ) ( Fig. 5 ).

The link between VIRMA amplification and overexpression was further supported by a correlation analysis of VIRMA copy number values and mRNA expression levels, which demonstrated a highly significant ( p = 3.02e-60, Pearson correlation) positive association (Fig. 5I ).

By qPCR on ChIP DNA we confirmed that CGGBP1 was indeed bound to the identified peaks (one SE motif-containing peak randomly selected from each chromosome) and that this binding was strongly and highly significantly enhanced upon serum stimulation (T-test, p = 3.785E-60; Fig. 1D ).

These ROS-responsive genes overlapped with 207 ++Fe-induced and 10 ++Fe-suppressed genes, and the degree of overlap between ROS-responsive and ++Fe-inducible genes was highly significant ( P = 1.5 × 10 -59 by Fisher’s exact test), confirming that excess Fe causes oxidative stress in leaves ( Figure 6E ).

An example was NMU , for which DAESC-Mix reports highly significant dynamic ASE ( p = 1.93 × 10 − 59 ) and captures the haplotype combinations well ( p f i s h e r = 1.51 × 10 − 6 ).

We observed highly significant genetic correlations, with the strongest overlap between AF and heart failure (r g = 0.57, P = 2.30 × 10 −59 ), suggesting a substantial shared genetic basis.

The 2 scores were highly significantly and positively correlated ( Figure 4 ; r = .937, P = 3.94 × 10 − 59 , N = 127).

Highly significant associations were detected on BTA6, BTA7, and BTA20 (e.g., ADG on BTA7, p = 1.16 × 10−58; MBW on BTA20, p = 8.39 × 10−280), with carcass weight QTLs overlapping MWT and BCS on BTA7 ( p = 4.61 × 10−31) and BTA20 ( p = 2.87 × 10−58).

Both parameters revealed highly significant correlations with age, with PWVao showing a correlation coefficient of 0.75 ( p = 5.74 × 10 −58 ) and age with SAF showing a correlation coefficient of 0.69 ( p = 1.03 × 10 −45 ) ( Figure 1 A).

For faces, the comparison between w -based and VGGFace-1-based encoders shows no significant difference (2-Sample T-Test; t (1918) = −0.2859, p = 0.78) but we found highly significant differences when comparing w -based encoders with VGGFace-3 (2-Sample T-Test; t (1918) = 16.5817, p = 8.21 e − 58) and with VGGFace-5 (2-Sample T-Test; t (1918) = 15.0820, p = 1.17 e − 48).

The two partial correlations were both quite significant ( f versus txn rate/tlns per mRNA | protein production rate, complex membership: Spearman partial r = 0.227, n = 4,746, p = 10 −57 ; complex membership versus txn rate/tlns per mRNA | protein production rate, f: Spearman partial r = 0.147, n = 4,746, p = 10 −24 ), suggesting that fitness effect and protein complex membership are independently associated with the expression strategy that minimizes stochastic fluctuation.

As shown in SI Figure 1 , highly significant difference was apparent in the staining intensities of cancer cells versus stromal cells, with stromal cells showing a nearly 8-fold greater average intensity than the cancer cells ( p -value = 1.54 × 10 −57 ).

CCDC168 , another gene with a Faroese enriched stop gain variant had highly significant rare variant associations in the UK Biobank with corneal hysteresis and intraocular pressure (rs1361247423, p =1.79e-57, p =5.21e-13, respectively).

This overlap is highly significant (hypergeometric test, P = 2.1 × 10 -57 ) and suggests that enhancer-associated MIRs might have an impact on erythropoietic regulation.