“highly significant”

Among the 12 genes related to hormone secretion, Vgf (nerve growth factor inducible) showed a highly significant increase in expression in GCGR-KO α-cells (Log 2 FC = 1.38; p = 2.21E-203) (Fig. 4a ).

In the present study, we found a highly significant enrichment of long TRD sequences in RA compared to healthy individuals ( P = 7.91e − 202, Additional file 32 : Fig S7).

These tendencies were observed in both the 1645 group and the 239 group (data not shown) and were highly significant by Wilcoxon's rank-sum test (both of them showed P < 1e−200).

This module contained 753 genes, which showed a highly significant association with nmSCs infiltration levels (Cor =0.88, P<1e−200; Figure 2C ).

Notably, chemical effects on cell-level SRPs were reliably detected across varying signature lengths, particularly in the UPR, where chemicals such as Brefeldin A, Cycloheximide, and Troglitazone exhibited highly significant length-dependent effects ( p < 1e-200) despite their small effect sizes.

The analysis shows clear, highly significant (p-value < 1e-200) enrichment with matching FC signs between our SCZ analysis and reference PsychENCODE SCZ data (Supplementary Fig.

In total 689 genes appear in both lists, which represents a highly significant overlap ( P value <1E-200) (Figure 3a and Additional data file 2 , Table S2).

This finding was further supported by scatter plots, which demonstrated a highly significant level of connectivity within the turquoise module (cor = 0.77, P < 1e-200, Fig. 3 E).

Within the brown module, a highly significant correlation was observed between gene significance (GS) and module membership (MM) (correlation coefficient = 0.92, p < 1e − 200) (Fig. 2 D).

A highly significant enrichment of Hsf1 binding sites was detected in the promoters of genes belonging to cluster 4 ( p < 10 −197 ; Table 1 ; Figure S6a in Additional file 11 ).

Steady state mRNA levels had a highly significant ( p < 10 −197 ) correlation with mRNA stability ( Fig. 2c ).

This trend is, again, present and highly significant in the experimental data ( 52 ) (logistic regression with two-tailed t -test, P = 1.5 × 10 − 195 , n = 7 , 311 ; Fig. 3 D , Right ).

The strong positive correlation between the cophenetic pairwise distances and proteomic dissimilarities is highly significant (rho = 0.6540, p-value = 1.9599e-195; r = 0.7291, p-value = 7.6776e-265), suggesting that the representative tree illustrates quite well the differences in the proteomic properties.

The shift for “No IC” and “Any IC” was also both highly significant ( p = 7.79406e–193 and p = 5.31155e–78, respectively) ( Table S3 ).

There is a highly significant positive correlation (r = 0.709, p = 8.98 × 10 −193 ) between the expected, real IC 50 values measured in the CCLE dataset and the values predicted by regression, based on the CGP dataset, which clearly confirms the validity of the prediction framework proposed here.

Consistent with our previous results, we found a small but highly significant enrichment of dDMPs becoming hypomethylated with cortex development ( n = 28,780 [56.5%], p = 1.61 × 10 −191 ) with the mean effect size being significantly greater for hypomethylated dDMPs than hypermethylated dDMPs (change in DNA methylation [%] per week: hypermethylated dDMPs = 1.03, hypomethylated dDMPs = −1.53, t test p < 1 × 10 −320 , Figure S3 ).

However, the correlation in expression of CD14 and K2 was highly significant (p = 8 x 10 −191 ) compared to that of CD19 and K2 (p = 0.065) at 1 dpi.

50 With regard to the highly significant overlap ( P = 1.9E − 184) with the dataset comparing MDA-MB-231 cells vs MCF10A cells, it was striking that the majority of the 2385 overlapping gene features showed a negative correlation ( Fig. 2E ), indicating that more than 2/3 of the transcriptional alterations induced by low density cultivation of MCF10A cells overlapped significantly with MDA-MB-231 cells.

This deviation is highly significant (χ 2 = 841.64, df = 2, P < 1.74 × 10 − 183 ) ( supplementary table S3 , Supplementary Material online).

To determine whether the overlap between the differentially expressed genes in FFPE RNA-Seq and FF microarrays in both datasets was not due to random association, we performed a hypergeometric test which revealed that the overlap was highly significant ( p < 10 -182 ) for both increased and decreased genes.

While about 8% of the worm genome is arranged antisense to another gene (Thierry-Mieg & Thierry-Mieg, 2006 ), approximately 35% of increased and decreased transcripts were arranged in this manner, representing a highly significant enrichment ( P = 5.3 × 10 −181 , hypergeometric distribution (hgd)) (Fig 1 B).

We found that the expression of 60% of sugar-responsive genes was also altered in dfoxoΔ flies, representing a highly significant overlap (p = 9.4 × 10 −181 ; Figure 2 ).

A One-Way ANOVA was performed, and the results indicate a highly significant difference between the ligand groups (P-value < 6.6718 × 10 −177 ).

This trend was confirmed across two additional independent sampling replicates ( n = 10,000 molecules per replicate), indicating that the effect is not attributable to stochastic variability. Across all runs, the improvement in QED at T = 0.6 remained highly significant (one-way ANOVA p < 10 –175 ; Kruskal–Wallis p < 10 –180 ), with a similarly significant reduction in structural alerts ( p < 10 –2 ).

Analysis of CpG sites positively correlated across all tissues revealed ‘nervous system development’ as a highly significant gene ontology (GO) term (P = 2.0 × 10 –171 ).