Results Strong, negative association between elevation & lung cancer incidence Performing best subset regression for each cancer, we found a highly significant, strong negative association between elevation and lung cancer incidence with a standardized coefficient ( β z ) of −0.35 99% CI [−0.46, −0.25] ( p < 10 −16 , one-tailed t -test) ( Table 2 ).
Excerpts
The correlation between RNA-seq fold changes computed on the data from day 2 versus that from day 4 was highly significant (r = 0.50, P<10 −16 , Figure S2A ).
In particular, there was a highly significant overlap ( p < 1E-16, one-sided Fisher’s exact test) between the top 56 enriched cytobands from the CBTN cohort and a top set of 79 enriched cytobands from the PCAWG cohort, involving 29 cytobands (Figure S1e).
Each result is highly significant ( p < 10 −16 , for each predictor.
The network displayed an average clustering coefficient of 0.604 and a highly significant PPI enrichment ( p < 1.0 × 10−16), indicating substantial functional connectivity among the proteins.
This detrimental effect of antibiotics was highly significant among the phyla Bacteroidota and Firmicutes_A (p < 1e–16, OR 0.7) and observed at various host ages ( Figure S2 E).
The PPI network comprised 51 nodes and 283 edges, with a highly significant enrichment (PPI enrichment p-value < 1.0e-16) as shown in Figure 4A .
However, larger differences were observed between organs that were highly significant ( P < 10 −16 for all four targets).
They were not identical to the ones identified in each disease individually, but showed a highly significant overlap in both cases ( p < 1E−16, χ 2 -test).
This overlap is highly significant ( P -value <10 −16 , hypergeometric test where the intersection is 9000 between 700 000 conserved islands and 60 000 DHSs, assuming a total of 30 000 000 potential loci), consistent with the idea that sequence conservation at overlapping unannotated conserved island/DHS loci reflects the importance of regulatory factor binding to DNA.
The correlation between HNRNPK binding events and nuclear enrichment was highly significant when controlling for transcript length and expression levels (R=0.2, P<10 -16 in HepG2 cells and R=0.07, P<10 -16 in K562 cells).
The overall PPI enrichment was highly significant ( p -value < 1.0e-16).
Acquisition and analysis of intersection targets of ROSA and CHIKV- The PPI analysis of the CHIKV disease target network revealed a total of 502 nodes and 1,386 edges, with a highly significant p-value of < 1.0e-16 ( Figure 2A ).
The difference of the average log2-scaled metformin levels in blood between both groups was highly significant ( p < 10 −16 ).
The expected number of edges is 393 and has a PPI enrichment p -value was highly significant ( p < 10 −16 ).
All were highly significant ( p < 10 –16 for all chromosomes after Bonferroni correction), with over 96% of the variation in the F5 position being explained by the F2 position for every chromosome tested ( Figure 2 ).
PPI enrichment analysis was highly significant (P < 1.0e-16; Fig 5B ), indicating that the observed interaction density was greater than expected by chance and suggesting coordinated involvement of these genes in bladder cancer–related pathways.
We do detect a highly significant enrichment of marine-freshwater differentially expressed genes, as predicted ( P < 10 −16 ).
The perfect association of the haplotype was highly significant (p<10 −16 ).
The difference in degree of nucleotide conservation between the IDR and the remainder of the molecule is highly significant ( P <10 −16 ), and indicates a dramatically higher level of divergence for the IDR-encoding portion of the mammalian TS transcript.
This enrichment in interactions was further supported by a highly significant PPI enrichment p -value of <1.0 × 10 −16 , indicating that the proteins in our network have more interactions among themselves.
Figure 4 puts the predicted ratios in the context of the training ratios, and Table S8 of the Supporting Information quantifies their correlations, elucidating a variety of trends: (1) no_resampling shows a positive trend between the training and the predicted ratio (Pearson’s r 95% CI: [0.440, 0.496], p < 10 –16 ), but since the training and the test ratio are also positively correlated ( Figure 3 ), the latter could be the one driving the predicted ratio of positives; (2) resampling_after_clustering had a constant
To validate the biological significance of this manually compiled pathway, we applied STRING protein–protein interaction enrichment analysis, which confirmed highly significant interaction for the RORC consensus pathway (expected number of edges: 11, observed number of edges: 83, enrichment p < 10 −16 ).
In contrast, highly significant differences were observed between promoter usage in ΔCTCF-HPV18 episomes compared to HPV18 following keratinocyte differentiation (p < 1E-16).
Consistent with this structure, the STRING PPI enrichment analysis was highly significant (p < 1 × 10 −16 ), supporting the conclusion that these proteins form a biologically coherent interaction network rather than a random assembly ( Figure 9 ).