“highly significant”

These tests were all found to be statistically highly significant, with p < 2.2 × 10 −16 .

In both cases the difference in expression level was highly significant ( p < 2.2e-16) indicating that the coverage of those genes was too low for an assembly of at least 55% in one species.

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).

The sequencing data showed highly significant expression correlation with the array data ( R = 0.88, p < 2.2 × 10 −16 ) for 101 genes whose expression was significantly altered in KO mouse (Table S3 and Figure S8 ).

The P2′ statistic was found to be highly significant across the 57 X substitution lines ( P = 2.2 × 10 −16 ), thus indicating that genotype has an effect on the variation seen for the proportion of progeny sired by the experimental X chromosome male when he is the second to mate.

This deviation from the expected distribution is highly significant by chi-square analysis ( P value = 2.2 × 10 -16 ).

all clusters, and highly significant p-values for both directions (lesser and greater, p-value < 2.2e-16) are recorded.

This revealed a highly significant agreement of the number of events between paired replicates (Supplementary Fig. 2b , Pearson's correlation 0.997, n = 30, two-sided, p value < 2.2e−16), indicating that uvCLAP events capture the amount of pulled down RNA exceptionally well.

The results indicated highly significant Pearson correlation coefficients of −0.82, −0.68, −0.78, and − 0.71, respectively, with P -values < 2.2e-16 ( Fig. 3B-E ).

8 A–D, GSTO1 expression is significantly elevated in tumor tissues compared to normal tissues across several datasets (E_MTAB_8588, GSE42743 , and TCGA_HNSC), with highly significant p-values (p < 2.2e–16, p = 7.3e–08, and p < 2.2e–16, respectively).

Among these were 20.0% of the genes upregulated in XY° males (993 out of 4973) versus 40.8% of the genes upregulated in XX females (3856 out of 9472) in at least one developmental stage (FDR < 0.05), a highly significant difference ( χ 2 = 330.0, p < 2.2e−16).

That is, traits within a group (e.g., both traits related to pigment level) are more highly significant (p < 2.2e-16 to 0.11, average p = 0.0041) than the significance is of correlations between groups (e.g., one trait is pigment level and another is patterning, p = 4e-13 to 0.99, average p = 0.148) ( S4 Table ).

A modest, but highly significant, increase in circRNA size was also observed, again consistent with the ESC retinal model ( Fig. 8 C, P <2.2E-16, Jonckheere-Terpstra test).

We observed a highly significant gain of methylation with age at the locus in the LBC cohort, validating our approach (Fig. 1 a, T-test, p < 2.2 × 10 −16 ).

The overlap is very highly significant (Fisher’s Exact Test: Odds Ratio: 9.38; p-value < 2.2e-16).

Further, the concordance of miRNA expression (log normalized) of the common miRNAs was also explored by Spearman correlation and showed a highly significant correlation with rho of 0.81, p<2.2x10 -16 ( Fig 4b ).

The overlap between CNM genes and genes correlated with aging was highly significant (p < 2.2 × 10 –16 , Fisher’s exact test).

The correlation of the concentrations determined by 1 H-NMR and by quantitative methods were highly significant for both the samples of ccDMEM (Pearson: r = 0.99, p = 2.20 * 10 −16 ) and of vcDMEM (Pearson: r = 0.91, p = 2.84 * 10 −6 ).

Their overlap of 306 genes is highly significant (Fisher’s exact test p-value < 2.2e-16).

Consistent with previous reports ( Vetter et al., 2004 ), there were highly significant differences in both impedance magnitude ( Figure 5B : χ 2 = 311.86, p < 2.2 × 10 −16 , df = 8; Kruskal–Wallis test) and phase angle ( Figure 5C : χ 2 = 164.72, p < 2.2 × 10 –16 , df = 8; Kruskal–Wallis test) during the first WPI.

There was, however, a highly significant correlation between change in TE score and GC content (Pearson’s correlation value of −0.1337, p-value<2.2e −16 ) ( Figure 1I ).

This reduction was highly significant with a p -value < 2.2 × 10 −16 ( Figure 2 ).

Finally, we observed a highly significant increase (one-sided Student’s t -test, p = 2.2 × 10 −16 ) in average epistasis values in the winning CR genotypes compared with the overall population, indicating that positive epistasis plays an important role in determining the fittest genotypes in this selection (Fig. 5b ).

For all three species comparisons, a linear regression of %ID and log 2 hybridization ratio showed a strong and highly significant correlation ( D. sechellia : Multiple R 2 = 0.3257, P < 2.2e-16; D. simulans : Multiple R 2 = 0.2920, P < 2.2e-16; D. yakuba : Multiple R 2 = 0.4083, P < 2.2e-16) (Figure 2 ), with the data for D. yakuba showing the strongest correlation.

By linear regression analysis, the correlation between the two are highly significant (Spearman's rank correlation = 0.83, P-value <2.2×10 −16 ).