Barely Significant
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“marginally significant”

26,083 sentences · 26,083 papers · 36,483 search hits before verification · confirmed specimen

Sighted at

p>=0.1

Listed by Hankins (2013) · Otte et al. (2022)

In the literature

Each line indicates an individual microarray feature that is statistically significant (P < FDR 0.1, black), marginally significant (P < FDR 0.2, solid grey) or not significant (grey dashed) for genes represented by 2 microarray features (A-H), 3 microarray features (I-N) and 8 microarray features (O).
However, while we cannot completely exclude that common variation may contribute to PrCa risk at this locus as data from the ENCODE project suggests some degree of potential functionality for the variants we have identified here, (in particular rs145922598, which remained marginally significant in the conditional regression, is highly conserved, overlaps a DNaseI hypersensitivity site in several cell lines including LNCaP and transcription factor binding sites for FOXA1 and FOXA2 transcription factors ( Table 1 , Figure 1 )); the much stronger evidence for significance for the rare coding variant coupled with the results of our haplotype analyses appear to indicate that this SNP is solely responsible for the detected association signal.
Respondents aged 25 to 34 (OR = 0.34, P < 0.01), those aged 35 to 54 (OR = 0.39, P < 0.01), and those aged 55 and over (OR = 0.40, P = 0.01) were significantly less likely than 18 to 24 year old marijuana users to agree or strongly agree with the statement “In certain situations, I might drive high.” The age groups of 35 to 54 (OR = 0.55, P = 0.08) and 55 and over (OR = 0.51, P = 0.07) were associated with marginally significant decreases in the odds of agreeing or strongly agreeing with the statement “I might drive high even though I know I shouldn’t.” Openness to driving while high was also associated with race/ethnicity.
We first investigated whether infants’ overall fair choice score differed as a function of condition: there was a marginally significant difference in infants’ selection of the fair distributor in the CF/CUF condition (Caucasian Fair / Caucasian Unfair, M = 0.72, SE = 0.05) versus the AF/CUF condition (Asian Fair / Caucasian Unfair, M = 0.57, SE = 0.09), t (34) = 1.50, p = 0.07, d = 0.51.
For green tea, consumption of 120–360 mL/day was significantly associated with a decreased risk of GBC (HR = 0.56; 95% CI, 0.32–0.97), and the association between consumption of >720 mL/day and a decreased risk of GBC was marginally significant (HR = 0.57; 95% CI, 0.32–1.01); additionally, there was a non‐significant trend of decreased EHBDC risk associated with increased volume of consumption ( P ‐trend = 0.160).
Results from an experiment of combining LHS and genetic algorithm (GA) showed that 10 3 of LHS sampling followed by 100 generations of GA optimization yielded a similar set of kinetic motifs for NFBLB (Additional file 1 : Table S1), suggesting that optimization can help to find more solutions from a smaller initial parameter set, but in this case the hybrid approach did not reduce the computational cost (since it also needed a total of 10 5 model evaluations), and could miss some of the marginally significant motifs (Additional file 1 : Table S1).