There were no significant associations between SNPs and oil content in the Q, P + K models based on threshold −log10(p) = 5.7, which might indicate false negatives in this analysis.
Discussed TEAM model was based on threshold currents, whereas VTEAM is based on threshold voltages.
Activation within these regions was analysed using non-parametric permutation tests (RANDOMISE, http://www.fmrib.ox.ac.uk/fsl/randomise/, version 2.9) inference based on threshold-free cluster enhancement and FWE-corrected p < 0.05 (with default parameters H = 2, E = 0.5; [62]).
Differentially expressed genes have been selected based on a threshold p-value of 10−4.
The variables relevant to the models were selected from the univariate FACIT-F total score analysis, based on a threshold p-value ≤0.20 (gender, age group, marital status, depression, anxiety, and baseline QOL level).
Simple interval mapping was used for an initial genome wide scan to select significant candidate QTLs based on the threshold [−log10(p value)], and the ones having the highest [−log10(p value)] were selected as cofactors, then several rounds of composite interval mapping (CIM) were done until no new QTLs were detected.
This conclusion was based on the Bonferroni threshold (p = 0.05/3 = 0.017) for controlling a family wise error rate at 0.05.
The stepwise incorporation and exclusion of markers were based on predefined alpha threshold (p).
We identified three loci that were significantly differentially methylated in relation to blood arsenic concentration based on the Bonferroni threshold p < 1 × 10 7, as shown in Figure 1.
In the present study, we observed no overlap between our top 35 differentially methylated loci and the top signals previously reported for other arsenic-related traits among studies that used the Illumina methylation array, although none of these prior studies identified statistically differentially methylated loci based on a Bonferroni threshold (p < 1 × 10 7).
