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For this reason the computational complexity of RS-SNP is proportional only to the number of column permutations required, that is equal to the inverse of the minimum observable P-value.
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The adjusted p-value for each SNP is the percentage of permutations with the observed p-value ≥ the minimum permuted p-value and takes into account the different number of SNPs per gene.
For each permutation, we recorded the minimum permuted p-value among the N permuted p-values for a gene and compared the observed p-values to the minimum p-value obtained from the permutation to adjust for multiple testing.
Y axis is minimum Fisher p-value in the H3K9me2- or H3K27me3-marked genes.
In each permutation, the minimum P-value is compared to the minimum P-value over all the analyses in the original data.
Both the minimum p-value for all tagging SNPs within the gene and minimum false discover rate (FDR) adjusted p-values for the three SNP haplowalk sliding window for VDR and RXRA were significantly associated with RCC risk.
Meanwhile, γ is demonstrated to be the most significant variable for the minimum p-value.
Again we used the minimum p-value approach described above in assigning p-values to genes with multiple probe sets.
For genes with an EV occurrence = 6/6 a minimum p-value of 10−6 can be reached.
For any candidate module, we utilize the minimum p-value for 1, 2,.., k.
In each permutation, we used the minimum p-value approach described above to assign p-values to genes with multiple probe sets.
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