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However, they used permutations of variables and distinguished between the first and the last variables.
In this paper, we develop efficient parallel algorithms for some commonly used permutations namely, bit reversal, vector reversal, perfect shuffle, unshuffle and transpose on the OMULT network.
Secondly, we used permutations to establish stringent genome-wide thresholds for declaring significant association for each phenotype.
We used permutations to estimate false discovery rates (FDRs) for the modified t-statistics obtained from the frozen tissue and FFPET for 3SEQ and HEEBO, as described in [52].
We used permutations of histone modifications which showed concordant marking biases in K562 cells in either expressed or non-expressed genes (H3K36me3 followed by H3K27me1 - both favoring exons of expressed genes; H3K27me3 followed by H3K36me1 - both favoring exons of non-expressed genes).
We used permutations to look for a geographical structure of cultivated or original alleles, i.e. to detect if some alleles were more geographically clustered than expected at random.
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Secondary analysis used permutation approaches.
To assess the statistical significance of the LTOCV results, we used permutation tests [ 41, 42].
In addition, we also used permutation-based tests to exclude the possibility of random effect.
For assessment of global significance of the periodicity and expression scores, we used permutation testing.
We used permutation testing to assign P-values to the logistic regression coefficients.
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