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For each of 10,000 such permuted samples, we computed the mean, over all nuclei, of the distance of each positive signal to the closest one.
For the eight CHAMACOS metabolites with detection frequencies > 50% in both samples, we computed the Spearman's rank correlation between the first and second prenatal samples.
To assess the degree of coverage variability across samples, we computed the standard deviation in coverage for each exon across samples for both custom-designed panel enrichment techniques.
By applying different ceiling ratios for willingness to pay per QALY to these bootstrap samples, we computed the probability of cost-effectiveness at different willingness-to-pay thresholds, and presented results in cost-effectiveness acceptability curves.
For these three sample sets (19,000 DE samples, 19,000 LH samples and 100 LH samples) we computed the acceptance ratios of all 119 experimental strains and sorted them in ascending order, as shown in Figure 8.
To evaluate any potential significance of function abundance differences among samples, we computed D scores for each individual COG as well as D ranks for COG pathways and categories as defined in IMG/M (Markowitz et al. 2008).
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Accordingly, with the K data samples, we compute the MI I(x Q (k, m)) for different m and choose the one that maximizes the MI to be a good estimation of the relative delay (32).
Similarly to the M-EFT, using the predicted global eigenvalue expression (21) considering white Gaussian noise samples, we compute the global threshold coefficients via the hypotheses for the tensor case (23).
Since our analysis comprises 1000 constrained and 1000 unconstrained samples, we compute average values at each quantile and show confidence intervals as shaded areas around the average.
Based on the RMLEs and, we generate B bootstrap samples from the following distribution: for k= T, R and P. For each of the B bootstrap samples, we compute the observed value of statistic T j (j= W, R, L).
After assigning genotypes to all samples, we compute the center and variance of each group in two-dimensions (contrast and average intensity), and obtain a confidence score for each sample.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com