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The missing β-values were caused by probes with only a few good quality bead-level replicates, for which therefore no β-values were reported.
Outlying replicates for each spot were identified as those replicates for which exclusion from the analysis reduced the standard deviation of the log2-ratio values by at least 0.2 units: a maximum of one outlying replicate was excluded per gene.
When focusing only on the replicates for which the control data set did not display a significant heterozygosity excess (i.e., replicates 1, 4, and 5), only 4 out of 6 bottleneck events were detected.
In the replicates for which the pre-bottleneck laboratory-cultured populations did not significantly depart from a mutation/drift equilibrium, an important assumption of the program Bottleneck, only a portion of the bottleneck events were detected.
For each simulation, these type I error rates are the proportion of replicates for which the computed LRTS exceeds 0.2157, 6.25, 7.81, 9.348 or 11.34, which correspond to the 0.975, 0.10, 0.05, 0.025 and 0.01 significance level cutoffs for a central chi-square distribution with 3 degrees of freedom (the asymptotic null distribution for each simulation).
For the chromosomes 3 and 9 linkage peaks, respectively, we observed 36 and 53 distinct genomic locations among 1000 sets of replicates for which a LOD score in any age category met or exceeded the observed scores, resulting in corresponding empirical P values of 0.037 [upper 95% confidence limit 0.048] and 0.054 [upper 95% confidence limit 0.067].
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A replicate spot for which either channel was flagged as poor quality was excluded from these calculations.
A similar pattern emerged for the frequency of variant occurrences (i.e., the total number of times, sequence changes were found across all replicate populations), for which 131 out of 139 cases fell into CDSs (table 1).
For each model, we recorded the proportion of replicates of data for which the P-value of each test was less than a 5% significance threshold.
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For large numbers of simulation replicates, the proportion of the replicates in each bin for which the one-divergence model is true will approximate the probability that the one-divergence model is the correct model.
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CEO of Professional Science Editing for Scientists @ prosciediting.com