Sentence examples for deviation from random distribution from inspiring English sources

Since we expect sequences related to a specific biological conclusion be distributed relatively evenly across the sequencing assay surface, any significant deviation from random distribution, either at the full sample overview or at the all tile/panel summary view, will suggest the involvement of sequencing quality issues.

To overcome these limitations we used an alternative approach where we compared the frequency of changed genes and their contribution to deviation from random distributions on the targeted chromosome with other chromosomes (see Materials and Methods).

Individual-based null models were used to identify deviations from random distribution across the three spatial scales.

These curves showed no evidence of deviations from random distributions, indicating that the assumption of the model was not violated (data not shown).

No deviation from a random distribution was seen in children from any transmission region when all species (P.

Monte Carlo procedure was used to test the significance of deviation from a random distribution at 95% upper and lower confidence envelops, generating 10,000 replications.

In this case, when plotting the distribution of Trl true positive real binding sites against the total number of computational predictions, the curve reaches the maximum deviation from the random distribution between 0.40 0.60 (see Additional file 8, top).

The G-test for goodness of fit detected a highly significant deviation from a random distribution (G (9) = 61.55; p < 0.001), with all but O7 chromosome segments covered by inversions having a higher than expected number of genes.

The frequency of genes with TFBS to a given TF was then compared between the lists of regulated and non-regulated genes to statistically assess any deviation from a random distribution (P < 0.05, z-test).

Third, we calculated the deviation from a random distribution with Nonac's binomial skew index, or B index (Nonacs 2000, 2003), which allowed us to investigate male skew independently of male dominance hierarchy.

For orthologs to genes that contribute the most to growth there was also a strong over-representation on the large chromosome while orthologs to the least growth contributing genes did not display a significant deviation from a random distribution between the chromosomes.