Sentence examples for by the hypergeometric probability from inspiring English sources

Under the hypothesis that the articles i and j cite, respectively, (d_{i}) and (d_{j}) distinct elements uniformly at random from (S^{k}_{B}), the probability that they select the same X articles is given by the hypergeometric probability function: mathcal{P}bigl(X | N_{B}^{k},d_{i},d_{j}bigr) = frac{{{d_{i}}choose {X}} {{N_{B}^{k}-d_{i}}choose {d_{j} - X}}}{{{N_{B}^{k}}choose {d_{j}}}}.

Those observations allow us to confirm in an alternative and independent manner the reassortment events predicted by the hypergeometric probability analysis.

For each signature hub, we detected pathways enriched with its interaction neighbours by the hypergeometric probability model [ 67].

This is done by using the hypergeometric probability density function.

To achieve this, we evaluate the disease correlation by calculating the hypergeometric probability of corresponding pathway profiles: a method that has been successfully applied to calculate the correlation between phylogenetic profiles in our previous study [ 65].

The calculated p-value, which measures the significance of deviation from the null hypothesis that the gene is not differentially expressed, is computed exactly by using the hypergeometric probability of observed or more extreme differences while keeping the marginal sums in the contingency table unchanged.

Test of this null assumption was performed by calculating statistical significance of the hypergeometric probability as follows.

If we set an FDR = 0.05, we eliminate all pathways for which the hypergeometric probability exceeds 0.05 divided by the number of pathways to which genes were assigned.

The hypergeometric probability of this overlap occurring by chance is <1.40 × 10−7.

In a particular pathway, if n1 genes are identified by TCGA data, and n2 by AGS (all at nominal p < 0.001), we calculate the hypergeometric probability of finding at least n genes (the observed number) common to the two sets.

Using the hypergeometric probability distribution, pro b m i f is given by the following formula.