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We used a hypergeometric distribution with a P value threshold of 0.05 to test for statistical significance.
To associate tissues and phenotypes based on gene expression and phenotype data, we used a hypergeometric distribution as well as the association rule mining.
Under the assumption that functionally related miRNAs tend to be associated with phenotypically similar diseases [ 4], Jiang et al. [ 5] used a hypergeometric distribution to construct a miRNA functional network and used phenotype similarity information to infer potential miRNA-disease associations.
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Commonly enriched GO terms among mRNAs associated with selected proteins were retrieved with the GO Term Finder that uses a hypergeometric distribution with Multiple Hypothesis Correction to calculate p-values (SGD; www.yeastgenome.org).org
We use a hypergeometric distribution to obtain the significance level of a key term; that is, for each key term appearing in the initial document set with a frequency greater than the expected frequency based on the whole MEDLINE database, the Recent engine calculates the occurrence probability of that number of times the key term appears.
Using a hypergeometric distribution and after Bonferroni correction only human homologues in SINE-free regions as detected by RT-PCR from late development (Theiler stages 10, 11, 13, 15 22, 24 26 & 28) were found to be expressed significantly higher than expected by chance (not shown).
Calculations were performed using a hypergeometric distribution.
Gene enrichment was calculated using a hypergeometric distribution [ 32].
The significance of gene list overlaps was calculated using a hypergeometric distribution test.
Transcription factor target and motif enrichment significance were calculated using a hypergeometric distribution test.
Functional enrichment is tested from this contingency table using a hypergeometric distribution.
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