The p-value for the enrichment test from hypergeometric distribution of the random variable ρ is calculated from the cumulative probability of observing at least ρ i out of ρ i + ρ j times.
For this test, the hypergeometric distribution was used to determine, for each population, whether the observed value of n1* was significantly large, given the null scenario in which a random sample of n1*+n2* transcripts are chosen from all those evaluated on the array platform.
For statistical testing, the hypergeometric distribution was used to test for the probability that a specific set of genes is annotated with the same GO term by considering the background distribution of GO terms (Rivals et al., 2007).
In order to test for overrepresentation of GO terms among our two protein data sets, we applied a test in hypergeometric distribution as implemented in the Cytoscape plugin BINGO [31].
We used Fisher's exact right-side test based on hypergeometric distribution and corrected for multiplicity testing by the Bonferroni method.
To correct for multiple hypothesis testing, the hypergeometric distribution with Bonferroni correction is used in the DiRE tool [ 106].
Fisher's exact test of the hypergeometric distribution was calculated and correction for multiple comparisons was performed using the Benjamini-Hochberg procedure [ 58].
This test follows the hypergeometric distribution and the GOToolBox allows for FDR correction, pointing at statistically relevant over- or underrepresented terms within a dataset.
Enrichment analysis on metabolic pathways was calculated for each dataset using Fisher exact test based on hypergeometric distribution with a p-value cutoff of 0.1.
We use Fisher's exact test with the hypergeometric distribution.
