Description Usage Arguments Details Value Author(s) See Also

Function to do a one-sided hypergeometric test, i.e. calculate the probability to draw more or less (expectation value smaller than observed number of successes respectively expectation value greater than observed number of successes) than a certain number of successes (ObservedNrOfAnnsInTerm) in a fixed number of draws (NrOfGenesInSample), without replacement, from a finite population of fixed size (NrOfGenesInUniverse) that contains a known number of successes (NrOfAnnotationsInTerm), wherein each draw is either a success or a failure.

1 2 3 | ```
hypergeoTest(ObservedNrOfAnnsInTerm, NrOfAnnotationsInTerm, NrOfGenesInSample,
NrOfGenesInUniverse, LogPvalues = TRUE)
``` |

`ObservedNrOfAnnsInTerm` |
Numeric; Vector of observed numbers of input genes annotated to one GO term. |

`NrOfAnnotationsInTerm` |
Numeric; Vector of numbers of all genes annotated to one GO term. |

`NrOfGenesInSample` |
Numeric; The number of input genes (genes of interest in sample) annotated to at least one GO term. |

`NrOfGenesInUniverse` |
Numeric; The number of genes in universe, i.e. all genes annotated to at least one GO term. |

`LogPvalues` |
Boolean; Default: TRUE Set TRUE if -log(p-values) should be calculated. Set FALSE if non-transformed p-values should be returned. |

Hypergeometric test is done one-sided depending on `ExpectedNrOfAnnsInTerm`

:
If the expected number of genes annotated to one GO term is less than
ObservedNrOfAnnsInTerm, the log-p-value will be log(P(X>=ObservedNrOfAnnsInTerm))
where X is the hypergeometric distributed random variable.
If the expected number of genes annotated to one GO term is greater than
ObservedNrOfAnnsInTerm, thelog-p-value will be log(P(X<ObservedNrOfAnnsInTerm))
where X is the hypergeometric distributed random variable.

`LogPvalues` |
Numeric; Vector of log-p-values of one-sided hypergeometric test. |

CL

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