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
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.