tweeDExact: Exact test for differences between two Poisson-Tweedie groups

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/tweeDExact.R

Description

Carry out an exact test for differences between two Poisson-Tweedie populations.

Usage

1
2
tweeDExact(counts, group, tol = 1e-15, mc.cores = 1)
exactTestPT(counts, group, tol = 1e-15, threshold = 150e3)

Arguments

counts

The RNA-seq counts. An object of type 'matrix' or 'data.frame' for 'tweeDExact', or an object of type 'vector' for 'exactTest'.

group

vector giving the experimental group/condition for each sample/library.

tol

Tolerance for the Poisson-Tweedie probability computations. The probabilities under the 'tol' value will automatically considered as 0.

threshold

an integer (default is 50e3). If the sum of all counts in a certain gene excedes this value 'testPoissonTweedie' will be called instead of 'exactTest'. Larger values will result in a longer computing time.

mc.cores

number of cpu cores to be used. This option is only available when the 'multicore' package is installed and loaded first. In such a case, if the default value of 'mc.cores=1' is not changed, all available cores will be used.

Details

'exactTest' performs the exact test for a vector of counts.

'tweeDExact' performs the test for a whole 'data.frame'. The P-values are then corrected using the Benjamini and Hochberg method.

Value

'exactTest' returns the p-value resulting from the exact test between two different Poisson-Tweedie populations, as well as the method that was used to compute it.

'tweeDExact' returns a 'data.frame'. Each row corresponds to a gene and it contains the following information:

- In the first columns the mean of counts in each of the subgroups.

- In the third column the p-value of the test for differential expression between the two subgroups.

- In the fourth column the p-value corrected for multiple comparisons using the Benjamini-Hochberg FDR procedure.

- In the last (fifth) column the method that was used to compute the p-value.

Author(s)

Mikel Esnaola

References

P. Hougaard, M.L. Ting Lee, and G.A. Whitmore (1997). Analysis of overdispersed count data by mixtures of poisson variables and poisson processes. Biometrics 53, pages 1225-1238.

See Also

testPoissonTweedie tweeDExact

Examples

1
2
3
counts <- matrix(rPT(n = 1000, a = 0.5, mu = 10, D = 5), ncol = 40)

tweeDExact(counts, group = rep(c(1,2),20))

tweeDEseq documentation built on May 2, 2018, 4:44 a.m.