plotPosteriors: Plots the posterior likelihoods estimated for a 'countData'...

In baySeq: Empirical Bayesian analysis of patterns of differential expression in count data

Description

This function plots the posterior likelihoods estimated for a 'countData' object against the log-ratios observed between two sets of sample data. For those data where the log-ratio is infinite (because in one set of sample data all observed counts are zero), we plot instead the log-values of the other group.

Usage

plotPosteriors(cD, group, samplesA, samplesB, ...)

Arguments

cD	A countData object, for which posterior likelihoods have been estimated (see getPosteriors).
group	From which group (as defined in the 'cD@groups' slot) should posterior likelihoods be shown? Can be defined either as the number of the element in 'cD@groups' or as a string which will be partially matched to the names of the 'cD@groups' elements.
samplesA	A numerical vector giving the columns of data in the 'countData' object that forms sample set A.
samplesB	A numerical vector giving the columns of data in the 'countData' object that forms sample set B.
...	Any other parameters to be passed to the plot function.

Value

Plotting function.

Author(s)

Thomas J. Hardcastle

See Also

getPosteriors

Examples

# We load in a `countData' object containing the estimated posterior
# likelihoods of expression (see `getLikelihoods').

data(CDPost)

plotPosteriors(CDPost, group = "DE", samplesA = 1:5, samplesB = 6:10)

# equivalent to plotPosteriors(CDPost, group = 2, samplesA = 1:5, samplesB = 6:10)

baySeq documentation built on Nov. 8, 2020, 5:43 p.m.