plotPriors: Plots the density of the log values estimated for the mean rate in the prior data for the Negative Binomial approach to detecting differential expression

Description

This function plots the density of the log values estimated for the mean rate in the data used to estimate a prior distribution for data under the assumption of a Negative Binomial distribution. This function is useful for looking for bimodality of the distributions, and thus determining whether we should try and identify data with no true expression.

Usage

plotPriors(cD, group, par = 1)

Arguments

countData object, for which priors have been estimated using the assumption of a Negative Binomial distribution (see getPriors.NB).

group

Which group should we plot the priors for? In general, should be the group that defines non-differentially expressed data. 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.

par

The parameter of the prior that will be plotted.

Value

Plotting function.

Details

If the plot of the data appears bimodal, then it may be sensible to try and look for data with no true expression by using the option nullPosts = TRUE in getLikelihoods.NB.

Examples

Run this code


# We load in a `countData' object containing the estimated priors (see `getPriors').

data(CDPriors)

plotPriors(CDPriors, group = "NDE", par = 1)