compareCountDist {tweeDEseq} | R Documentation |
Compares the empirical and estimated distributions for different count data models
compareCountDist(x, plot=TRUE, ...)
x |
numeric vector containing the read counts. |
plot |
If |
... |
Further arguments to be passed to the plot function. |
This function serves the purpose of comparing a empirical distribution of counts with three Poisson-Tweedie distributions arising from estimating mean, dispersion and setting a=1 for comparing against a Poisson, a=0 for comparing against a negative binomial and estimating the shape parameter a from data too. The legend shows the values of the a parameter and the P-value of the likelihood ratio test on whether the expression profile follows a negative binomial distribution (H_0:a=0).
List with the following components:
a |
shape parameter estimated from the input data |
p.value |
P-value for the test that the data follows a negative binomial distribution, i.e., H_0:a=0. |
Esnaola M, Puig P, Gonzalez D, Castelo R and Gonzalez JR (2013). A flexible count data model to fit the wide diversity of expression profiles arising from extensively replicated RNA-seq experiments. BMC Bioinformatics 14: 254
# Generate 500 random counts following a Poisson Inverse Gaussian # distribution with mean = 20 and dispersion = 5 randomCounts <- rPT(n = 500, mu = 20, D = 5, a = 0.5) xx <- compareCountDist(randomCounts, plot=FALSE) xx