computeVPC.CP: Calculate the compound Poisson (CP) variance partition...

In HeritSeq: Heritability of Gene Expression for Next-Generation Sequencing

Description

Calculate the CP VPC for one or more features following the model fitting function fit.CP().

Usage

computeVPC.CP(para)

Arguments

para	A G x 4 matrix of CP fit parameters for G features, G≥q 1. The column order is intercept α_g, random effect σ_g^2 (σ_g^2≥q0), tweedie parameter p_g (1<p_g<2), and dispersion φ (φ>0).

Value

A G x 1 matrix consisting of VPC for G features based on compound Poisson mixed models. Column name is "CP-fit"; row names are the feature names.

Examples

## Compute VPC for each feature under compound Poisson mixed models. 
vpc.cp <- computeVPC.CP(para_cp) 

## Visulize the distribution of the VPCs. 
hist(vpc.cp, breaks = 50, col = "cyan")

## Plot sorted VPCs.
plot(sort(vpc.cp), ylab = "Heritability (h2)", ylim = c(0,1), main = "Sorted CP VPC scores")
abline(h = 0.9, lty = 2, col = "red")
text(50, 0.92, "h2 = 0.9", col = "red")

HeritSeq documentation built on July 13, 2021, 1:06 a.m.