approx.expected.info {edgeR}R Documentation

Approximate of expected information (Fisher information)

Description

Using a linear fit (for simplicity), the expected information from the conditional log likelihood of the dispersion parameter of the negative binomial is calculated over all genes.

Usage

 
approx.expected.info(object, d, qA, robust = FALSE) 

Arguments

object DGEList object containing the raw data with elements data (table of counts), group (vector indicating group) and lib.size (vector of library sizes)
d delta parameter for negative binomial - phi/(phi+1)
qA list from output of quantileAdjust
robust logical on whether to use a robust fit, default FALSE

Value

vector of Fisher information approximates (with length same as the number of rows of the original data)

Author(s)

Mark Robinson

Examples

set.seed(0)
y<-matrix(rnbinom(40,size=1,mu=10),ncol=4)
d<-list(data=y,group=rep(1:2,each=2),lib.size=rep(c(1000:1001),2))
qA<-quantileAdjust(d,alpha=100)
exp.inf<-approx.expected.info(d,1/(1 + qA$r[1]),qA)

[Package edgeR version 1.0.4 Index]