Conditional Log-Likelihoods in Terms of Delta
Common conditional log-likelihood parameterized in terms of delta (phi / (phi+1))
commonCondLogLikDerDelta(y, delta, der = 0)
y |
list with elements comprising the matrices of count data (or pseudocounts) for the different groups |
delta |
delta ( |
der |
derivative, either 0 (the function), 1 (first derivative) or 2 (second derivative) |
The common conditional log-likelihood is constructed by summing over all of the individual genewise conditional log-likelihoods. The common conditional log-likelihood is taken as a function of the dispersion parameter (phi), and here parameterized in terms of delta (phi / (phi+1)). The value of delta that maximizes the common conditional log-likelihood is converted back to the phi scale, and this value is the estimate of the common dispersion parameter used by all genes.
numeric scalar of function/derivative evaluated at given delta
Davis McCarthy
estimateCommonDisp is the user-level function for estimating the common dispersion parameter.
counts<-matrix(rnbinom(20,size=1,mu=10),nrow=5) d<-DGEList(counts=counts,group=rep(1:2,each=2),lib.size=rep(c(1000:1001),2)) y<-splitIntoGroups(d) ll1<-commonCondLogLikDerDelta(y,delta=0.5,der=0) ll2<-commonCondLogLikDerDelta(y,delta=0.5,der=1)
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