estimatePs {edgeR} | R Documentation |
Estimate expression levels (i.e. proportion of all sample mRNA corresponding to each tag; or, concentration of mRNA for each tag in sample mRNA) using maximum likelihood with dispersion parameter fixed based on the negative binomial model for each tag/gene and sample group. Expression proportions are used to determine overall abundance of each tag/gene and differential expression of tags/genes between groups.
estimatePs(object, r, tol = 1e-10, maxit = 30)
object |
list containing (at least) the elements |
r |
numeric vector providing the size parameter of negative binomial model ( |
tol |
numeric scalar, tolerance between iterations |
maxit |
positive integer scalar, maximum number of iterations |
The Newton-Raphson method is used to calculate iteratively the maximum likelihood estimate of the expression level (i.e. concentration of mRNA for a particular tag in the sample mRNA) for each tag/gene.
A list with elements:
conc.common |
numeric vector giving overall proportion/concentration for each tag |
conc.group |
numeric matrix with columns giving estimates of tag/gene concentrations (proportion of total RNA for that group that that particular tag/gene contributes) for different groups) |
Mark Robinson, Davis McCarthy
set.seed(0) y<-matrix(rnbinom(40,size=1,mu=10),ncol=4) d<-DGEList(counts=y,group=rep(1:2,each=2),lib.size=rep(c(1000:1001),2)) conc<-estimatePs(d,r=1)