Estimate Genewise Dispersions from Exon-Level Count Data
Estimate a dispersion value for each gene from exon-level count data by collapsing exons into the genes to which they belong.
estimateExonGenewiseDisp(y, geneID, group=NULL)
y |
either a matrix of exon-level counts or a |
geneID |
vector of length equal to the number of rows of |
group |
factor supplying the experimental group/condition to which each sample (column of |
This function can be used to compute genewise dispersion estimates (for an experiment with a one-way, or multiple group, layout) from exon-level count data. estimateCommonDisp
and estimateTagwiseDisp
are used to do the computation and estimation, and the default arguments for those functions are used.
estimateExonGenewiseDisp
returns a vector of genewise dispersion estimates, one for each unique geneID
.
Davis McCarthy, Gordon Smyth
estimateCommonDisp
and related functions for estimating the dispersion parameter for the negative binomial model.
# generate exon counts from NB, create list object y<-matrix(rnbinom(40,size=1,mu=10),nrow=10) d<-DGEList(counts=y,group=rep(1:2,each=2)) genes <- rep(c("gene.1","gene.2"), each=5) estimateExonGenewiseDisp(d, genes)
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