I am interested in fitting bioHMM on some non-array CGH data using the
function runBioHMM. Say I have have a vector, y, of processed
intensity measurements at M SNPs along a chromosome and a vector of
corresponding genomic locations, say pos. How can I use this to run
bio HMM?
Thanks for any help,
Stacey
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You will have to create a SegList object in order to do this, for the
runBioHMM() function a SegList needs to have the following components
M.observed: a matrix with the copynumber values samples in columns,
probes in rows
genes: A data.frame with at list a Chr and a Position column
Make sure that the data is already ordered by chromosome and position
# example code starting with vectors of cn.data, chromosome and
# base.position
Idx<-order(chromosome,base.position)
segList<-list()
observed<- matrix(cn.data[Idx],ncol=1)
colnames(observed)<-"sample1"
segList$M.observed <- observed
segList$genes <-
data.frame(Chr=chromosome[Idx],Position=base.position[Idx])
segList<-new("SegList", segList)
result<-runBioHMM(segList)
Jan
> I am interested in fitting bioHMM on some non-array CGH data using
the
> function runBioHMM. Say I have have a vector, y, of processed
intensity
> measurements at M SNPs along a chromosome and a vector of
corresponding
> genomic locations, say pos. How can I use this to run bio HMM?
>
