You might try posting on the Bioconductor list instead. They might
have more suitable tools for what you are trying to do. It shoudn't
hurt to ask, anyway ...
If you do this and find something there that better meets your needs,
please post back that information to this list so that others don't
waste time on your query here.
Cheers,
Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Wed, Dec 23, 2015 at 1:30 PM, Tahani Libya <libya.tahani at gmail.com>
wrote:> *Hi,*
>
> *while I try to analysis my data as the following ,I faced some problem
> with (heatmap()):*
>
>
>> dat<-ReadAffy()
>> dat
>
>
> AffyBatch object
> size of arrays=1164x1164 features (20 kb)
> cdf=HG-U133_Plus_2 (54675 affyids)
> number of samples=10
> number of genes=54675
> annotation=hgu133plus2
> notes>> dat2<-rma(dat)
> Background correcting
> Normalizing
> Calculating Expression
>> dat.m<-exprs(dat2)
>
> *The normalized data can be so large that clustering all the genes (or*
> *arrays) becomes impossible. Clustering about 23000 genes takes about 1GB
> of memory, and clustering 54675 genes would consume about more than 4 GBs
> ofmemory, and would not be feasible on a standard Windows workstation.*
>
> *So I tried to sample the data, and this sample*
> *is then clustered. This should convey approximately the same information
> asthe clustering of the whole dataset:*
>> n<-1:nrow(dat.m)
>> n.s<-sample(n, nrow(dat.m)*0.1)
>> dat.sample<-dat.m[n.s,]
>> library(amap)
>> clust.genes<-hcluster(x=dat.sample, method="pearson",
> + link="average")
>> clust.arrays<-hcluster(x=t(dat.sample), method="pearson",
> + link="average")
>
> *The sample size is here 10% of the original dataset.*
>
> Ok, then I tried to visualizing the clustering results as a heatmap:
>> heatcol<-colorRampPalette(c("Green", "Red"))(32)
>> heatmap(x=as.matrix(dat.m), Rowv=as.dendrogram(clust.genes),
> + Colv=as.dendrogram(clust.arrays), col=heatcol)
>
> *Error in .heatmap(x=as.matrix(dat.m),
> Rowv=as.dendrogram(clust.genes), :**row dendrogram ordering gave
> **index of wrong length*
>
> *Was that sample of the data make an error with heatmap()??*
>
> *Cheers,*
>
> *Tahani.*
>
> [[alternative HTML version deleted]]
>
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