On 29.04.2011 09:01, mimato wrote:
I want to classify bipolar neurons in human cochleas and have data of the
following structure:

Vol_Nuc Vol_Soma
1   186.23   731.96
2   204.58  4370.96
3   539.98  7344.86
4   477.71  6939.28
5   421.22  5588.53
6   276.61  1017.05
7   392.28  6392.32
8   424.43  6190.13
9   256.41  3850.51
10  249.17  3118.14
11  276.97  3037.29
12  295.30  3703.76
13  314.43  5265.97
14  301.15  5781.73

I already worked with Matlab (I´m not a programmer) and created nice
colourcoded dendrograms and also made some verifications of them. I started
now working with R and bootstrapped data with a library named pvclust. It
worked and R computed ...

here is the code:

library(pvclust)

data =
data.frame(Vol_Nuk=c(186.23,204.58,539.98,477.71,421.22,276.61,392.28,424.43,256.41,249.17,276.97,295.3,314.43,301.15),
Vol_Soma=c(731.96,4370.96,7344.86,6939.28,5588.53,1017.05,6392.32,6190.13,3850.51,3118.14,3037.29,3703.76,5265.97,5781.73))

plot(data)
result<-pvclust(data,nboot=100)
plot(result)

It is also not working using following commands:

cluster.bootstrap<- pvclust(Raw, nboot=1000, method.dist="abscor")
plot(cluster.bootstrap)
pvrect(cluster.bootstrap)

I always get the following problem:

mistake in plot.hclust(x$hclust, main = main, sub = sub, xlab = xlab, col =
col,  :
invalid input for Dendrogram

Does anyone has an idea whats wrong...


Yes: You have only 2 variables and when clustering these 2 variables it makes no sense to plot this. My I guess you want to cluster observations rather than variables? Then transpose your data before applying pvclust.

Best,
Uwe Ligges



Thanks a lot!!

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