Sreedevi Gopalan wrote:
we have implemented teh following code for determinging the clustering
model of a dataset.
bicvals <- EMclust( hdata, 7)
sumry1 <- summary(bicvals, hdata,7) # summary object for emclust()
print(sumry1)
This set of code gives the following output
classification table:
1 2 3 4 5 6 7 1 1 1 4 1 1 1 which I think means there is 1 gene in the 1st cluster...1 gene in the
2nd cluster , 4 genes in the 4th cluster and so on....But I need to know
which gene is in which cluster.
Is there any way to find that out....
Here's an example:
R> data(iris) R> irisMatrix <- as.matrix(iris[,1:4]) R> irisBic <- EMclust(irisMatrix) R> irisBest <- summary(irisBic, irisMatrix) R> names(irisBest) [1] "bic" "options" [3] "classification" "uncertainty" [5] "n" "d" [7] "G" "z" [9] "mu" "sigma" [11] "decomp" "pro" [13] "loglik" "Vinv" [15] "modelName" R> irisBest$classification [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [23] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [45] 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 [67] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 [89] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 [111] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 [133] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 R>
Hope this helps,
Sundar
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