similar to: "cophenetic" function for objects of class "dendrogram"

Note that cophenetic.default (which works on the output of hclust(dist(X))) uses the row names of X as labels. as.dendrogram.hclust does not retain those row names so cophenetic.dendrogram cannot use them (so it orders them based on the topology of the dendrogram). Bill Dunlap TIBCO Software wdunlap tibco.com On Thu, Apr 21, 2016 at 7:59 AM, William Dunlap <wdunlap at tibco.com> wrote:

I think the results differ only in the order of the labels. The following function puts the labels in a standard order and then the results are the same: canonicalize.dist <- function (distObject) { o <- order(labels(distObject)) as.matrix(distObject)[o, o, drop = FALSE] } identical(canonicalize.dist(d2), canonicalize.dist(d3)) [1] TRUE Bill Dunlap TIBCO Software

Hi, I'm trying to build dendrograms to pass to heatmap(). The dendrograms I build plot properly, but when I pass them to heatmap() I get the error message "row dendrogram ordering gave index of wrong length" (see output log below). I looked in the code of heatmap() and saw that the error was due to a NULL return value from order.dendrogram(), which in turn got a NULL return value

Hello, I analyse some free-sorting data so I use hierarchical clustering. I want to compare my proximity matrix with the tree representation to evalute the fitting. (stress, cophenetic correlation (pearson's correlation)...) "The cophenetic similarity of two objects a and b is defined as the similarity level at wich objects a and b become members of the same cluster during the course of

Hi, I am using the function heatmap(stats) to draw a microarray heatmap, columns are samples and rows are gene features. I did a 2D clustering during the heatmap drawing. The features and samples indeed cluster into several blocks both vertically and horizontally. I can get the index of re-ordered rows and columns after the heatmap drawing by typing the the return variable of the heatmap

I would like to draw horizontal or vertical lines on a heatmap to highlight the clusters at some specified cut depth of the dendrogram. As a hacked example, the following code would work if I could set the coordinates of the top and bottom of the false color image correctly (ymin and ymax), but the correct values seem to depend on the output device and its size. I realize that heatmaps use a 2x2

Hi, I have produced a dendrogram of categorical data in R using the hclust function, although the input was a dissimilarity matrix produced in SAS, as I have defined my own distances. The dendrogram is fine and I can view and use this. However, I was wondering if there is a method by which I can find out the optimal place to place groups, rather than relying on my visual analysis? I don't

Hello, I've been trying to figure out how to access the individual elements from an object of class phylo. I am reading in 201 trees created by paup as below. > read.nexus("A_30knj_200t.txt", tree.names= NULL) -> anj30 > anj30[1] $tree1 $edge [,1] [,2] [1,] "-1" "-2" [2,] "-2" "-3" [3,] "-3" "1"

Hello all, I wish to compare two dendrograms (representing Hierarchical Clusterings). My problems are several: 1) how do I manually create a dendrogram object ? That is, how can I reconstruct it as an "hclust" object that creates such a dendrogram, when all I have is the dendrogram image (but don't have the underlaying distance matrix that produced it) ? I see that there is a

Dear All, I wrote a function for cluster analysis to compute cophenetic correlations between dissimilarity matrices (using the VEGAN library) and cluster analyses of every possible clustering algorithm (SEE ATTACHED) http://old.nabble.com/file/p26288610/cor.coef.R cor.coef.R . As it is now, it is extremely long, and for the future I was hoping to find a more efficient way of doing this sort of

I am having trouble displaying a dendrogram of evolutionary relationships (a phylogram imported from the ape package) as the vertical component of a heatmap, but keeping the hierarchical clustering of the horizontal component. The relationships of the vertical component in the generated heatmap are not that of the dendrogram, although the ordering is. In more detail, I am attempting to generate

I am having difficulty getting the dynamic tree cut package to work. Given the data table "myddtable" LengthPlaceColorAge5HRed224ABlue205WGreen243GRed222GBlue236WGreen255ARed194H Blue23 I created a similarity matrix using DAISY and Gower metric and specified Place and Color columns as characters (since they are categorical variables) > dd.daisy<-daisy(myddtable, metric =

Is there a function available in R that implements Mojena's Upper Tail Rule or that draws a Mojena plot? I would also like to find a function that implements Duda and Hart's stopping rule. Finally with function cophenet how can I achieve a straightforward Cophenet correlation coefficient (i.e. one number for example 0.876) that gives the agreement between the structure of the

I'd like to get a measure of goodness of fit for a heirarchical clustering result from hclust. Something that would indicate the extent to which the dendrogram accurately represents the original dissimilarity matrix. Is there an easy way to do this? Or, does anyone have code for computing distances between nodes given an hclust structure? So far, my searches have come up dry. -- David

Dear r-list, I am trying to visually seperate the two main clusters of a dendrogram. The idea is to use: 'edgePar=list(lty=3)' for 'dend1[[1]]' and 'edgePar=list(lty=1)' for 'dend1[[2]]' I have not found a way to solve this. Any suggestions? Patrick hc <- hclust(dist(USArrests), "ave") (dend1 <- as.dendrogram(hc)) par(mfrow=c(2,2)) plot(dend1)

I know that within sum of squares, DB, sillhouette and cophenetic are indicators of clustering quality, but what indicators I need to observe when I choose attributes for kmeans? -- View this message in context: http://r.789695.n4.nabble.com/Feature-selection-for-kmeans-tp4657830.html Sent from the R help mailing list archive at Nabble.com.

Hi all, I'm having a problem where by I'm trying to use the NeatMap draw.dendrogram function as it is more versatile in placement/direction of dendrograms, instead of the limited plot function. Using plot I can get my dendrograms to display the species name for each leaf of the tree. But I cannot figure out how to make this happen using draw.dendrogram.. genetic<-

Dear List, I have a 47 species * 83 samples matrix containing percentage abundance data. I have two cluster analyses one of the samples and one of the species, and have ordered the rows and columns of the species by samples matrix according to these two cluster analyses. So far so good! Now what I want to do is create a plot with the species dendrogram at the top of the plot, the samples

I am having difficulty getting the dynamic tree cut package to work. Given the data table "myddtable" LengthPlaceColorAge5HRed224ABlue205WGreen243GRed222GBlue236WGreen255ARed194H Blue23 I created a similarity matrix using DAISY and Gower metric and specified Place and Color columns as characters (since they are categorical variables) > dd.daisy<-daisy(myddtable, metric =

Hi List, I am looking for a variable selection procedure with a forward-backward selection method. Firstly, it is meant to work with the cophenetic correlation coefficient (CPCC) and intended to find the variable combination with the highest cophenetic correlation. Secondly, it is aimed at Gower metric with wards method (though this could be easily extended) aimed at categorical data. What I