Hi Johannes, you mentioned dynamicTreeCut - the dynamic hybrid method works fine on your data. Just supply the dissimilarity matrix as well: I use the function plotDendroAndColors from WGCNA to show the results; if you don't want to use WGCNA, just leave out the last call.
library(WGCNA) set.seed(42) x <- c(rnorm(100,50,10),rnorm(100,200,25),rnorm(100,80,15)) y <- c(rnorm(100,50,10),rnorm(100,200,25),rnorm(100,150,25)) df <- data.frame(x,y) hc <- hclust(dist(df,method = "euclidean"), method="centroid") dm = as.matrix(dist(df,method = "euclidean")) plot(hc) labels = cutreeDynamic(hc, distM = dm, deepSplit = 2) # ..cutHeight not given, setting it to 115 ===> 99% of the (truncated) height range in #dendro. #..done. plotDendroAndColors(hc, labels) As you see, the algorithm found 3 clusters that seem right based on the dendrogram. Please look carefully at the help file for cutreeDynamic since the defaults may not be what you want. If you absolutely want to cut at a given height, it can be done as well, but the arguments will need some massaging. Best, Peter On Mon, Jul 14, 2014 at 4:42 AM, Johannes Radinger <johannesradin...@gmail.com> wrote: > Of course, > manually checking the number of clusters that are cut at a specific height > (e.g. by abline()) > is one possibility. However, this only makes sense for single trees, but is > not a feasible > approach for multiple model runs when hundreds of trees are built with many > cluster branches. > > Thus, I'd be nice if somebody knows a more programatic approach or another > package > that allows cutting "centroid"-trees. > > /Johannes > > > On Fri, Jul 11, 2014 at 4:19 PM, David L Carlson <dcarl...@tamu.edu> wrote: > >> The easiest workaround is the one you included in your original posting. >> Specify k= and not h=. Examine the dendrogram and decide how many clusters >> are at the level you want. You could add guidelines to the dendrogram with >> abline() to make it easier to see the number of clusters at various heights. >> >> >> >> plot(hc) >> >> abline(h=c(20, 40, 60, 80, 100, 120), lty=3) >> >> >> >> David C >> >> >> >> *From:* Johannes Radinger [mailto:johannesradin...@gmail.com] >> *Sent:* Friday, July 11, 2014 3:24 AM >> *To:* David L Carlson; R help >> *Subject:* Re: [R] Cutting hierarchical cluster tree at specific height >> fails >> >> >> >> Hi, >> >> >> >> @David: Thanks for the explanation why this does not work. This of >> >> course makes theoretically sense. >> >> >> >> However in a recent discussion >> >> ( >> http://stats.stackexchange.com/questions/107448/spatial-distance-between-cluster-means >> ) >> >> it was stated that "the 'reversals problem' of centroid method is >> >> not a serious reason to deactivate the option of 'tree cut'". Instead >> >> a warning message should be provided rather than a deactivation. >> >> >> >> So does anyone know how a tree that was created with "centroid" can still >> >> be cut at a specific height? I tried the package "dynamicTreeCut", but this >> >> also relies on cutree and consequently raises an error when used for >> cutting >> >> "centroid" trees. >> >> >> >> Does anyone know a work around and can provide a minimum working example? >> >> >> >> /Johannes >> >> >> >> On Wed, Jul 9, 2014 at 4:58 PM, David L Carlson <dcarl...@tamu.edu> wrote: >> >> To cut the tree, the clustering algorithm must produce consistently >> increasing height values with no reversals. You used one of the two options >> in hclust that does not do this. Note the following from the hclust manual >> page: >> >> "Note however, that methods "median" and "centroid" are not leading to a >> monotone distance measure, or equivalently the resulting dendrograms can >> have so called inversions (which are hard to interpret)." >> >> The cutree manual page: >> >> "Cutting trees at a given height is only possible for ultrametric trees >> (with monotone clustering heights)." >> >> Use a different method (but not median). >> >> ------------------------------------- >> David L Carlson >> Department of Anthropology >> Texas A&M University >> College Station, TX 77840-4352 >> >> >> -----Original Message----- >> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] >> On Behalf Of Johannes Radinger >> Sent: Wednesday, July 9, 2014 7:07 AM >> To: R help >> Subject: [R] Cutting hierarchical cluster tree at specific height fails >> >> Hi, >> >> I'd like to cut a hierachical cluster tree calculated with hclust at a >> specific height. >> However ever get following error message: >> "Error in cutree(hc, h = 60) : >> the 'height' component of 'tree' is not sorted (increasingly)" >> >> >> Here is a working example to show that when specifing a height in cutree() >> the code fails. In contrast, specifying the number of clusters in cutree() >> works. >> What is the exact problem and how can I solve it? >> >> x <- c(rnorm(100,50,10),rnorm(100,200,25),rnorm(100,80,15)) >> y <- c(rnorm(100,50,10),rnorm(100,200,25),rnorm(100,150,25)) >> df <- data.frame(x,y) >> plot(df) >> >> hc <- hclust(dist(df,method = "euclidean"), method="centroid") >> plot(hc) >> >> df$memb <- cutree(hc, h = 60) # this does not work >> df$memb <- cutree(hc, k = 3) # this works! >> >> plot(df$x,df$y,col=df$memb) >> >> >> Thank you for your hints! >> >> Best regards, >> Johannes >> >> [[alternative HTML version deleted]] >> >> ______________________________________________ >> R-help@r-project.org mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide >> http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. >> >> >> > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
