similar to: Hierarchical clustering using own distance matrices

Hi, I have tried looking at the archives but havent found any answer that works till now (Sorry if i have missed anything) I am a newbie to R and i am trying to carry out hierarchical clustering using hclust -> as.dendrogram and then plotting the results as a dendrogram using the plot function plot(object). My question is : In the function "plot", can one decrease the leaf label

Hi I have a distance matrix which is computed by user defined method. I would like to plot the dendrogram. I would like to use different color and want the leaves laying down bottom. The script like this. I am not familiar with R. I followed the example shown in http://stat.ethz.ch/R-manual/R-devel/library/stats/html/dendrogram.html dist.obj <- as.dist(matrix.distance) hc.obj <-

I am trying to learn how to format Ascii data files for scan or read into R. Precisely for a quickie project, I found some code (at end of this email) to do exactly what I need: To cluster and graph a dendrogram from package (stats). I am stuck on how to format a text file to run the script. I looked at the dataset USArrests (which would be replaced by my data and labels) using UltraEdit. That

I have a data set with 6 variables and 251 cases. The people who supplied me with this data set believe that it falls naturally into three groups, and have given me a rule for determining group number from these 6 variables. If I do scaled.stuff <- scale(stuff, TRUE, c(...the design ranges...)) stuff.dist <- dist(scaled.stuff) stuff.hc <- hclust(stuff.dist)

Dear all, i performed a clusteranalysis - which worked so far... i plotted the dendrogram and sooo many branches, a rough sketch would be enough ;) i tried max.levels therefore which worked, but not for the plot... i used the following plot(hcd,nodePar =nP, str(hcd,max.level=1)) the output on the terminal was: --[dendrogram w/ 2 branches and 196 members at h = 2.70] |--[dendrogram w/ 2

Hello, I am new to the R package. After I use R to perform the hierarchical clustering, I am only interested in retrieving the leaf nodes that share the last common ancestors. As illustrated below, I'd like to retrieve (B, C) as a cluster and then (D, E) as another cluster. Any chance to do this in R? Thanks! BTW, I just subscribed to this list (not sure if the subscription is

Hi There, I'm working on some cluster analyses on a large data-set using hclust with Wards method and Manhattan (city block) distance measures. I've created dendrograms to illustrate the clustering criteria, but would like to create a plot to examine for the classic elbow criterion to use in determining the best number of clusters. Ideally I'd like to plot percent variance explained

Hey group, I have a problem of drawing dendrogram as the result of my program written in C. My algorithm is a approximation algorithm for single linkage method. AS a result I will get the following data: [Average distance] [cluster A] [cluster B] For example: 42.593141 1 26 42.593141 4 6 42.593141 123 124 42.593141 4 113 74.244206 1 123 74.244206 4 133 74.244206 1 36 So far I have used C to

Dear R user, I am a biochemist/bioinformatician, at the moment working on protein clusterings by conformation similarity. I only started seriously working with R about a couple of months ago. I have been able so far to read my way through tutorials and set-up my hierarchical clusterings. My problem is that I cannot find a way to obtain information on the rooting of specific nodes, i.e. of

Core developers, I couldn't find any simple way to send a vector of colors to apply to each terminal in plot.dendrogram() or plot.hclust()---I asked R-help about it a few weeks ago and didn't get any response---so I hacked that functionality into the plot.dendrgram code (see below for hacked function plus examples).... Is there any chance this functionality could be added to the

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

Hi All, I have a question which does not pertain directly to the use of R but comes from my use of R! I have data which can be described as 3-dimensional e.g. (x,y,z), with no negative component. The suggested way to analyze this data is via multivariate techniques or by calculating what amounts to a levene's test on the data and then an ANOVA on the three components if the first test is

Hello All, i've a set of observations that is in the form : a, b, c, d, e, f 67.12, 4.28, 1.7825, 30, 3, 16001 67.12, 4.28, 1.7825, 30, 3, 16001 66.57, 4.28, 1.355, 30, 3, 16001 66.2, 4.28, 1.3459, 13, 3, 16001 66.2, 4.28, 1.3459, 13, 3, 16001 66.2, 4.28, 1.3459, 13, 3, 16001 66.2,

Hello, a. when I use hclust with the methods media, centroid, and mcquitty, and plot the results, the dendrograms have lines that are crossing each other. Is this ok? b. My next question refers to plot.dendrogram: How can I use parameters as "hang" or "cex" here? E.g. for st <- as.dendrogram(subtreeshc[[x]]) I would like to have something like this, where cex and hang

Hi All, i've problem to understand how to work with R to generate a hierarchical clustering my data are in a csv and looks like : idcode,count,temp,sal,depth_m,subs 16001,136,4.308,32.828,63.46,47 16001,109,4.31,32.829,63.09,49 16001,107,4.302,32.822,62.54,47 16001,87,4.318,32.834,62.54,48 16002,82,4.312,32.832,63.28,49 16002,77,4.325,32.828,65.65,46 16002,77,4.302,32.821,62.36,47

Dear List RGui Version : 2.3.0 User : 1 month I am having the *dendrogram plotting problem * The code i tried: >library(cluster) DD<-DataSetS01022 # 575 x 2 matrix > VC<-hclust(dist(DD),"ave") *Warning message: NAs introduced by coercion* ( what does it mean? Is that the problem?) > plot(VC,hang=-2) Output: http://roughjade.blogspot.com Can anyone guide me? Thanks

Dear everybody! In the function hclust, at each stage distances between clusters are recomputed by the Lance-Williams dissimilarity update formula according to the particular clustering method being used. Using "centroid" method, Lance-Williams recurrence formula works properly only for euclidean distance. How is it possible to use properly centroid method with manhattan distance ?

Hello everyone, I wanted to know if it was possible to change the color of certain leaves in a hclust object in order to make my graph more readable. I know I can color certain groups but I would like to enter a vector telling the plot function which leaves to color in which color. Thanks in advance, Eleni [[alternative HTML version deleted]]

Hi, I'm new to R; this is my second email to this forum. I have a dataset that looks like this: Gene A B C D A 511 6116 1515 1515 B 164 115 1515 494 C 21646 D

Hello, I want to use pearson's correlation as distance between observations and then use any centroid based linkage distance (ex. Ward's distance) When linkage distances are formed as the Lance-Williams recursive formulation, they just require the initial distance between observations. See here: http://en.wikipedia.org/wiki/Ward%27s_method It is said that you have to use euclidean