similar to: Help!!! Agnes dendogram (Clustering)

Hello. I have the following distance matrix between 8 points: [1,] 0.000000 3.162278 7.280110 8.544004 7.071068 9.899495 6.403124 8.062258 [2,] 3.162278 0.000000 5.000000 6.403124 4.472136 8.944272 6.082763 8.062258 [3,] 7.280110 5.000000 0.000000 1.414214 1.000000 5.000000 4.242641 5.830952 [4,] 8.544004 6.403124 1.414214 0.000000 2.236068 4.123106 4.472136 5.656854 [5,] 7.071068 4.472136

Hello all! I am performingsome clustering analysis on microarray data using agnes{cluster} and I have created my own dissimilarity matrix according to a distance measure different from "euclidean" or "manhattan" etc. My question is, if I choose for example method="complete", how are the distances between the elements calculated? Are they taken form the dissimilarity

Hi, this is rather a (presumed) bug report than a question because I can solve my personal statistical problem by working with hclust instead of agnes. I have done a complete linkage clustering on a dist object dm with 30 objects with agnes (R 1.8.0 on RedHat) and I want to obtain the partition that results from a cut at height=0.4. I run > cl1a <- agnes(dm, method="complete")

Hi, this is rather a (presumed) bug report than a question because I can solve my personal statistical problem by working with hclust instead of agnes. I have done a complete linkage clustering on a dist object dm with 30 objects with agnes (R 1.8.0 on RedHat) and I want to obtain the partition that results from a cut at height=0.4. I run > cl1a <- agnes(dm, method="complete")

Hello, I had a question regarding clustering using the agnes() function from the 'cluster' package. I was wondering if anyone knew how I can identify cluster points after running the agnes function. For example, I created a dataset with points randomly scattered around (0,0), (0,1) and (1,0). After clustering, the dendrogram shows all the clustered points and I get the ordering and

I try to perform a clustering using an existing dissimilarity matrix that I calculated using distance (analogue) I tried two different things. One of them worked and one not and I don`t understand why. Here the code: not working example library(cluster) library(analogue) iris2<-as.data.frame(iris) str(iris2) 'data.frame': 150 obs. of 5 variables: $ Sepal.Length: num 5.1 4.9 4.7

Dear All, I am trying to find a way to plot a dendogram in reverse, that is, if the terminal leaves are labelled 1-10 bottom to top (or left to right), I would like to be able to plot it in a way such that if would display 10-1 bottom to top or left to right. Any idea how to achieve this? Thanks in advance, r. Dr. Rafael Najmanovich European Bioinformatics Institute Wellcome Trust

I am trying to make dendogram based on gene expression matrix , but getting some error: I countMatrix = read.table("count.row.txt",header=T,sep='\t',check.names=F) colnames(countMatrix) count_matrix <- countMatrix[,-1] # remove first column (gene names) rownames(count_matrix) <- countMatrix[,1] #added first column gene names as rownames) >

Hi, I'm trying to use the cluster package and I'm having some trouble... I always get the message: > myagnes <- agnes("datafile.dat") > Error: could not find function "agnes" the package cluster is listed in the library() command, and I can reach the help files from Agnes as well I know that this can be some really easy thing to fix, but right now I have no

Hello! I created a distances matrix for 13 objects using daisy (see the attached file). I am trying to clusteranalyse it using agnes but it's not working. What might be the problem: mydistances<-read.csv("Results of daisy.csv") mycluster<-agnes(mydistances, method="ward") I am getting: Error in agnes(mydistances, method = "ward") : NA/NaN/Inf in foreign

Hello does anyone know what algorithm is used to produce the hierarchical clustering in the gplots package using the function heatmap.2? I think it may be the complete linkage clustering algorithm, but I can't find a source that seems reliable. Thank you and sorry if I posted this in the wrong place. If I have, please let me know and I will move it to the appropriate list. -- View this

Dear All, I am trying to make dendogram based on gene expression matrix , but getting some error: I countMatrix = read.table("count.row.txt",header=T,sep='\t',check.names=F) colnames(countMatrix) count_matrix <- countMatrix[,-1] # remove first column (gene names) rownames(count_matrix) <- countMatrix[,1] #added first column gene names as rownames)

Dear all, I need to make dendogram from read count in a csv file across 34 samples including biological replicate. Please share R code or package to do this. Do I also need to normalized read count before using read data? Thanks [[alternative HTML version deleted]]

Hi, I want to know if there is a difference between the two hierarchical methods Agnes and hclust when there are used with the same method and the same metric on the same data! I ask this question because I executed the following program: hc <- hclust(dist(AGRIINSTTableFinaleCR), "ward") agnes<-agnes(dist(AGRIINSTTableFinaleCR),method="ward") And clusters are not the

Dear all, I am no stat wiz and I am just trying to use the AGNES algorithm at my very modest level of statistical of understanding. I have difficulties understanding the ouput from AGNES. My question is: how to interpret the output, especially how do you I know which cluster solution is the best? In SPSS, an Agglomeration Schedule table is produced and I used to look at the biggest jump between

Hi , I want to assign names to the rows in my matrix so that when I use the 'agnes' function from R cluster package , the dendogram that is produced represents the rows of the matrix. This way I would know what elements in the matrix are clustered together. But when I do the following, rownames(distF) <- paste("A",dim(distF)[1]) it gives the following error; Error in

I think are looking for the function 'cutree' from package mva checkout its documentation: > require(mva) > ?cutree pleanty of examples to do what you want. ############################################################################# Hi R lovers! I am using the agnes function of the package cluster to compute a hierarchical clustering. I'd like to know if somebody has ever

Hi, I'm mighty new to R. I'm using it on Windows. I'm trying to cluster using a distance matrix I created from the data on my own and called it D10.dist. I loaded the cluster package. Then tried the following command... > agnes("E:D10.dist", diss = TRUE, metric = "euclidean", stand = FALSE, > method = "average", par.method, keep.diss = n < 1000,

Hi all, I am creating dendrograms using agnes and was wondering if it is possible to add color to the leaves (and just the leaves). For example, in the documentation, they have an example using the "votes.repub" data set. If I wanted to make the word "Washington" green (and only Washington), is it possible and if so how? I can apply "summary" to the object

Dear R Users: I am new to R and I am trying to do a cluster analysis on a single continuous variable using the Agnes [Agglomerative Nesting (Hierarchical Clustering) ] in the Package ‘cluster’. I was able to apply this clustering method to my data: ward1 <- Agnes(balances, diss= FALSE, metric = "euclidean", stand = TRUE, method = "ward", keep.diss =TRUE, keep.data =