Hello, Are there ways in which using method = "pearson" and link = "average" or "complete" in the hcluster function of amap fails? In other words, is there a mathematical reason why the Pearson correlation as a distance metric yields undefined clustering, or did I encounter a bug? Full story: I've ran into an error while using the hclust2treeview function in the ctc package stemming from such a call to hcluster. Code: data <- read.table('file.dat', header=TRUE, sep='\t') clusterings <- hclust2treeview(data, file='filename.cdt', method='pearson', keep.hclust=TRUE) #this calls hr <- hcluster(coverage, method = "pearson", link = "average") internally I traced the problem to the 5 - 9th entries of hr$order, which had the value -5744, thus throwing the following error when the negative number was used as an index: Error in `[.default`(xj, i) : only 0's may be mixed with negative subscripts Calls: hclust2treeview ... r2cdt -> [ -> [.data.frame -> [ -> [.factor -> NextMethod Execution halted I tried using method = "euclidean", and no error appeared, but I would prefer using another distance metric or know why I can't use the Pearson correlation. My data file seemed to be correctly formatted and comprised a header line followed by a matrix of non-negative integers). I found this related help thread: http://r.789695.n4.nabble.com /hierarchical-clustering-with-pearson-s-coefficient-td4662788.html Thanks, Eric Liaw Stanford University, undergraduate student -- output of sessionInfo(): R version 2.15.2 (2012-10-26) Platform: x86_64-pc-linux-gnu (64-bit) locale: [1] C attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] ctc_1.32.0 amap_0.8-7 Biobase_2.14.0 loaded via a namespace (and not attached): [1] tools_2.15.2 -- Sent via the guest posting facility at bioconductor.org.