hopach2tree {hopach} | R Documentation |
The MapleTree software (http://mapletree.sourceforge.net/) is an open source, cross-platform, visualization tool to graphically browse results of cluster analyses. The hopach2tree
function takes a data matrix, plus corresponding hopach
clustering output for genes and/or arrays, and writes the (.cdt, .gtr, and .atr) files needed to view these hierarchical clustering results in MapleTree. The function makeTree
is called internally by hopach2tree
.
hopach2tree(data, file = "HOPACH", hopach.genes = NULL, hopach.arrays = NULL, dist.genes = NULL, dist.arrays = NULL, d.genes = "cosangle", d.arrays = "euclid", gene.wts = NULL, array.wts = NULL, gene.names = NULL) makeTree(labels, ord, medoids, dist, side = "GENE")
data |
data matrix, data frame or ExpressionSet of gene expression measurements. Each column corresponds to an array, and each row corresponds to a gene. All values must be numeric. Missing values are ignored. |
file |
name for the output files (the extensions .cdt, .gtr and .atr will be added). |
hopach.genes |
output of the hopach function applied to genes (rows of data . If only arrays are clustered, hopach.genes can be NULL. There must be at least K=2 levels in the hopach final tree (ie: hopach.genes$final$labels greater than 1 digit) for a gtr file to be generated. |
hopach.arrays |
optional output of the hopach function applied to arrays (columns of data . There must be at least K=2 levels in the hopach final tree (ie: hopach.arrays$final$labels greater than 1 digit) for an atr file to be generated. |
dist.genes |
matrix of pair wise distances between all genes. All values must be numeric, and missing values are not allowed. If NULL, this matrix is computed using the metric specified by d.genes . Only needed if genes are clustered (hopach.genes!=NULL). |
dist.arrays |
matrix of pair wise distances between all arrays. All values must be numeric, and missing values are not allowed. If NULL, this matrix is computed using the metric specified by d.arrays . Only needed if arrays are clustered (hopach.arrays!=NULL). |
d.genes |
character string specifying the metric to be used for calculating dissimilarities between genes. The currently available options are "cosangle" (cosine angle or uncentered correlation distance), "abscosangle" (absolute cosine angle or absolute uncentered correlation distance), "euclid" (Euclidean distance), "abseuclid" (absolute Euclidean distance), "cor" (correlation distance), and "abscor" (absolute correlation distance). Advanced users can write their own distance functions and add these to the functions distancematrix() and distancevector() . |
d.arrays |
character string specifying the metric to be used for calculating dissimilarities between arrays. |
gene.wts |
an optional vector of numeric weights for the genes. |
array.wts |
an optional vector of numeric weights for the arrays. |
gene.names |
optional vector of names or annotations for the genes, which can be different from the row names of data . |
labels |
final cluster labels from a hopach object. |
ord |
final ordering from a hopach object. |
medoids |
final medoids matrix from a hopach object. |
dist |
gene or array distance matrix. |
side |
character string specifying if the tree is for genes ("GENE", default) or arrays ("ARRY"). |
The function hopach2tree
has no value. It writes up to three text files to the current working directory. A .cdt file is always produced. This file can be used to visualize the data matrix as a heat map in MapleTree or other viewers such as TreeView (http://rana.lbl.gov/EisenSoftware.htm), jtreeview (http://sourceforge.net/projects/jtreeview/), and GeneXPress (http://genexpress.stanford.edu/). When hopach.genes
!=NULL, a .gtr is produced, and gene clustering results can be viewed, including ordering the genes in the heat map according to the final level of the hopach
tree and drawing the dendogram for hierarchical gene clustering. Similarly, when hopach.arrays
!=NULL, an .atr file is produced and array clustering results can be viewed.
The function makeTree
is called internally by hopach2tree
to make the objects needed to write the MapleTree files for a gene and/or array HOAPCH clustering result.
Operating systems use different end of line characters. These characters can cause errors in MapleTree when files generated on one OS are visualized on another OS. Hence, hopach2tree
should be run on the same OS as MapleTree whenever possible.
Thank you to Lisa Simirenko <lsimirenko@lbl.gov> for providing HOPACH views in MapleTree, and to Karen Vranizan <vranizan@uclink.berkeley.edu> for her input.
The MapleTree software can be downloaded from: http://sourceforge.net/projects/mapletree/
Katherine S. Pollard <kpollard@soe.ucsc.edu>
van der Laan, M.J. and Pollard, K.S. A new algorithm for hybrid hierarchical clustering with visualization and the bootstrap. Journal of Statistical Planning and Inference, 2003, 117, pp. 275-303.
http://www.stat.berkeley.edu/~laan/Research/Research_subpages/Papers/hopach.pdf
hopach
, boothopach
, bootmedoids
, boot2fuzzy
#25 variables from two groups with 3 observations per variable mydata<-rbind(cbind(rnorm(10,0,0.5),rnorm(10,0,0.5),rnorm(10,0,0.5)),cbind(rnorm(15,5,0.5),rnorm(15,5,0.5),rnorm(15,5,0.5))) dimnames(mydata)<-list(paste("Var",1:25,sep=""),paste("Exp",1:3,sep="")) mydist<-distancematrix(mydata,d="cosangle") #compute the distance matrix. #clusters and final tree clustresult<-hopach(mydata,dmat=mydist) #write MapleTree files hopach2tree(mydata,hopach.genes=clustresult,dist.genes=mydist)