Performs hierarchical cluster analysis given a distance measure and an agglomeration method, and produces a dendrogram.
Dendrogram(featuredata, groupdata, saveplot = FALSE,
plotname = "dendrogram", savetype = c("png", "bmp", "jpeg", "tiff",
"pdf"), distmethod = "manhattan", aggmethod = "ward.D",
main = "Dendrogram", cex = 0.8, clust = FALSE, rect = FALSE,
nclust = NULL, height = NULL, bordercol = 2, ...)
A data frame in the featuredata format. This should have sample names in the first column to be read as row names and the metabolomics variables in the remaining columns.
A data frame or a table with optional sample names in the first column to be read as row names and group names in the following column.
A logical indication whether to save the dendrogram produced.
Name of the output file if the file is to be saved.
The required format for the plot to be saved in. Threre is a
choice of "png","bmp","jpeg","tiff","pdf"
type files.
The distance measure to be used. This must be one of
"euclidean
", "maximum
", "manhattan
", "canberra
",
"binary
" or "minkowski
".
The agglomeration method to be used. This should be one of
"ward
", "single
", "complete
", "average
", #ward -> ward.D
"mcquitty
", "median
" or "centroid
".
Plot title.
A numerical value giving the amount by which plotting text and symbols should be magnified relative to the default.
A logical indicating whether the results from heirarchical clustering should be grouped
A logical indicatng whether rectanges should be drawn highlighting the groups from clust above
The desired number of clusters for clust or rect.
The desifed height to obtain clusters for clust or rect. Either nclust or height must be supplied for clust or rect.
If rect=TRUE, a vector with border colors for the rectangles.
Arguments to be passed on to other methods.
A dendrogram plot and a list containing an object of class `hclust' and a vector with cluster membership if clust or rect is set to TRUE.
# NOT RUN {
data(mixdata) #unadjusted data
Dendrogram(mixdata$featuredata,mixdata$sampledata[,1])
# }
Run the code above in your browser using DataLab