distanceMatrix {ClassDiscovery}R Documentation

Distance Matrix Computation


This function computes and returns the distance matrix determined by using the specified distance metric to compute the distances between the columns of a data matrix.


distanceMatrix(dataset, metric, ...)



A numeric matrix or an ExpressionSet


A character string defining the distance metric. This can be pearson, sqrt pearson, spearman, absolute pearson, uncentered correlation, weird, cosine, or any of the metrics accepted by the dist function. At present, the latter function accepts euclidean, maximum, manhattan, canberra, binary, or minkowski. Any initial substring that uniquely defines one of the metrics will work.


Additional parameters to be passed on to dist.


This function differs from dist in two ways, both of which are motivated by common practice in the analysis of microarray or proteomics data. First, it computes distances between column vectors instead of between row vectors. In a typical microarray experiment, the data is organized so the rows represent genes and the columns represent different biological samples. In many applications, relations between the biological samples are more interesting than relationships between genes. Second, distanceMatrix adds additional distance metrics based on correlation.


A distance matrix in the form of an object of class dist, of the sort returned by the dist function or the as.dist function.


It would be good to have a better name for the weird metric.


Kevin R. Coombes krc@silicovore.com

See Also

dist, as.dist


dd <- matrix(rnorm(100*5, rnorm(100)), nrow=100, ncol=5)
distanceMatrix(dd, 'pearson')
distanceMatrix(dd, 'euclid')
distanceMatrix(dd, 'sqrt')
distanceMatrix(dd, 'weird')
rm(dd) # cleanup

[Package ClassDiscovery version 3.4.0 Index]